Multiple Access Channel Research Articles

Interference Management of Analog Function Computation in Multicluster Networks

Computation over multiple access channels (CoMAC) has been proposed to solve the problem of spectrum scarcity in wireless networks, which combines communication and computation efficiently using the superposition property of wireless channels. In this paper, we consider a multi-cluster CoMAC network, whose performance is affected by the inter-cluster interference and the non-uniform fading. To minimize the sum mean squared error of signals aggregated at different fusion centers (FCs), we propose a transceiver design for multi-cluster CoMAC. Specifically, we adopt a uniform-forcing transmitter design to formulate the receiver design as a quadratic sum-of-ratios problem with nonconvex quadratic constraints. Then, we propose a branch-and-bound algorithm to find its optimal solution with a given error tolerance. To solve the problem in a decentralized way, we develop a distributed algorithm based on the primal decomposition theory. Each subproblem is solved by using the successive convex approximation method. Further combining Lagrange duality, we derive the optimal solution structure of each subproblem, based on which we can find the solution with lower complexity. Simulation results demonstrate the effectiveness of the proposed distributed transceiver design.

Analysis and Design of Short Analog Fountain Codes for the Multiple Access Channel

In this letter, we design and analyse analog fountain codes (AFC) for the multiple access channel (MAC). First, we present several encoding schemes, including the superposition coding and joint encoding, and decoding schemes, including successive interference cancellation and joint decoding, for multiple access AFC (MA-AFC). We propose different combinations of encoding and decoding schemes for MA-AFC and evaluate their performance in terms of block error rate (BLER) to determine which combination has the best performance. We propose a density evolution (DE) based framework to track the evolution of messages exchanged between check nodes and variable nodes in the iterative joint belief propagation (BP) decoder of MA-AFC. With the proposed DE framework, we formulate optimisation problems to find the optimal AFC code parameters, specifically the weight set, which minimises the bit error rate at a given signal-to-noise ratio (SNR). Simulation results show that the AFC code with the optimised parameters outperforms existing AFC code designs in the multiple access scenario.

A New Rate Splitting Strategy for Uplink CR-NOMA Systems

In uplink non-orthogonal multiple access (NOMA) channels, the existing cooperative successive interference cancellation (SIC) and power control (PC) schemes lack the capability of achieving the full capacity region, which restricts the outage performance of uplink NOMA users. For the uplink cognitive radio inspired NOMA system, we propose a new rate splitting (RS) strategy to maximize the achievable rate of the secondary user without deteriorating the primary user's outage performance. Based on the interference threshold and its own channel gain, the secondary user adaptively conducts RS, transmit power allocation and SIC, which utilizes the transmit power efficiently. The closed-form expression for the outage probability is derived for the secondary user. Numerical results show that the proposed RS scheme achieves the best outage performance for the secondary user among the existing cooperative SIC and PC schemes.

Zero-Error Capacity Regions of Noisy Networks

This paper presents the first systematic study of the zero-error capacity regions of noisy networks. First, we consider two simple such networks, each consisting of a stationary memoryless multiple access channel with two binary inputs and one discrete output. There are two users in each network. Each of the two users transmits a message through the network, and the sink(s) of the network can decode both messages with zero error. A graph is used to represent the distinguishability of the inputs of the channel, and a <i>graph set</i> is used to represent the distinguishability of the inputs of the network. We show that for two networks represented by the same graph set, their zero-error capacity regions are the same. We list all the possible graph sets for the two networks and determine the zero-error capacity regions for some of these graph sets. Based on this result, we explore a relation between graph theory and set theory, and then redefine the <i>cancellative pair of families of subsets</i>. We further extend the problem formulation to a general network called the <i>parallel network</i>, which may consist of more than one channel with multiple inputs and multiple outputs.

Secrecy Rate Region Enhancement in Multiple Access Wiretap Channel

It is commonly known that physical layer security is achieved with a trade-off in terms of the achievable rate. Hence, security constraints generate rate losses in wiretap channels. To mitigate such rate losses in multi-user channels, we propose a coding/decoding scheme for multi-user multiple access wiretap channel (MAC-WT), where previously transmitted messages are used as a secret key to enhance the secrecy rates of the transmitting users, until the usual Shannon capacity region of a multiple access channel (MAC) is achieved without the secrecy constraint. With this coding scheme, all messages transmitted in the recent past are secure with respect to all the information of the eavesdropper till now. To achieve this goal, we introduce secret key buffers at both the users and the legitimate receiver. Finally, we consider a fading MAC-WT and show that with this coding/decoding scheme, we can achieve the capacity region of a fading MAC channel (in the ergodic sense).

The Quantum Multiple-Access Channel With Cribbing Encoders

Communication over a quantum multiple-access channel (MAC) with cribbing encoders is considered, whereby Transmitter 2 performs a measurement on a system that is entangled with Transmitter 1. Based on the no-cloning theorem, perfect cribbing is impossible. This leads to the introduction of a MAC model with noisy cribbing. In the causal and non-causal cribbing scenarios, Transmitter 2 performs the measurement before the input of Transmitter 1 is sent through the channel. Hence, Transmitter 2's cribbing may inflict a "state collapse" for Transmitter 1. Achievable regions are derived for each setting. Furthermore, a regularized capacity characterization is established for robust cribbing, i.e. when the cribbing system contains all the information of the channel input. Building on the analogy between the noisy cribbing model and the relay channel, a partial decode-forward region is derived for a quantum MAC with non-robust cribbing. For the classical-quantum MAC with cribbing encoders, the capacity region is determined with perfect cribbing of the classical input, and a cutset region is derived for noisy cribbing. In the special case of a classical-quantum MAC with a deterministic cribbing channel, the inner and outer bounds coincide.

Multiple Access Channel Resolvability Codes From Source Resolvability Codes

We show that the problem of code construction for multiple access channel (MAC) resolvability can be reduced to the simpler problem of code construction for source resolvability. Specifically, we propose a MAC resolvability code construction that relies on a combination of multiple source resolvability codes, used in a black-box manner, and leverages randomness recycling implemented via distributed hashing and block-Markov coding. Since explicit source resolvability codes are known, our results also yield the first explicit coding schemes that achieve the entire MAC resolvability region for any discrete memoryless multiple-access channel with binary input alphabets.

Performance analysis of one‐source‐with‐one‐helper transmission over shadowed κ$\kappa$‐μ$\mu$ fading multiple access channels

The performance of correlated sources transmission over multiple access shadowed κ $\kappa$ - μ $\mu$ fading channels is investigated, in which one of the correlated sources needs to be recovered at the destination, whereas the other serves as a helper. The sufficient condition for lossless coding is determined by the intersection of the modified Slepian–Wolf region and the multiple access channel region. The outage probability upper bounds are derived based on the sufficient condition, with the Gaussian codebook capacity and the constellation constrained capacity, respectively. The difference between the outage probabilities derived with the two kinds of capacities is found to be very minor, when the spectrum efficiency or source rate is low; however, with high spectrum efficiency or high source rate, such difference becomes significant. A closed-form outage approximation is also obtained at the high signal-to-noise ratio region. The accuracy of the analytical results is verified by the Monte-Carlo simulations. It is found that shadowing significantly affects the outage performance, however, it has no effect on the diversity gain. Furthermore, the power allocation between the source and the helper is studied to minimize the outage probability and it is found that generally more power should be allocated to the helper in the case with higher source-helper correlation.

Self-Secure Capacity-Achieving Feedback Schemes of Gaussian Multiple-Access Wiretap Channels With Degraded Message Sets

Self-Secure Capacity-Achieving Feedback Schemes of Gaussian Multiple-Access Wiretap Channels With Degraded Message Sets

Power Management Strategies in Energy-Harvesting Wireless Sensor Networks

Power management strategies are extremely important in Wireless Sensor Networks (WSNs). The objective is to make the nodes operate as long as possible. In the same context, in this article, our aim is to provide the optimal transmission power to maximize the network lifetime using the Orthogonal Multiple Access Channel (OMAC) in Harvesting System (HS). We consider that the nodes have direct communication with a Fusion Center (FC) with causal Channel Side Information (CSI) at the sender and receiver.We begin the analysis by considering a single transmitter node powered by a rechargeable battery with limited capacity energy. Afterward, we generalize the analysis with M transmitter nodes. In both cases, the transmitters are able to harvest energy from nature.Eventually, we show the viability of our approach in simulations results.

On the Age of Information in a Two-User Multiple Access Setup.

This work considers a two-user multiple access channel in which both users have Age of Information (AoI)-oriented traffic with different characteristics. More specifically, the first user has external traffic and cannot control the generation of status updates, and the second user monitors a sensor and transmits status updates to the receiver according to a generate-at-will policy. The receiver is equipped with multiple antennas and the transmitters have single antennas; the channels are subject to Rayleigh fading and path loss. We analyze the average AoI of the first user for a discrete-time first-come-first-served (FCFS) queue, last-come-first-served (LCFS) queue, and queue with packet replacement. We derive the AoI distribution and the average AoI of the second user for a threshold policy. Then, we formulate an optimization problem to minimize the average AoI of the first user for the FCFS and LCFS with preemption queue discipline to maintain the average AoI of the second user below a given level. The constraints of the optimization problem are shown to be convex. It is also shown that the objective function of the problem for the first-come-first-served queue policy is non-convex, and a suboptimal technique is introduced to effectively solve the problem using the algorithms developed for solving a convex optimization problem. Numerical results illustrate the performance of the considered optimization algorithm versus the different parameters of the system. Finally, we discuss how the analytical results of this work can be extended to capture larger setups with more than two users.

A simple Encoding Scheme to Achieve the Capacity of Half-Duplex Relay Channel

In this paper, the Half-Duplex Relay Channel (HDRC) is thoroughly investigated. Even though this channel model is widely studied, the capacity is not yet fully understood and particularly has not been tightly expressed. In this work, a new capacity expression of the discrete memoryless HDRC is explicitly established. In particular, a new expression of the achievable rate is derived by taking advantage of the well-known capacity results of both the degraded broadcast channel and the multiple access channel. Specifically, in order to obtain the achievable rate, the transmission from the source to destination is operated over two phases. In the first phase, the broadcast phase, the source broadcasts to both relay and destination. In the second phase, both source and relay transmit to destination to form multiple access channel. Then, we prove that the new achievable rate meets the cut-set outer bound such that the capacity of the discrete memoryless HDRC is attained. Next, the new derived capacity result is extended to the case of additive Gaussian channel. Further, the attained capacity is analytically and then numerically shown to encompass all well-known available findings in the literature. Additional numerical examples are also shown to present the cases in which the relay is beneficial and how the achievable capacity varies with the source-relay and relay-destination channel gains.

Optical frequency comb assisted denoising for multiple access and capacity enhancement of covert wireless communication.

An optical frequency comb (OFC)-assisted covert wireless communication system with multiple access and enhanced capacity is proposed and experimentally demonstrated. In the scheme, signals in multiple channels are spread and mixed together to use a single transmitter and then received by individual receivers according to multiple access channels. The mixed signal is highly contaminated by noise to achieve high concealment in both the time and frequency domains, and then effectively recovered as different channels using the OFC assisted analog deep denoising technique. In experiments, mixed signals of 16 access channels with a signal-to-noise ratio (SNR) from -18 to -5 dB are accommodated, showing high covertness and 16× capacity enhancement (16×10 Mbit/s). Mutual interference among different channels is also analyzed and greatly eliminated by phases optimization in the spectral-spreading process. This scheme can greatly improve the time and spectrum utilization efficiency, which will be of great significance for enabling multiple access, large capacity, and high security for wireless communications.

Universal Classical-Quantum Superposition Coding and Universal Classical-Quantum Multiple Access Channel Coding

We derive universal classical-quantum superposition coding and universal classical-quantum multiple access channel code by using generalized packing lemmas for the type method. Using our classical-quantum universal superposition code, we establish the capacity region of a classical-quantum compound broadcast channel with degraded message sets. Our universal classical-quantum multiple access channel codes have two types of codes. One is a code with joint decoding and the other is a code with separate decoding. The former universally achieves corner points of the capacity region and the latter universally achieves general points of the capacity region. Combining the latter universal code with the existing result by Quantum Inf Process. 18, 246 (2019), we establish a single-letterized formula for the capacity region of a classical-quantum compound multiple access channel.

Convergence of Federated Learning Over a Noisy Downlink

We study federated learning (FL), where power-limited wireless devices utilize their local datasets to collaboratively train a global model with the help of a remote parameter server (PS). The PS has access to the global model and shares it with the devices for local training using their datasets, and the devices return the result of their local updates to the PS to update the global model. The algorithm continues until the convergence of the global model. This framework requires downlink transmission from the PS to the devices and uplink transmission from the devices to the PS. The goal of this study is to investigate the impact of the bandwidth-limited shared wireless medium on the performance of FL with a focus on the downlink. To this end, the downlink and uplink channels are modeled as fading broadcast and multiple access channels, respectively, both with limited bandwidth. For downlink transmission, we first introduce a digital approach, where a quantization technique is employed at the PS followed by a capacity-achieving channel code to transmit the global model update over the wireless broadcast channel at a common rate such that all the devices can decode it. Next, we propose analog downlink transmission, where the global model is broadcast by the PS in an uncoded manner. We consider analog transmission over the uplink in both cases, since its superiority over digital transmission for uplink has been well studied in the literature. We further analyze the convergence behavior of the proposed analog transmission approach over the downlink assuming that the uplink transmission is error-free. Numerical experiments show that the analog downlink approach provides significant improvement over the digital one with a more notable improvement when the data distribution across the devices is not independent and identically distributed. The experimental results corroborate the convergence analysis, and show that a smaller number of local iterations should be used when the data distribution is more biased, and also when the devices have a better estimate of the global model in the analog downlink approach.

Near-Optimal Coding for Many-User Multiple Access Channels

This paper considers the Gaussian multiple-access channel (MAC) in the asymptotic regime where the number of users grows linearly with the code length. We propose efficient coding schemes based on random linear models with approximate message passing (AMP) decoding and derive the asymptotic error rate achieved for a given user density, user payload (in bits), and user energy. The tradeoff between energy-per-bit and achievable user density (for a fixed user payload and target error rate) is studied, and it is demonstrated that in the large system limit, a spatially coupled coding scheme with AMP decoding achieves near-optimal tradeoffs for a wide range of user densities. Furthermore, in the regime where the user payload is large, we also study the tradeoff between energy-per-bit and spectral efficiency and discuss methods to reduce decoding complexity.

User Identification and Channel Estimation by Iterative DNN-Based Decoder on Multiple-Access Fading Channel

User Identification and Channel Estimation by Iterative DNN-Based Decoder on Multiple-Access Fading Channel

Private Classical Communication Over Quantum Multiple-Access Channels

We study private classical communication over quantum multiple-access channels. For an arbitrary number of transmitters, we derive a regularized expression of the capacity region. In the case of degradable channels, we establish a single-letter expression for the best achievable sum-rate and prove that this quantity also corresponds to the best achievable sum-rate for quantum communication over degradable quantum multiple-access channels. In our achievability result, we decouple the reliability and privacy constraints, which are handled via source coding with quantum side information and universal hashing, respectively. Hence, we also establish that the multi-user coding problem under consideration can be handled solely via point-to-point coding techniques. As a by-product of independent interest, we derive a distributed leftover hash lemma against quantum side information that ensures privacy in our achievability result.

Computable limits of optical multiple-access communications

Communication rates over quantum channels can be boosted by entanglement, via superadditivity phenomena or entanglement assistance. Superadditivity refers to the capacity improvement from entangling inputs across multiple channel uses. Nevertheless, when unlimited entanglement assistance is available, the entanglement between channel uses becomes unnecessary -- the entanglement-assisted (EA) capacity of a single-sender and single-receiver channel is additive. We generalize the additivity of EA capacity to general multiple-access channels (MACs) for the total communication rate. Furthermore, for optical communication modelled as phase-insensitive bosonic Gaussian MACs, we prove that the optimal total rate is achieved by Gaussian entanglement and therefore can be efficiently evaluated. To benchmark entanglement's advantage, we propose computable outer bounds for the capacity region without entanglement assistance. Finally, we formulate an EA version of minimum entropy conjecture, which leads to the additivity of the capacity region of phase-insensitive bosonic Gaussian MACs if it is true. The computable limits confirm entanglement's boosts in optical multiple-access communications.

Deep Reinforcement Learning Based Optical and Acoustic Dual Channel Multiple Access in Heterogeneous Underwater Sensor Networks.

In this paper, we investigate how to efficiently utilize channel bandwidth in heterogeneous hybrid optical and acoustic underwater sensor networks, where sensor nodes adopt different Media Access Control (MAC) protocols to transmit data packets to a common relay node on optical or acoustic channels. We propose a new MAC protocol based on deep reinforcement learning (DRL), referred to as optical and acoustic dual-channel deep-reinforcement learning multiple access (OA-DLMA), in which the sensor nodes utilizing the OA-DLMA protocol are called agents, and the remainder are non-agents. The agents can learn the transmission patterns of coexisting non-agents and find an optimal channel access strategy without any prior information. Moreover, in order to further enhance network performance, we develop a differentiated reward policy that rewards specific actions over optical and acoustic channels differently, with priority compensation being given to the optical channel to achieve greater data transmission. Furthermore, we have derived the optimal short-term sum throughput and channel utilization analytically and conducted extensive simulations to evaluate the OA-DLMA protocol. Simulation results show that our protocol performs with near-optimal performance and significantly outperforms other existing protocols in terms of short-term sum throughput and channel utilization.