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Code-division multiple access
Code-division multiple access
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Code-division multiple access (CDMA) is a channel access method used by various radio communication technologies. CDMA is an example of multiple access, where several transmitters can send information simultaneously over a single communication channel. This allows several users to share a band of frequencies (see bandwidth). To permit this without undue interference between the users, CDMA employs spread spectrum technology and a special coding scheme (where each transmitter is assigned a code).[1][2]

CDMA optimizes the use of available bandwidth as it transmits over the entire frequency range and does not limit the user's frequency range.

It is used as the access method in many mobile phone standards. IS-95, also called "cdmaOne", and its 3G evolution CDMA2000, are often simply referred to as "CDMA", but UMTS, the 3G standard used by GSM carriers, also uses "wideband CDMA", or W-CDMA, as well as TD-CDMA and TD-SCDMA, as its radio technologies. Many carriers (such as AT&T, UScellular and Verizon) shut down 3G CDMA-based networks in 2022 and 2024, rendering handsets supporting only those protocols unusable for calls, even to 911.[3][4]

It can be also used as a channel or medium access technology, like ALOHA for example or as a permanent pilot/signalling channel to allow users to synchronize their local oscillators to a common system frequency, thereby also estimating the channel parameters permanently.

In these schemes, the message is modulated on a longer spreading sequence, consisting of several chips (0s and 1s). Due to their very advantageous auto- and crosscorrelation characteristics, these spreading sequences have also been used for radar applications for many decades, where they are called Barker codes (with a very short sequence length of typically 8 to 32).

For space-based communication applications, CDMA has been used for many decades due to the large path loss and Doppler shift caused by satellite motion. CDMA is often used with binary phase-shift keying (BPSK) in its simplest form, but can be combined with any modulation scheme like (in advanced cases) quadrature amplitude modulation (QAM) or orthogonal frequency-division multiplexing (OFDM), which typically makes it very robust and efficient (and equipping them with accurate ranging capabilities, which is difficult without CDMA). Other schemes use subcarriers based on binary offset carrier modulation (BOC modulation), which is inspired by Manchester codes and enable a larger gap between the virtual center frequency and the subcarriers, which is not the case for OFDM subcarriers.

History

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The technology of code-division multiple access channels has long been known.

United States

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In the US, one of the earliest descriptions of CDMA can be found in the summary report of Project Hartwell on "The Security of Overseas Transport", which was a summer research project carried out at the Massachusetts Institute of Technology from June to August 1950.[5] Further research in the context of jamming and anti-jamming was carried out in 1952 at Lincoln Lab.[6]

Soviet Union

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In the Soviet Union (USSR), the first work devoted to this subject was published in 1935 by Dmitry Ageev.[7] It was shown that through the use of linear methods, there are three types of signal separation: frequency, time and compensatory.[clarification needed] The technology of CDMA was used in 1957, when the young military radio engineer Leonid Kupriyanovich in Moscow made an experimental model of a wearable automatic mobile phone, called LK-1 by him, with a base station.[8] LK-1 has a weight of 3 kg, 20–30 km operating distance, and 20–30 hours of battery life.[9][10] The base station, as described by the author, could serve several customers. In 1958, Kupriyanovich made the new experimental "pocket" model of mobile phone. This phone weighed 0.5 kg. To serve more customers, Kupriyanovich proposed the device, which he called "correlator."[11][12] In 1958, the USSR also started the development of the "Altai" national civil mobile phone service for cars, based on the Soviet MRT-1327 standard. The phone system weighed 11 kg (24 lb). It was placed in the trunk of the vehicles of high-ranking officials and used a standard handset in the passenger compartment. The main developers of the Altai system were VNIIS (Voronezh Science Research Institute of Communications) and GSPI (State Specialized Project Institute). In 1963 this service started in Moscow, and in 1970 Altai service was used in 30 USSR cities.[13]

Uses

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A CDMA2000 mobile phone
  • Synchronous CDM (code-division 'multiplexing', an early generation of CDMA) was implemented in the Global Positioning System (GPS). This predates and is distinct from its use in mobile phones.
  • The Qualcomm standard IS-95, marketed as cdmaOne.
  • The Qualcomm standard IS-2000, known as CDMA2000, is used by several mobile phone companies, including the Globalstar network.[nb 1]
  • The UMTS 3G mobile phone standard, which uses W-CDMA.[nb 2]
  • CDMA has been used in the OmniTRACS satellite system for transportation logistics.

Steps in CDMA modulation

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CDMA is a spread-spectrum multiple-access technique. A spread-spectrum technique spreads the bandwidth of the data uniformly for the same transmitted power. A spreading code is a pseudo-random code in the time domain that has a narrow ambiguity function in the frequency domain, unlike other narrow pulse codes. In CDMA a locally generated code runs at a much higher rate than the data to be transmitted. Data for transmission is combined by bitwise XOR (exclusive OR) with the faster code. The figure shows how a spread-spectrum signal is generated. The data signal with pulse duration of (symbol period) is XORed with the code signal with pulse duration of (chip period). (Note: bandwidth is proportional to , where = bit time.) Therefore, the bandwidth of the data signal is and the bandwidth of the spread spectrum signal is . Since is much smaller than , the bandwidth of the spread-spectrum signal is much larger than the bandwidth of the original signal. The ratio is called the spreading factor or processing gain and determines to a certain extent the upper limit of the total number of users supported simultaneously by a base station.[1][2]

Generation of a CDMA signal

Each user in a CDMA system uses a different code to modulate their signal. Choosing the codes used to modulate the signal is very important in the performance of CDMA systems. The best performance occurs when there is good separation between the signal of a desired user and the signals of other users. The separation of the signals is made by correlating the received signal with the locally generated code of the desired user. If the signal matches the desired user's code, then the correlation function will be high and the system can extract that signal. If the desired user's code has nothing in common with the signal, the correlation should be as close to zero as possible (thus eliminating the signal); this is referred to as cross-correlation. If the code is correlated with the signal at any time offset other than zero, the correlation should be as close to zero as possible. This is referred to as auto-correlation and is used to reject multi-path interference.[18][19]

An analogy to the problem of multiple access is a room (channel) in which people wish to talk to each other simultaneously. To avoid confusion, people could take turns speaking (time division), speak at different pitches (frequency division), or speak in different languages (code division). CDMA is analogous to the last example where people speaking the same language can understand each other, but other languages are perceived as noise and rejected. Similarly, in radio CDMA, each group of users is given a shared code. Many codes occupy the same channel, but only users associated with a particular code can communicate.

In general, CDMA belongs to two basic categories: synchronous (orthogonal codes) and asynchronous (pseudorandom codes).

Code-division multiplexing (synchronous CDMA)

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The digital modulation method is analogous to those used in simple radio transceivers. In the analog case, a low-frequency data signal is time-multiplied with a high-frequency pure sine-wave carrier and transmitted. This is effectively a frequency convolution (Wiener–Khinchin theorem) of the two signals, resulting in a carrier with narrow sidebands. In the digital case, the sinusoidal carrier is replaced by Walsh functions. These are binary square waves that form a complete orthonormal set. The data signal is also binary and the time multiplication is achieved with a simple XOR function. This is usually a Gilbert cell mixer in the circuitry.

Synchronous CDMA exploits mathematical properties of orthogonality between vectors representing the data strings. For example, the binary string 1011 is represented by the vector (1, 0, 1, 1). Vectors can be multiplied by taking their dot product, by summing the products of their respective components (for example, if u = (a, b) and v = (c, d), then their dot product u·v = ac + bd). If the dot product is zero, the two vectors are said to be orthogonal to each other. Some properties of the dot product aid understanding of how W-CDMA works. If vectors a and b are orthogonal, then and:

Each user in synchronous CDMA uses a code orthogonal to the others' codes to modulate their signal. An example of 4 mutually orthogonal digital signals is shown in the figure below. Orthogonal codes have a cross-correlation equal to zero; in other words, they do not interfere with each other. In the case of IS-95, 64-bit Walsh codes are used to encode the signal to separate different users. Since each of the 64 Walsh codes is orthogonal to all other, the signals are channelized into 64 orthogonal signals. The following example demonstrates how each user's signal can be encoded and decoded.

Example

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An example of 4 mutually orthogonal digital signals

Start with a set of vectors that are mutually orthogonal. (Although mutual orthogonality is the only condition, these vectors are usually constructed for ease of decoding, for example columns or rows from Walsh matrices.) An example of orthogonal functions is shown in the adjacent picture. These vectors will be assigned to individual users and are called the code, chip code, or chipping code. In the interest of brevity, the rest of this example uses codes v with only two bits.

Each user is associated with a different code, say v. A 1 bit is represented by transmitting a positive code v, and a 0 bit is represented by a negative code −v. For example, if v = (v0, v1) = (1, −1) and the data that the user wishes to transmit is (1, 0, 1, 1), then the transmitted symbols would be

(v, −v, v, v) = (v0, v1, −v0, −v1, v0, v1, v0, v1) = (1, −1, −1, 1, 1, −1, 1, −1).

For the purposes of this article, we call this constructed vector the transmitted vector.

Each sender has a different, unique vector v chosen from that set, but the construction method of the transmitted vector is identical.

Now, due to physical properties of interference, if two signals at a point are in phase, they add to give twice the amplitude of each signal, but if they are out of phase, they subtract and give a signal that is the difference of the amplitudes. Digitally, this behaviour can be modelled by the addition of the transmission vectors, component by component.

If sender0 has code (1, −1) and data (1, 0, 1, 1), and sender1 has code (1, 1) and data (0, 0, 1, 1), and both senders transmit simultaneously, then this table describes the coding steps:

Step Encode sender0 Encode sender1
0 code0 = (1, −1), data0 = (1, 0, 1, 1) code1 = (1, 1), data1 = (0, 0, 1, 1)
1 encode0 = 2(1, 0, 1, 1) − (1, 1, 1, 1) = (1, −1, 1, 1) encode1 = 2(0, 0, 1, 1) − (1, 1, 1, 1) = (−1, −1, 1, 1)
2 signal0 = encode0 ⊗ code0
= (1, −1, 1, 1) ⊗ (1, −1)
= (1, −1, −1, 1, 1, −1, 1, −1)
signal1 = encode1 ⊗ code1
= (−1, −1, 1, 1) ⊗ (1, 1)
= (−1, −1, −1, −1, 1, 1, 1, 1)

Because signal0 and signal1 are transmitted at the same time into the air, they add to produce the raw signal

(1, −1, −1, 1, 1, −1, 1, −1) + (−1, −1, −1, −1, 1, 1, 1, 1) = (0, −2, −2, 0, 2, 0, 2, 0).

This raw signal is called an interference pattern. The receiver then extracts an intelligible signal for any known sender by combining the sender's code with the interference pattern. The following table explains how this works and shows that the signals do not interfere with one another:

Step Decode sender0 Decode sender1
0 code0 = (1, −1), signal = (0, −2, −2, 0, 2, 0, 2, 0) code1 = (1, 1), signal = (0, −2, −2, 0, 2, 0, 2, 0)
1 decode0 = pattern.vector0 decode1 = pattern.vector1
2 decode0 = ((0, −2), (−2, 0), (2, 0), (2, 0)) · (1, −1) decode1 = ((0, −2), (−2, 0), (2, 0), (2, 0)) · (1, 1)
3 decode0 = ((0 + 2), (−2 + 0), (2 + 0), (2 + 0)) decode1 = ((0 − 2), (−2 + 0), (2 + 0), (2 + 0))
4 data0=(2, −2, 2, 2), meaning (1, 0, 1, 1) data1=(−2, −2, 2, 2), meaning (0, 0, 1, 1)

Further, after decoding, all values greater than 0 are interpreted as 1, while all values less than zero are interpreted as 0. For example, after decoding, data0 is (2, −2, 2, 2), but the receiver interprets this as (1, 0, 1, 1). Values of exactly 0 mean that the sender did not transmit any data, as in the following example:

Assume signal0 = (1, −1, −1, 1, 1, −1, 1, −1) is transmitted alone. The following table shows the decode at the receiver:

Step Decode sender0 Decode sender1
0 code0 = (1, −1), signal = (1, −1, −1, 1, 1, −1, 1, −1) code1 = (1, 1), signal = (1, −1, −1, 1, 1, −1, 1, −1)
1 decode0 = pattern.vector0 decode1 = pattern.vector1
2 decode0 = ((1, −1), (−1, 1), (1, −1), (1, −1)) · (1, −1) decode1 = ((1, −1), (−1, 1), (1, −1), (1, −1)) · (1, 1)
3 decode0 = ((1 + 1), (−1 − 1), (1 + 1), (1 + 1)) decode1 = ((1 − 1), (−1 + 1), (1 − 1), (1 − 1))
4 data0 = (2, −2, 2, 2), meaning (1, 0, 1, 1) data1 = (0, 0, 0, 0), meaning no data

When the receiver attempts to decode the signal using sender1's code, the data is all zeros; therefore the cross-correlation is equal to zero and it is clear that sender1 did not transmit any data.

Asynchronous CDMA

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When mobile-to-base links cannot be precisely coordinated, particularly due to the mobility of the handsets, a different approach is required. Since it is not mathematically possible to create signature sequences that are both orthogonal for arbitrarily random starting points and which make full use of the code space, unique "pseudo-random" or "pseudo-noise" sequences called spreading sequences are used in asynchronous CDMA systems. A spreading sequence is a binary sequence that appears random but can be reproduced in a deterministic manner by intended receivers. These spreading sequences are used to encode and decode a user's signal in asynchronous CDMA in the same manner as the orthogonal codes in synchronous CDMA (shown in the example above). These spreading sequences are statistically uncorrelated, and the sum of a large number of spreading sequences results in multiple access interference (MAI) that is approximated by a Gaussian noise process (following the central limit theorem in statistics). Gold codes are an example of a spreading sequence suitable for this purpose, as there is low correlation between the codes. If all of the users are received with the same power level, then the variance (e.g., the noise power) of the MAI increases in direct proportion to the number of users. In other words, unlike synchronous CDMA, the signals of other users will appear as noise to the signal of interest and interfere slightly with the desired signal in proportion to number of users.

All forms of CDMA use the spread-spectrum spreading factor to allow receivers to partially discriminate against unwanted signals. Signals encoded with the specified spreading sequences are received, while signals with different sequences (or the same sequences but different timing offsets) appear as wideband noise reduced by the spreading factor.

Since each user generates MAI, controlling the signal strength is an important issue with CDMA transmitters. A CDM (synchronous CDMA), TDMA, or FDMA receiver can in theory completely reject arbitrarily strong signals using different codes, time slots or frequency channels due to the orthogonality of these systems. This is not true for asynchronous CDMA; rejection of unwanted signals is only partial. If any or all of the unwanted signals are much stronger than the desired signal, they will overwhelm it. This leads to a general requirement in any asynchronous CDMA system to approximately match the various signal power levels as seen at the receiver. In CDMA cellular, the base station uses a fast closed-loop power-control scheme to tightly control each mobile's transmit power.

In 2019, schemes to precisely estimate the required length of the codes in dependence of Doppler and delay characteristics have been developed.[20] Soon after, machine learning based techniques that generate sequences of a desired length and spreading properties have been published as well. These are highly competitive with the classic Gold and Welch sequences. These are not generated by linear-feedback-shift-registers, but have to be stored in lookup tables.

Advantages of asynchronous CDMA over other techniques

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Efficient practical utilization of the fixed frequency spectrum

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In theory CDMA, TDMA and FDMA have exactly the same spectral efficiency, but, in practice, each has its own challenges – power control in the case of CDMA, timing in the case of TDMA, and frequency generation/filtering in the case of FDMA.

TDMA systems must carefully synchronize the transmission times of all the users to ensure that they are received in the correct time slot and do not cause interference. Since this cannot be perfectly controlled in a mobile environment, each time slot must have a guard time, which reduces the probability that users will interfere, but decreases the spectral efficiency.

Similarly, FDMA systems must use a guard band between adjacent channels, due to the unpredictable Doppler shift of the signal spectrum because of user mobility. The guard bands will reduce the probability that adjacent channels will interfere, but decrease the utilization of the spectrum.

Flexible allocation of resources

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Asynchronous CDMA offers a key advantage in the flexible allocation of resources i.e. allocation of spreading sequences to active users. In the case of CDM (synchronous CDMA), TDMA, and FDMA the number of simultaneous orthogonal codes, time slots, and frequency slots respectively are fixed, hence the capacity in terms of the number of simultaneous users is limited. There are a fixed number of orthogonal codes, time slots or frequency bands that can be allocated for CDM, TDMA, and FDMA systems, which remain underutilized due to the bursty nature of telephony and packetized data transmissions. There is no strict limit to the number of users that can be supported in an asynchronous CDMA system, only a practical limit governed by the desired bit error probability since the SIR (signal-to-interference ratio) varies inversely with the number of users. In a bursty traffic environment like mobile telephony, the advantage afforded by asynchronous CDMA is that the performance (bit error rate) is allowed to fluctuate randomly, with an average value determined by the number of users times the percentage of utilization. Suppose there are 2N users that only talk half of the time, then 2N users can be accommodated with the same average bit error probability as N users that talk all of the time. The key difference here is that the bit error probability for N users talking all of the time is constant, whereas it is a random quantity (with the same mean) for 2N users talking half of the time.

In other words, asynchronous CDMA is ideally suited to a mobile network where large numbers of transmitters each generate a relatively small amount of traffic at irregular intervals. CDM (synchronous CDMA), TDMA, and FDMA systems cannot recover the underutilized resources inherent to bursty traffic due to the fixed number of orthogonal codes, time slots or frequency channels that can be assigned to individual transmitters. For instance, if there are N time slots in a TDMA system and 2N users that talk half of the time, then half of the time there will be more than N users needing to use more than N time slots. Furthermore, it would require significant overhead to continually allocate and deallocate the orthogonal-code, time-slot or frequency-channel resources. By comparison, asynchronous CDMA transmitters simply send when they have something to say and go off the air when they do not, keeping the same signature sequence as long as they are connected to the system.

Spread-spectrum characteristics of CDMA

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Most modulation schemes try to minimize the bandwidth of this signal since bandwidth is a limited resource. However, spread-spectrum techniques use a transmission bandwidth that is several orders of magnitude greater than the minimum required signal bandwidth. One of the initial reasons for doing this was military applications including guidance and communication systems. These systems were designed using spread spectrum because of its security and resistance to jamming. Asynchronous CDMA has some level of privacy built in because the signal is spread using a pseudo-random code; this code makes the spread-spectrum signals appear random or have noise-like properties. A receiver cannot demodulate this transmission without knowledge of the pseudo-random sequence used to encode the data. CDMA is also resistant to jamming. A jamming signal only has a finite amount of power available to jam the signal. The jammer can either spread its energy over the entire bandwidth of the signal or jam only part of the entire signal.[18][19]

CDMA can also effectively reject narrow-band interference. Since narrow-band interference affects only a small portion of the spread-spectrum signal, it can easily be removed through notch filtering without much loss of information. Convolution encoding and interleaving can be used to assist in recovering this lost data. CDMA signals are also resistant to multipath fading. Since the spread-spectrum signal occupies a large bandwidth, only a small portion of this will undergo fading due to multipath at any given time. Like the narrow-band interference, this will result in only a small loss of data and can be overcome.

Another reason CDMA is resistant to multipath interference is because the delayed versions of the transmitted pseudo-random codes will have poor correlation with the original pseudo-random code, and will thus appear as another user, which is ignored at the receiver. In other words, as long as the multipath channel induces at least one chip of delay, the multipath signals will arrive at the receiver such that they are shifted in time by at least one chip from the intended signal. The correlation properties of the pseudo-random codes are such that this slight delay causes the multipath to appear uncorrelated with the intended signal, and it is thus ignored.

Some CDMA devices use a rake receiver, which exploits multipath delay components to improve the performance of the system. A rake receiver combines the information from several correlators, each one tuned to a different path delay, producing a stronger version of the signal than a simple receiver with a single correlation tuned to the path delay of the strongest signal.[1][2]

Frequency reuse is the ability to reuse the same radio channel frequency at other cell sites within a cellular system. In the FDMA and TDMA systems, frequency planning is an important consideration. The frequencies used in different cells must be planned carefully to ensure signals from different cells do not interfere with each other. In a CDMA system, the same frequency can be used in every cell, because channelization is done using the pseudo-random codes. Reusing the same frequency in every cell eliminates the need for frequency planning in a CDMA system; however, planning of the different pseudo-random sequences must be done to ensure that the received signal from one cell does not correlate with the signal from a nearby cell.[1]

Since adjacent cells use the same frequencies, CDMA systems have the ability to perform soft hand-offs. Soft hand-offs allow the mobile telephone to communicate simultaneously with two or more cells. The best signal quality is selected until the hand-off is complete. This is different from hard hand-offs utilized in other cellular systems. In a hard-hand-off situation, as the mobile telephone approaches a hand-off, signal strength may vary abruptly. In contrast, CDMA systems use the soft hand-off, which is undetectable and provides a more reliable and higher-quality signal.[2]

Collaborative CDMA

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A novel collaborative multi-user transmission and detection scheme called collaborative CDMA[21] has been investigated for the uplink that exploits the differences between users' fading channel signatures to increase the user capacity well beyond the spreading length in the MAI-limited environment. The authors show that it is possible to achieve this increase at a low complexity and high bit error rate performance in flat fading channels, which is a major research challenge for overloaded CDMA systems. In this approach, instead of using one sequence per user as in conventional CDMA, the authors group a small number of users to share the same spreading sequence and enable group spreading and despreading operations. The new collaborative multi-user receiver consists of two stages: group multi-user detection (MUD) stage to suppress the MAI between the groups and a low-complexity maximum-likelihood detection stage to recover jointly the co-spread users' data using minimal Euclidean-distance measure and users' channel-gain coefficients. An enhanced CDMA version known as interleave-division multiple access (IDMA) uses the orthogonal interleaving as the only means of user separation in place of signature sequence used in CDMA system.

See also

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Notes

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References

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Further reading

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
Code-division multiple access (CDMA) is a for communication systems that enables multiple users to share the same physical channel simultaneously by assigning each a unique pseudorandom code sequence to distinguish their signals. This technique relies on spread-spectrum modulation, particularly (DS-SS), where the data signal is multiplied by a high-rate spreading code, expanding its bandwidth far beyond the original bandwidth to allow overlapping transmissions without interference. At the receiver, the intended signal is recovered by correlating the received composite with the matching code, while signals from other users, appearing as pseudonoise, are suppressed due to low properties of the codes. Originating from military spread-spectrum applications in the 1940s and 1950s—with parallel developments in the during the mid-20th century—for secure, jam-resistant communications, CDMA was adapted for commercial cellular use in the late 1980s by engineers, including Irwin Jacobs and . A pivotal 1991 paper by researchers demonstrated that CDMA could achieve significantly higher in cellular networks through universal frequency reuse and , outperforming traditional (FDMA) and (TDMA) systems. This led to the development of the IS-95 standard, approved by the in 1993, which became the basis for the 2G cdmaOne networks deployed commercially starting in 1995 in and later in the United States by carriers like Sprint and Verizon. CDMA's key advantages include enhanced capacity via soft capacity limits, seamless soft handoffs between base stations, and inherent resistance to multipath fading and interference, making it suitable for dense urban environments. It evolved into 3G standards such as (using 1.25 MHz channels with 1.22 Mcps chip rates) and wideband CDMA (WCDMA) in (using 5 MHz channels with 3.84 Mcps chip rates), supporting data rates up to several Mbps for voice, video, and services. Although CDMA networks have been largely phased out in favor of (OFDMA) in LTE and , with major carrier shutdowns occurring in the early , CDMA's foundational principles of code-based continue to inform advanced multiple-access schemes in modern wireless systems, including satellite communications and IoT networks.

Fundamentals

Definition and Core Principles

Code-division multiple access (CDMA) is a that enables multiple users to share the same frequency band simultaneously by assigning each user a unique spreading code to encode their data signal. This technique relies on spread-spectrum signaling, where the bandwidth of the original data signal is deliberately expanded to allow coexistence of multiple signals with minimal interference. The primary mechanism in CDMA is (DSSS), in which a pseudo-noise (PN) code—a sequence of bits with noise-like properties—is multiplied by the data signal to spread its spectrum across a wider bandwidth. PN codes, generated from deterministic algorithms, appear random and have low , enabling the signal to be distinguished from or other signals. The chip rate of the PN code, which determines the spreading, is significantly higher than the original data rate, typically by a factor of 100 or more. A core principle of CDMA is code , which ensures that the spreading codes assigned to different users are mutually orthogonal, thereby minimizing cross-interference when signals are superimposed. Examples include Walsh codes, derived from Hadamard matrices and providing perfect for synchronous systems, and , which offer good properties for asynchronous scenarios. This allows the receiver to separate user signals effectively within the shared . The spreading process can be expressed mathematically as the transmitted signal s(t)=d(t)c(t)s(t) = d(t) \cdot c(t), where d(t)d(t) is the data signal and c(t)c(t) is the spreading with values typically ±1. The gain GpG_p, which quantifies the interference rejection capability, is defined as Gp=RcRdG_p = \frac{R_c}{R_d}, the ratio of the chip rate RcR_c to the data rate RdR_d; higher values of GpG_p enhance the system's ability to support more users. At the receiver, despreading recovers the original data by correlating the received signal with the user's specific spreading code, which collapses the spread spectrum back to the narrowband data signal while treating other users' signals as uncorrelated noise. This process rejects interference from non-matching codes, as their correlation yields near-zero output, allowing the desired signal to emerge with amplified power relative to noise.

Comparison to Other Multiple Access Methods

Code-division multiple access (CDMA) differs fundamentally from other multiple access methods such as (FDMA), (TDMA), and (OFDMA) in how it allocates shared communication resources to multiple users. FDMA divides the available into non-overlapping frequency bands, assigning each user a dedicated sub-band to transmit continuously, which requires guard bands to prevent . TDMA, in contrast, allocates the entire bandwidth to users in non-overlapping time slots, allowing sequential transmissions within a frame, often combined with FDMA for hybrid systems like . OFDMA extends this by dividing the into orthogonal subcarriers and assigning subsets to users, enabling flexible allocation and high in broadband systems like LTE. Unlike these orthogonal methods, CDMA permits all users to transmit simultaneously over the same frequency band and time using unique spreading codes, relying on code orthogonality to distinguish signals at the receiver. A primary distinction lies in interference management and resource utilization. FDMA and TDMA minimize intra-system interference through physical separation of resources—frequency guards in FDMA and time guards in TDMA—avoiding the multi-user interference inherent in CDMA. CDMA's shared medium introduces the near-far problem, where a strong nearby signal can overwhelm weaker distant ones, necessitating sophisticated to maintain signal-to-interference ratios. OFDMA reduces interference via subcarrier but can suffer from inter-carrier interference in multipath environments without proper cyclic prefixes. While FDMA and TDMA provide predictable resource division, CDMA's code-based approach enhances spectrum reuse in cellular systems by allowing overlapping transmissions, though it demands higher receiver for despreading and multiuser detection.
ParameterFDMATDMACDMAOFDMA
Resource AllocationFrequency bandsTime slotsSpreading codesSubcarriers
Spectrum EfficiencyLow (due to guard bands)Moderate (slot overhead)High (code reuse)High (orthogonal subcarriers)
ComplexityLow (simple filtering)Moderate (timing sync)High (code correlation)Moderate (FFT processing)
Susceptibility to FadingHigh (narrowband fading)High (burst errors in slots)Low (rake receiver diversity)Low (frequency diversity)
Interference HandlingGuard bandsTime guardsPower control for near-farCyclic prefix for multipath
This table summarizes key parameters based on established analyses in systems. In channels, CDMA benefits from spread-spectrum processing and rake receivers that combine multipath components for diversity gain, outperforming FDMA's vulnerability and TDMA's sensitivity to timing errors. Analytical studies confirm CDMA's exceeds TDMA's under normalized conditions in cellular environments, with capacity gains from interference averaging. Hybrid systems have evolved to leverage CDMA's strengths alongside other methods; for instance, time-division synchronous code-division multiple access (TD-SCDMA), a standard developed in , integrates CDMA spreading with TDMA slotting to manage uplink access and reduce interference. OFDMA, while dominant in , contrasts with CDMA by offering superior resistance to multipath fading through OFDM modulation, though CDMA remains robust in spread-spectrum scenarios for voice-centric applications.

Historical Development

Early Work in the United States

The origins of code-division multiple access (CDMA) trace back to early spread-spectrum techniques developed during , when actress and composer patented a frequency-hopping system designed to guide radio-controlled torpedoes while evading jamming by German forces. Their 1942 invention, titled "Secret Communication System," synchronized frequency shifts between transmitter and receiver using piano-roll mechanisms to hop across 88 radio frequencies, providing a foundational concept for spreading signals over a wide bandwidth to enhance and resistance to interference—a precursor to the (DSSS) methods central to CDMA. Although the U.S. Navy did not implement it during the war, the patent influenced subsequent military research into anti-jam communications. In the 1950s and , U.S. military efforts advanced DSSS for s, with key developments at organizations like Sylvania Corporation and . Sylvania built the F9C spread-spectrum for the U.S. in the 1950s, which transmitted narrowband teletype signals using pseudonoise (PN) codes to spread the spectrum, enabling low-probability-of-intercept operations during the . This system, derived from Lincoln Laboratory's earlier NOMAC prototype—a pioneering DSSS implementation tested in 1949 and produced as the F9C—demonstrated robust interference rejection through processing gains exceeding 20 dB in military trials, allowing signals to operate effectively amid jamming attempts with interference-to-signal ratios over 20 dB. , established in 1958, contributed to related projects in the , integrating spread-spectrum principles into and defense systems for anti-jamming and low-detectability features, though much of this work remained classified. These efforts culminated in early DSSS patents and prototypes that prioritized spectrum spreading for military resilience, setting the stage for CDMA's evolution. The transition to commercial applications accelerated in the 1980s through innovations at , founded in 1985 by Irwin Jacobs and , who adapted military spread-spectrum concepts for cellular . Their work focused on DSSS to enable multiple users to share efficiently via unique orthogonal codes, leading to the IS-95 standard—commercially known as cdmaOne—adopted by the in July 1993. A pivotal milestone was Qualcomm's public demonstration on November 7, 1989, of a digital CDMA cellular system in , showcasing voice calls with soft handoff between cell sites and interference rejection capabilities inherited from military designs. This demo proved CDMA's viability for wide-area coverage, paving the way for regulatory support; in the mid-1990s, the auctioned Personal Communications Services (PCS) licenses, enabling CDMA deployment in the 1.9 GHz band as part of emerging networks.

Parallel Advances in the Soviet Union

In the 1930s, Soviet theoretical work laid early foundations for CDMA concepts, with Dmitry Ageev publishing in 1935 on linear methods for separating multiplexed signals, demonstrating through experiments that three types of signals could be distinguished in a shared channel using code-like —predating similar Western ideas. In the 1950s, Soviet engineers independently explored spread-spectrum techniques for enhancing resistance to jamming in and radio systems, driven by military needs during the early era. A notable early contribution came from Kupriyanovich, who in 1957 developed an experimental wearable model, LK-1, achieving a range of up to 20 km with a device weight of 3 kg. This work laid groundwork for practical mobile communications in non-cellular contexts, focusing on portability and basic anti-jamming properties. During the and , research at institutions such as the Soviet Academy of Sciences advanced theoretical and practical aspects of spread-spectrum multiplexing, particularly in developing code families for efficient signal separation in multi-user environments. The Altai system, introduced in 1963 as an early operational mobile radiotelephone network, exemplified these efforts in mobile applications; it supported up to 120 channels in and expanded to 30 cities by 1970, using to separate user signals and mitigate interference in urban settings. A key theoretical foundation was provided by V.A. Kotelnikov, whose work on the theory of optimum noise immunity established fundamental limits for in noisy channels, directly informing spread-spectrum designs by quantifying the trade-offs between bandwidth expansion and error resilience. Kotelnikov's multidimensional signal representation and capacity bounds, akin to Shannon's but predating it in some applications, enabled Soviet researchers to optimize spread-spectrum systems for high-interference scenarios, influencing subsequent code selection and modulation strategies. These advances found primary application in and satellite systems throughout the , where spread-spectrum's anti-jamming capabilities were critical for secure data links. Declassified documents from the 1980s reveal Soviet deployment of spread-spectrum techniques in and command systems for orbital assets, such as the Raduga series, to ensure reliable amid potential electronic warfare threats. Notably, early Soviet systems employed m-sequences (maximal-length pseudonoise sequences) for , leveraging their sharp properties to achieve peaks exceeding 10^4, which facilitated precise signal acquisition even in low signal-to-noise ratios. Post-Cold War highlighted how these Soviet innovations paralleled U.S. efforts, contributing to global recognition of spread-spectrum's versatility in multi-access schemes.

Technical Mechanisms

Spreading and Modulation Steps

In code-division multiple access (CDMA) systems, the process begins with channel coding to enhance error correction capabilities. The input data bits are encoded using techniques such as s or , which add redundancy to detect and correct transmission errors; for instance, in the IS-95 standard, a rate-1/2 with constraint length 9 is commonly applied to the before further processing. The next step involves spreading the encoded data signal across a wider bandwidth using a pseudo-noise (PN) code sequence, a process known as direct-sequence spreading. This is achieved by multiplying the data signal d(t)d(t) (typically at a lower ) with the high-rate chip sequence c(t)c(t) generated from the PN code, resulting in the spread signal s(t)=d(t)c(t)s(t) = d(t) \cdot c(t). The chip rate is significantly higher than the data rate—often by a factor of 128 or more—expanding the signal's bandwidth while maintaining the original data content; this spreading factor determines the processing gain and interference resistance of the system. Following spreading, the signal is modulated onto a carrier to prepare it for transmission. Common modulation schemes include binary (BPSK) or quadrature (QPSK), where the spread signal modulates the phase of the ; in IS-95 forward link implementations, QPSK is used to transmit the I and Q components separately after orthogonal Walsh code covering. This step shifts the signal to the desired frequency band, typically in the RF spectrum allocated for wireless communications. Power control is then applied to regulate the transmission power, ensuring that the received remains adequate despite varying path losses and interference from other users; this is critical in CDMA to prevent the near-far problem, where stronger signals overpower weaker ones. The modulated signal is amplified and transmitted over the air interface via the antenna. At the receiver, the process reverses: the incoming signal r(t)r(t) (which includes the desired spread signal plus and interference) is despread by multiplying it with the synchronized replica of the PN code c(t)c(t), yielding r(t)c(t)d(t)+r(t) \cdot c(t) \approx d(t) + low-pass filtered , thereby collapsing the bandwidth back to the original data rate and recovering the encoded bits for subsequent decoding. The end-to-end process can be visualized as a starting with input data bits entering the channel encoder, followed by interleaving (optional for burst mitigation), serial-to-parallel conversion if needed for multi-code transmission, spreading via PN multiplication, complex modulation to the carrier, power amplification, and transmission. At the receiver, synchronization acquisition—often using a pilot channel or for code alignment—precedes despreading, followed by matched filtering, de-interleaving, and decoding to output the recovered data bits. This sequential ensures robust in multipath and interference-prone environments.

Synchronous CDMA Operations

Synchronous code-division multiple access (CDMA), often referred to as code-division (CDM) in controlled environments, functions as a technique for scenarios involving fixed or precisely aligned users, such as the downlink transmission from a to multiple receivers. In this setup, all user signals maintain exact timing , enabling the separation of channels through orthogonal spreading codes without mutual interference. This contrasts with asynchronous variants by assuming perfect alignment, which is feasible when the transmitter controls the timing for all recipients. The core operation relies on the property of in spreading codes, where all users transmit simultaneously over the shared but can be distinguished at the receiver due to zero among codes under synchronized conditions. Codes from the Walsh-Hadamard matrix are commonly employed, as they form an orthogonal set ensuring no interference when the relative delay τ is zero. The between distinct codes cic_i and cjc_j (for iji \neq j) is defined as: Rij(τ)=kci(k)cj(kτ)R_{ij}(\tau) = \sum_{k} c_i(k) c_j(k - \tau) In synchronous CDMA, Rij(0)=0R_{ij}(0) = 0, resulting in interference I=0I = 0 for aligned signals. This eliminates multi-user interference (MAI) in ideal conditions, allowing clean despreading of each user's signal. A prominent example is the downlink in the IS-95 cellular standard, where the base station assigns unique orthogonal Walsh-Hadamard codes to up to 64 channels, broadcasting synchronized data streams to mobile users. Synchronization across base stations is achieved using GPS to align transmissions, preventing inter-cell interference and enabling efficient spectrum sharing. This approach supports higher user densities compared to non-orthogonal methods in controlled downlink scenarios. Under ideal synchronization with no multi-user interference, the system capacity is limited primarily by noise rather than inter-user effects, with the maximum number of users NN approximated by NPGEb/N0N \approx \frac{PG}{E_b/N_0}, where PGPG is the processing gain (equal to the spreading factor) and Eb/N0E_b/N_0 is the required energy per bit to ratio for target performance. This formula arises because the orthogonal structure allows up to PGPG users in theory, but practical limits incorporate the single-user Eb/N0E_b/N_0 threshold against thermal . Beyond downlinks, synchronous CDMA finds applications in wired and optical systems for high-density , such as in fiber-optic where multiple data streams share the medium with precise timing control to minimize and maximize throughput. For instance, direct-detection optical synchronous CDMA schemes utilize orthogonal codes to support bursty, high-speed transmissions over shared fibers.

Asynchronous CDMA Operations

In asynchronous CDMA systems, user transmissions occur without precise timing alignment, a common scenario in uplink channels of mobile networks where devices transmit independently from varying locations and distances. This lack of introduces timing offsets between signals, causing non-zero cross-correlations among spreading codes and generating multi-access interference (MAI) that degrades signal detection. Unlike synchronous CDMA operations, which serve as an ideal baseline assuming aligned transmissions, asynchronous modes must address these offsets to maintain reliable communication. To counter the challenges of MAI and related issues, asynchronous CDMA employs long pseudo-noise (PN) codes, such as Gold sequences, which are designed to have low auto-correlation and cross-correlation properties even under time misalignment. These sequences ensure that interference from other users approximates white noise, facilitating better despreading at the receiver. Complementing this, power control mechanisms dynamically adjust each user's transmit power to equalize received signal strengths at the base station, thereby mitigating the near-far effect where signals from nearby users dominate those from distant ones and amplify MAI. Receiver-side processing further enhances performance through the , which exploits by assigning "fingers" to resolve delayed signal replicas and combine them coherently. The Rake output is formed by weighting and summing these components as y=kαks(tτk),y = \sum_k \alpha_k \, s(t - \tau_k), where αk\alpha_k represents the complex channel gain for the kk-th path, s(t)s(t) is the spreading , and τk\tau_k is the delay of that path; this maximal ratio combining maximizes the . In asynchronous settings, such techniques help capture dispersed energy while suppressing interference. The capacity of asynchronous CDMA is inherently lower than in synchronized systems due to persistent MAI, typically approximated as NW/R1+ηN \approx \frac{W/R}{1 + \eta}, where NN is the number of supportable users, WW the system bandwidth, RR the data rate per user, and η\eta the interference factor capturing the residual MAI impact after mitigation. A practical illustration is the uplink in W-CDMA standards, where mobile stations transmit asynchronously using long scrambling codes, relying on the above methods to achieve viable multiuser capacity in real-world deployments.

Applications and Implementations

Role in Mobile and Wireless Standards

Code-division multiple access (CDMA) played a pivotal role in the evolution of second- and third-generation ( and ) mobile standards, enabling efficient spectrum use and higher capacity in networks. The IS-95 standard, developed in and standardized by the (TIA), introduced CDMA as a technology using 1.25 MHz channels and employing 64 orthogonal Walsh codes to support up to 64 simultaneous users per sector. This was extended in the family of standards by 3GPP2, maintaining the 1.25 MHz channel bandwidth for while enhancing data capabilities through multi-carrier operation and higher-order modulation, facilitating a smooth migration from IS-95 deployments. In parallel, the global 3G standard known as Wideband CDMA (W-CDMA) under the Universal Mobile Telecommunications System () framework, defined by , utilized a wider 5 MHz bandwidth and a chip rate of 3.84 Mcps to achieve peak data rates of up to 2 Mbps, with the core network evolving directly from infrastructure for seamless integration. A variant, Time Division CDMA (TD-CDMA), was specified for time-division duplex (TDD) operation in , allowing unpaired spectrum usage by alternating uplink and downlink in the same frequency band, particularly suited for indoor or asymmetric traffic scenarios. Subsequent enhancements under the (HSPA) evolutions, including HSPA+, built on W-CDMA's CDMA foundation to boost downlink speeds to 14 Mbps through techniques like higher-order modulation (16-QAM) and (HARQ), while maintaining compatibility with existing infrastructure. By 2010, CDMA-based technologies, encompassing both cdma2000 and W-CDMA/ variants, accounted for a substantial portion of global 3G deployments, with holding over 50% of the worldwide 3G subscriber base in key regions like the and . These standards paved migration paths to Long-Term Evolution (LTE) by refarming spectrum and leveraging shared core elements, enabling operators to transition from CDMA air interfaces to OFDMA-based without full network overhauls.

Uses in Non-Telecommunications Fields

Code-division multiple access (CDMA) principles have been adapted for global positioning systems (GPS), where satellite signals employ direct-sequence spread spectrum techniques akin to CDMA to enable multiple satellites to share the same frequency band without interference. In GPS, the civilian-accessible coarse/acquisition (C/A) code, generated at a 1.023 MHz chipping rate, modulates the L1 carrier (1575.42 MHz) for pseudorandom noise spreading, allowing receivers to distinguish signals from different satellites by correlating with unique Gold codes assigned to each. The military precision (P(Y)) code, an encrypted version of the original P code with a 10.23 MHz chipping rate, operates on both L1 and L2 (1227.60 MHz) frequencies in phase quadrature with the C/A code on L1, providing enhanced accuracy and anti-spoofing for authorized users. This CDMA-like structure ensures robust signal acquisition and tracking in noisy environments, supporting global navigation with minimal inter-satellite interference. In , CDMA facilitates secure, jam-resistant links by spreading signals across a wide bandwidth, making them difficult to detect or disrupt without knowledge of the specific spreading codes. Hybrid systems combining CDMA with (FHSS) further enhance resistance to jamming; for instance, code-hopping CDMA (CH-CDMA) dynamically changes spreading codes at high rates to evade or partial-band jammers, achieving processing gains that maintain link integrity under interference levels exceeding 20 dB. These techniques originated in military applications for tactical radios and links, where the low probability of intercept and anti-jam properties of CDMA protect sensitive data transmission in contested environments. CDMA has been integrated into wireless sensor networks (WSNs) for low-power (IoT) applications, particularly in scenarios where multiple nodes transmit correlated environmental data to a without excessive . Receiver-assigned CDMA (RA-CDMA) protocols assign unique codes to sensors upon association, enabling simultaneous uploads and reducing collision risks in dense deployments; this supports energy-efficient clustering, where aggregated data from nearby nodes is fused before transmission, extending network lifetime in battery-constrained setups like remote monitoring. In industrial IoT contexts, such as factory automation, RA-CDMA achieves low-latency aggregation with throughputs up to several kbps while keeping power draw below 10 mW per node. Optical CDMA (OCDMA) extends CDMA concepts to fiber-optic networks for all-optical switching and , using wavelength-division coding to assign unique spectral signatures to packets without optical-electrical conversion. In OCDMA systems, prime-hop codes or modified quadratic congruence sequences encode across multiple wavelengths (e.g., spaced at 100 GHz in the C-band), enabling asynchronous access and contention resolution in high-speed LANs or metropolitan networks. Wavelength-hopping variants combine time and spectral domains for reduced multiple-access interference, supporting exceeding 10 Gbps per user in multi-wavelength setups with encoder/decoder arrays based on arrayed gratings. These implementations provide scalable, label-free for photonic packet-switched architectures. Underwater acoustic networks leverage CDMA for multi-node ranging and communication in challenging multipath channels, where low frequencies (below 10 kHz) limit bandwidth but require robust multi-user access over long distances. Direct-sequence CDMA allows simultaneous transmissions from multiple autonomous underwater vehicles or sensors, using pseudonoise codes for code-division ranging that resolves positions with centimeter-level precision at ranges up to 10 km in shallow water. For example, hybrid path-oriented CDMA-MAC protocols enable efficient slot allocation for ranging pings, achieving network throughputs of 100-500 bps while mitigating inter-symbol interference through rake receivers adapted for acoustic multipath. This application supports oceanographic surveys and subsea monitoring by enabling collision-free data collection from distributed nodes.

Performance Characteristics

Advantages in Spectrum Efficiency

One of the primary advantages of code-division multiple access (CDMA) in spectrum efficiency stems from its universal frequency reuse pattern, which has a reuse factor of 1. This means that the entire available spectrum can be reused in every cell without the need for partitioning frequencies across cells, unlike (FDMA) systems that typically employ a 7-cell reuse pattern to avoid . As a result, CDMA systems can achieve substantially higher capacity per unit area by fully utilizing the spectrum in all cells simultaneously, leading to improved overall throughput in dense deployments. Central to this efficiency is the processing gain inherent in CDMA's spread- technique, which quantifies the system's ability to distinguish the desired signal from interference. The processing gain is given by Gp=10log10(RcRb)G_p = 10 \log_{10} \left( \frac{R_c}{R_b} \right) dB, where RcR_c is the chip rate and RbR_b is the information . This gain effectively spreads the signal over a wider bandwidth, allowing the receiver's despreading process to boost the and suppress noise from other users sharing the same band. Consequently, CDMA can support more than 10 times the number of simultaneous users in the same compared to multiple access methods like FDMA or TDMA, where interference limits are more stringent without such spreading. CDMA's capacity is characterized as "soft," meaning it degrades gracefully as user load increases, rather than enforcing hard limits that block additional connections once a fixed threshold is reached, as seen in (TDMA) systems. In CDMA, adding users incrementally reduces the signal quality for all but maintains connectivity, enabling higher average utilization of resources under fluctuating traffic conditions. This property arises from the statistical nature of interference management via orthogonal codes and , optimizing use without rigid slot or frequency assignments. Additionally, CDMA facilitates flexible by dynamically assigning transmission power levels and spreading codes to individual users based on their channel conditions and needs. This adaptability ensures efficient sharing, as resources are not wasted on underutilized fixed allocations but instead adjusted in real-time to maximize throughput across varying user demands. For example, in the standard, this contributes to higher for voice services compared to systems, often achieving several times the capacity in equivalent .

Challenges and Mitigation Techniques

One of the primary challenges in CDMA systems is the near-far problem, where signals from nearby users overpower those from distant users at the receiver, leading to disproportionate interference and degraded performance for weaker signals. This issue is mitigated through mechanisms, including open-loop estimation based on downlink and closed-loop adjustments via feedback commands from the , which dynamically regulate transmit power to maintain balanced received signal strengths. In IS-95, closed-loop operates at 800 Hz with 1 dB adjustment steps, while systems like and WCDMA use rates up to 1600 Hz for finer control, enabling effective resolution of the near-far effect in practical deployments. Multi-user interference (MAI), arising from non-orthogonal spreading codes among simultaneous users, further limits system performance by causing cross-talk that increases error rates, particularly in asynchronous operations where timing misalignments exacerbate the interference. Mitigation relies on multi-user detection (MUD) algorithms, which jointly process signals from all users to suppress MAI, unlike conventional single-user matched filtering. Seminal work by Sergio Verdú established the foundations of optimal MUD, including the decorrelating detector, a linear suboptimal approach that inverts the correlation matrix of spreading codes to eliminate MAI entirely in noise-free conditions, though it suffers from noise enhancement in low-SNR scenarios. Practical implementations, such as successive interference cancellation variants of MUD, have been integrated into CDMA receivers to improve capacity by 20-50% in moderate user loads. Self-interference due to , where delayed signal replicas overlap and distort the desired waveform, poses another significant hurdle in CDMA, reducing signal-to-interference ratios in dispersive environments. This is addressed by the , which exploits multipath diversity by correlating the received signal with delayed versions of the spreading code to resolve distinct paths, followed by to weight and sum these components optimally based on their signal strengths and noise variances. Originating from early concepts and adapted for CDMA in systems like IS-95, the with provides diversity gain against in typical urban channels with multiple resolvable paths. CDMA capacity is inherently limited, with the reverse link often serving as the bottleneck due to mobile transmit power constraints and higher vulnerability to interference compared to the forward link, where base stations can employ higher power and antenna techniques. The pole capacity, representing the theoretical maximum achievable throughput before , for a voice-dominated reverse link is given by C=W(EbN0)v,C = \frac{W}{ \left( \frac{E_b}{N_0} \right) v }, where WW is the chip rate bandwidth, EbN0\frac{E_b}{N_0} is the required energy per bit to noise spectral density ratio, and vv is the voice activity factor (typically 0.3-0.5 for speech, accounting for silence periods). This formula highlights how activity gating increases effective capacity by reducing average interference during non-transmission intervals, though practical limits are 50-70% of the pole due to other impairments. The high of advanced CDMA techniques, such as multi-user detection and precise , has contributed to its gradual replacement by (OFDMA) in 4G LTE and standards, where simpler per-subcarrier processing avoids the exponential growth in receiver demands with user count. While CDMA offered robust spectrum sharing, its sensitivity to synchronization errors and interference management overhead made scaling to data rates challenging, prompting the industry shift toward OFDMA for higher efficiency and lower complexity in multi-antenna environments.

Advanced and Collaborative Forms

Collaborative CDMA Protocols

Collaborative CDMA protocols enable users in a network to act as relays, forwarding signals through distributed spreading codes to mitigate outage probabilities in channels. This exploits CDMA's multiuser detection to handle interference from relayed transmissions, creating virtual antenna arrays that enhance signal reliability without dedicated . These protocols primarily employ amplify-and-forward (AF) or decode-and-forward (DF) relaying strategies combined with orthogonal code assignment. In AF relaying, the relay amplifies the received signal and retransmits it using a code orthogonal to the source's, preserving the signal's analog form while adding minimal processing delay. DF relaying, conversely, involves the relay decoding the source message, re-encoding it, and forwarding with an orthogonal complementary code to minimize cross-interference at the destination. Orthogonal codes ensure that cooperative signals can be separated effectively via despreading, supporting simultaneous multiuser access. In ad-hoc networks, collaborative CDMA improves diversity by distributing transmission paths across users, yielding substantial (BER) reductions through higher-order diversity. The cooperation factor, often represented by the number of active relays, elevates the diversity order GcG_c, providing robustness against . For instance, in wireless mesh networks, collaborative CDMA achieves capacity gains over non-cooperative schemes by leveraging user relaying to boost throughput and efficiency in multi-hop scenarios. Post-2000s research has emphasized energy-efficient variants of these protocols for IoT deployments, incorporating centralized and distributed optimization in multi-carrier DS-CDMA systems to minimize power usage via adaptive selection and allocation. These advancements address IoT's stringent constraints, enabling prolonged operation in dense, resource-limited environments.

Integration with Emerging Technologies

In fifth-generation (5G) New Radio (NR) systems, code-division multiple access (CDMA) principles have been hybridized with non-orthogonal multiple access (NOMA) schemes to enhance user multiplexing in massive multiple-input multiple-output () environments. Code-domain NOMA, a direct extension of CDMA, employs spreading codes to allow overlapping among users, improving and supporting higher connectivity densities compared to orthogonal methods. This integration leverages CDMA's interference management capabilities alongside massive MIMO's , enabling better sum-rate performance in multi-user scenarios. For instance, systematic reviews of NOMA variants highlight how code-based power allocation in mitigates inter-user interference while maintaining low complexity in massive MIMO deployments. In millimeter-wave (mmWave) communications, CDMA techniques facilitate code-based user separation to complement in high-frequency bands, addressing challenges like beam squint and limited . By assigning unique spreading codes to users within narrow beams, CDMA enables robust multi-user detection amid directional transmissions, reducing multi-access interference without relying solely on spatial isolation. This hybrid approach is particularly effective in beyond-5G (B5G) architectures, where concentrates energy but requires additional orthogonalization for dense user groups. Research on interference mitigation in B5G networks demonstrates that combining CDMA with achieves superior error rates and throughput in mmWave scenarios, outperforming pure spatial division methods. For (IoT) and ultra-reliable low-latency communication (URLLC) applications in , low-density CDMA (LD-CDMA) signatures enable grant-free access by allowing devices to transmit sporadically without scheduling overhead. LD-CDMA uses sparse spreading sequences to spread symbols over low-density chips, facilitating efficient multi-user detection via compressive sensing or algorithms at the receiver. This is crucial for massive IoT connectivity, where thousands of devices require low-latency, reliable access; surveys on grant-free NOMA for IoT note that LD-CDMA-inspired schemes achieve near-optimal detection performance with reduced pilot overhead, supporting URLLC's stringent requirements of 1 ms latency and 99.999% reliability. Looking toward future trends, quantum-secure CDMA variants incorporate code-based to protect against quantum attacks, building on classical CDMA for secure multi-user quantum networks. Proposed quantum CDMA (q-CDMA) protocols use chaotic encoding and to distribute entanglement over code-division channels, ensuring secure resistant to . In parallel, 2020s research explores non-orthogonal schemes like NOMA for terahertz (THz) communications to address molecular absorption and high . These efforts, including THz-NOMA for machine-type communications, aim to enable terabit-per-second rates for short-range, high-density applications in . Additionally, 3GPP Release 17 (2022) enhances NR sidelink for (V2X) services, including improvements in reliability, power saving, and coverage for direct communications.

References

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