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In a multiple access channel, autonomous stations are able to transmit and listen to a shared device. A fundamental problem, called contention resolution , is to allow any station to successfully deliver its message by resolving the conflicts that arise when several stations transmit simultaneously. Despite a long history on such a problem, most of the results deal with the static setting when all stations start simultaneously, while many fundamental questions remain open in the realistic scenario when stations can join the channel at arbitrary times. In this paper, we explore the impact that three major channel features (asynchrony among stations, knowledge of the number of contenders and possibility of switching off stations after a successful transmission) can have on the time complexity of non-adaptive deterministic algorithms. We establish upper and lower bounds allowing to understand which parameters permit time-efficient contention resolution and which do not. [ABSTRACT FROM AUTHOR]

A new converse bound is presented for the two-user multiple-access channel under the average probability of error constraint. This bound shows that for most channels of interest, the second-order coding rate—that is, the difference between the best achievable rates and the asymptotic capacity region as a function of blocklength $n$ with fixed probability of error—is $O(1/\sqrt {n})$ bits per channel use. The principal tool behind this converse proof is a new measure of dependence between two random variables called wringing dependence, as it is inspired by Ahlswede’s wringing technique. The $O(1/\sqrt {n})$ gap is shown to hold for any channel satisfying certain regularity conditions, which includes all discrete-memoryless channels and the Gaussian multiple-access channel. Exact upper bounds as a function of the probability of error are proved for the coefficient in the $O(1/\sqrt {n})$ term, although for most channels they do not match existing achievable bounds. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, we analyze inner and outer bounding capacity region of two-user multiple-access relay channel (MARC) with side information (SI) non-causally known at one encoder in different scenarios. First, we obtain a general capacity inner bound including various previous results as its special cases, where, the informed encoder transmits two-layer individual description of side information to the relay and destination, and block Markov, superposition, Marton and Gel'fand-Pinsker coding at the encoders and sliding-window decoding at the receiver are exploited. This individual side information can be considered as the partial SI at the relay and destination, which can potentially increase the transmission rates, especially for the uninformed encoder. Second, to show practical importance of the obtained inner bound, we extend it to the Gaussian version, which can be used in studying the coverage region and energy efficiency. Third, we study outer bounding the capacity region, aiming at outer bounds less than cut set bounds, by considering a general MARC with partial decode and forward (PDF) strategy at the relay. Finally, the obtained Gaussian inner bound is evaluated numerically, and we showed that our capacity inner bound results in more sum-rate in comparison with the previous studies. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) stands out as a promising technology by enhancing the electromagnetic wave propagation environment with its passive reflecting elements. In this paper, we focus on the ergodic sum-rate analysis and maximization of the RIS-assisted uplink multiuser multiple-input multiple-output (MIMO) multiple-access channel (MAC) under Rician fading by exploiting full statistical channel state information (CSI). The spatial correlations at the base station, the users, and the RIS are also considered. By using the replica method originated in statistical physics, the closed-form asymptotic ergodic sum-rate of the system is first derived in the large-system regime on the account of the unique channel structure of the RIS-assisted MIMO-MAC system. Then, based on the derived asymptotic ergodic sum-rate, we propose an alternating optimization (AO) algorithm to jointly design the transmit covariance matrix of users and the phase-shifting matrix of RIS with full statistical CSI. Simulation results are also demonstrated to verify the accuracy of the derived asymptotic ergodic sum-rate and the superiority of the proposed AO algorithm. The results reveal that the derived closed-form asymptotic ergodic sum-rate matches very well with the Monte Carlo results even for a small number of antennas, and the proposed AO algorithm can achieve up to 10 bps/Hz gain at high signal-to-noise (SNR) regime, which is therefore valuable for future RIS-assisted MIMO-MAC system designs. [ABSTRACT FROM AUTHOR]

Capacity of uncoordinated multiple access channel (MAC) with single-user demodulation has been studied in literature under various assumptions for symbol-synchronous transmission. This paper considers symbol-asynchronous uncoordinated transmission on a binary continuous-time noiseless MAC. It first proposes and develops a new multi-user interference analysis approach that in turn allows exact evaluation of the mutual information on the multi-access channel. Consequently, the sum-capacity of the considered binary symbol-asynchronous uncoordinated MAC is determined.

We consider transmission of packets over queue-length sensitive unreliable links, where packets are randomly corrupted through a noisy channel whose transition probabilities are modulated by the queue-length. The goal is to characterize the capacity of this channel. We particularly consider multipleaccess systems, where transmitters dispatch encoded symbols over a system that is a superposition of continuous-time GIk/GI/1 queues. A server receives and processes symbols in order of arrivals with queuelength dependent noise. We first determine the capacity of single-user queue-length dependent channels. Further, we characterize the best and worst dispatch processes for GI/M/1 queues and the best and worst service processes for M/GI/1 queues. Then, the multiple-access channel capacity is obtained using point processes. When the number of transmitters is large and each arrival process is sparse, the superposition of arrivals approaches a Poisson point process. In characterizing the Poisson approximation, we show that the capacity of the multiple-access system converges to that of a single-user M/GI/1 queue-length dependent system, and an upper bound on the convergence rate is obtained. This implies that the best and worst server behaviors of single-user M/GI/1 queues are preserved in the sparse multiple-access case.

We consider a point–to–point communication system, where in addition to the encoder and the decoder, there is a helper that observes non–causally the realization of the noise vector and provides a (lossy) rate– $ {R}_{{ \text { h}}}$ description of it to the encoder ($ {R}_{{ \text { h}}} < \infty $). In continuation to Lapidoth and Marti (2020), who derived the capacity of this model, here our focus is on error exponents. We consider both continuous–alphabet, additive white Gaussian channels and finite–alphabet, modulo–additive channels, and for each one of them, we study the cases of both fixed–rate and variable–rate noise descriptions by the helper. Our main finding is that, as long as the channel–coding rate, R, is below the helper–rate, $ {R}_{{ \text { h}}}$ , the achievable error exponent is unlimited (i.e., it can be made arbitrarily large), and in some of the cases, it is even strictly infinite (i.e., the error probability can be made strictly zero). However, in the range of coding rates $({R}_{{ \text { h}}}, {R}_{{ \text { h}}}+ {C}_{0})$ , C0 being the ordinary channel capacity (without help), the best achievable error exponent is finite and strictly positive, although there is a certain gap between our upper bound (converse bound) and lower bound (achievability) on the highest achievable error exponent. This means that the model of encoder–assisted communication is essentially equivalent to a model, where in addition to the noisy channel between the encoder and decoder, there is also a parallel noiseless bit–pipe of capacity $ {R}_{{ \text { h}}}$. We also extend the scope to the Gaussian multiple access channel (MAC) and characterize the rate sub–region, where the achievable error exponent is unlimited or even infinite. [ABSTRACT FROM AUTHOR]

Uplink-downlink duality refers to the fact that under a sum-power constraint, the capacity regions of a Gaussian multiple-access channel and a Gaussian broadcast channel with Hermitian transposed channel matrices are identical. This paper generalizes this result to a cooperative cellular network, in which remote access-points are deployed as relays in serving the users under the coordination of a central processor (CP). In this model, the users and the relays are connected over noisy wireless links, while the relays and the CP are connected over noiseless but rate-limited fronthaul links. Based on a Lagrangian technique, this paper establishes a duality relationship between such a multiple-access relay channel and broadcast relay channel, under the assumption that the relays use compression-based strategies. Specifically, we show that under the same total transmit power constraint and individual fronthaul rate constraints, the achievable rate regions of the Gaussian multiple-access and broadcast relay channels are identical, when either independent compression or Wyner-Ziv and multivariate compression strategies are used. The key observations are that if the beamforming vectors at the relays are fixed, the sum-power minimization problems under the achievable rate and fronthaul constraints in both the uplink and the downlink can be transformed into either a linear programming or a semidefinite programming problem depending on the compression technique, and that the uplink and downlink problems are Lagrangian duals of each other. Moreover, the dual variables corresponding to the downlink rate constraints become the uplink powers; the dual variables corresponding to the downlink fronthaul constraints become the uplink quantization noises. This duality relationship enables an efficient algorithm for optimizing the downlink transmission and relaying strategies based on the uplink. [ABSTRACT FROM AUTHOR]

A channel with multiplicity feedback in case of collision returns the exact number of stations simultaneously transmitting. In this model, Θ ((d log ⁡ (n / d)) / log ⁡ d) time rounds are sufficient and necessary to identify d transmitting stations out of n. In contrast, in the ternary feedback model the time complexity is Θ (d log ⁡ (n / d)). Generalizing, we can define a feedback interval [ x , y ] , where 0 ≤ x ≤ y ≤ d , such that the channel returns the exact number of transmitting stations only if this number is within that interval. For a feedback interval centered in d / 2 we show that it is possible to get the same optimal time complexity for the channel with multiplicity feedback even if the interval has only size O (d log ⁡ d). On the other hand, if we further reduce the size to O ( d log ⁡ d) , then we show that no protocol having time complexity Θ ((d log ⁡ (n / d)) / (log ⁡ d)) is possible. [ABSTRACT FROM AUTHOR]

A fundamental tool to prove inner bounds in classical network information theory is the so-called ‘conditional joint typicality lemma’. In addition to the lemma, one often uses unions and intersections of typical sets in the inner bound arguments without so much as giving them a second thought. These arguments do not work in the quantum setting. This bottleneck shows up in the fact that so-called ‘simultaneous decoders’, as opposed to ‘successive cancellation decoders’, are known for very few channels in quantum network information theory. Another manifestation of this bottleneck is the lack of so-called ‘simultaneous smoothing’ theorems for quantum states. In this paper, we overcome the bottleneck by proving for the first time a one-shot quantum joint typicality lemma with robust union and intersection properties. To do so we develop two novel tools in quantum information theory, which may be of independent interest. The first tool is a simple geometric idea called tilting, which increases the angles between a family of subspaces in orthogonal directions. The second tool, called smoothing and augmentation, is a way of perturbing a multipartite quantum state such that the partial trace over any subset of registers does not increase the operator norm much. Our joint typicality lemma allows us to construct simultaneous quantum decoders for many multiterminal quantum channels. It provides a powerful tool to extend many results in classical network information theory to the one-shot quantum setting. [ABSTRACT FROM AUTHOR]

A coding technique that is based on flash helping is proposed for communicating over additive noise channels where a helper observes the noise and can describe it to the encoder over a noise-free rate-limited bit pipe. The technique is applicable irrespective of whether the helper observes the noise causally or noncausally. On the single-user channel of general noise, the rate it achieves is the sum of the channel’s capacity without a helper and the rate of the bit pipe. For Gaussian noise and under an average-power constraint, it is optimal. Analogous results are derived for the additive noise multiple-access channel and the single-user Exponential channel. The approach is applicable also in some (noncausal) discrete settings, as demonstrated on the discrete modulo-additive noise channel. [ABSTRACT FROM AUTHOR]

Algebraic network information theory is an emerging facet of network information theory, studying the achievable rates of random code ensembles that have algebraic structure, such as random linear codes. A distinguishing feature is that linear combinations of codewords can sometimes be decoded more efficiently than codewords themselves. The present work further develops this framework by studying the simultaneous decoding of multiple messages. Specifically, consider a receiver in a multi-user network that wishes to decode several messages. Simultaneous joint typicality decoding is one of the most powerful techniques for determining the fundamental limits at which reliable decoding is possible. This technique has historically been used in conjunction with random i.i.d. codebooks to establish achievable rate regions for networks. Recently, it has been shown that, in certain scenarios, nested linear codebooks in conjunction with “single-user” or sequential decoding can yield better achievable rates. For instance, the compute–forward problem examines the scenario of recovering $L \le K$ linear combinations of transmitted codewords over a $K$ -user multiple-access channel (MAC), and it is well established that linear codebooks can yield higher rates. This paper develops bounds for simultaneous joint typicality decoding used in conjunction with nested linear codebooks, and applies them to obtain a larger achievable region for compute–forward over a $K$ -user discrete memoryless MAC. The key technical challenge is that competing codeword tuples that are linearly dependent on the true codeword tuple introduce statistical dependencies, which requires careful partitioning of the associated error events. [ABSTRACT FROM AUTHOR]

Physical-layer network coding (PNC) has received much attention, both from academia and industry lately, since it takes advantages of multiple-access signals. Because of a reduced number of time slots (TSs), PNC is capable of improving throughput significantly, especially for a typical 3-node network consisting of 2 user terminals and 1 relay node. However, a network with $M$ nodes ($M>3$) and without adopting additional techniques needs $(2M-2)$ TSs to realize information exchange among all the nodes, since network coding is unable to distinguish between users at the relay node. This paper proposes uniquely decodable codes (UDCs) for PNC in wireless cooperative communications. The proposed UDC requires only two TSs for information exchange irrespective of the number of nodes in the network. This paper also investigates the amplify-and-forward and decode-and-forward modes for UDC-based PNC. The bit error rate and throughput of the proposed schemes are analyzed in this paper. Using simulation results, we demonstrate that our theoretical results align well with the simulation results. [ABSTRACT FROM AUTHOR]

We study the fundamental problem of utilization of the channel shared by stations competing to transmit packets on the channel. In their turn, packets are continuously injected into stations' queues by an adversary at a rate at most ρ packets per round. The aim of the distributed medium access control algorithms is to successfully transmit packets and maintain system stability (bounded queues). We further restrain algorithms by introducing an upper bound k on the allowed number of active stations in any given round. We construct adaptive and full sensing protocols with optimal throughput 1 and almost optimal throughput 1 − ϵ (for any positive ϵ), respectively, in a constant-restrained channel. On the opposite side, we show that restricted protocols based on schedules known in advance suffer from a substantial drop of throughput, at most min ⁡ { k n , 1 log ⁡ n }. We compare our algorithms experimentally with well-known backoff protocols. [ABSTRACT FROM AUTHOR]

We consider the capacity region of a K-user multiple-access channel (MAC) with energy harvesting transmitters. Each user stores and schedules the randomly arriving energy using an energy buffer. Users can also perform energy cooperation by transmitting energy to other users or receiving energy from them. We derive the capacity region of this channel and show that: 1) the capacity region coincides with that of a traditional K-user Gaussian MAC with energy cooperation, where the average power constraints equal to the battery recharging rates of the energy harvesting case and 2) each rate on the capacity region boundary can be achieved using the save-and-forward power control and a fixed energy cooperation policy.

An execution of a distributed algorithm is often seen as a game between the algorithm and a conceptual adversary causing specific distractions to the computation. In this work we define a class of ordered adaptive adversaries, which cause distractions—in particular crashes—online according to some partial order of the participating stations, which is fixed by the adversary before the execution. We distinguish: Linearly-Ordered adversary, restricted by some pre-defined linear order of (potentially) crashing stations; Anti-Chain-Ordered adversary, previously known as the Weakly-Adaptive adversary, which is restricted by some pre-defined set of crash-prone stations (it can be seen as an ordered adversary with the order being an anti-chain, i.e., a collection of incomparable elements, consisting of these stations); k-Thick-Ordered adversary restricted by partial orders of stations with a maximum anti-chain of size k. We initiate a study of how they affect performance of algorithms. For this purpose, we focus on the well-known Do-All problem of performing t tasks by p synchronous crash-prone stations communicating on a shared channel. The channel restricts communication by the fact that no message is delivered to the operational stations if more than one station transmits at the same time. The question addressed in this work is how the ordered adversaries controlling crashes of stations influence work performance, defined as the total number of available processor steps during the whole execution and introduced by Kanellakis and Shvartsman (Distrib Comput 5(4):201–217, 1992) in the context of Write-All algorithms. The first presented algorithm solves the Do-All problem with work O (t + p t log p) against the Linearly-Ordered adversary. Surprisingly, the upper bound on performance of this algorithm does not depend on the number of crashes f and is close to the absolute lower bound Ω (t + p t) proved in Chlebus et al. (Distrib Comput 18(6):435–451, 2006). Another algorithm is developed against the Weakly-Adaptive adversary. Work done by this algorithm is O (t + p t + p min p / (p - f) , t log p) , which is close to the lower bound Ω (t + p t + p min p / (p - f) , t) proved in [11] and answers the open questions posed there. We generalize this result to the class of k-Thick-Ordered adversaries, in which case the work of the algorithm is bounded by O (t + p t + p min p / (p - f) , k , t log p). We complement this result by proving the almost matching lower bound Ω (t + p t + p min p / (p - f) , k , t). Independently from the results for the ordered adversaries, we consider a class of delayed adaptive adversaries, which could see random choices with some delay. We present an algorithm that works efficiently against the 1-RD adversary, which could see random choices of stations with one round delay, achieving close to optimal O (t + p t log 2 p) work complexity. This shows that restricting the adversary by not allowing it to react on random decisions immediately makes it significantly weaker, in the sense that there is an algorithm achieving (almost) optimal work performance. [ABSTRACT FROM AUTHOR]

The capacity of the semi-deterministic relay channel (SD-RC) with non-causal channel state information (CSI) only at the encoder and decoder is characterized. The capacity is achieved by a scheme based on cooperative-bin-forward. This scheme allows cooperation between the transmitter and the relay without the need of the later to decode a part of the message. The transmission is divided into blocks, and each deterministic output of the channel (observed by the relay) is mapped to a bin. The bin index is used by the encoder and the relay to choose the cooperation codeword in the next transmission block. In causal settings, the cooperation is independent of the state. In non-causal settings, dependence between the relay’s transmission and the state can increase the transmission rates. The encoder implicitly conveys partial state information to the relay. In particular, it uses the states of the next block and selects a cooperation codeword accordingly, and the relay transmission depends on the cooperation codeword and, therefore, also on the states. We also consider the multiple access channel with partial cribbing as a semi-deterministic channel. The capacity region of this channel with non-causal CSI is achieved by the new scheme. Examining the result in several cases, we introduce a new problem of a point-to-point (PTP) channel where the state is provided to the transmitter by a state encoder. Interestingly, even though the CSI is also available at the receiver, we provide an example showing that the capacity with non-causal CSI at the state encoder is strictly larger than the capacity with causal CSI. [ABSTRACT FROM AUTHOR]

This paper considers an unlicensed multiple-access channel (MAC) that coexists with a licensed point-to-point user, following the underlay cognitive radio paradigm. We assume that every transceiver except the secondary base station has one antenna and that the primary user (PU) is protected by a minimum rate constraint. In contrast to the conventional assumption of proper Gaussian signaling, we allow the secondary users to transmit improper Gaussian signals, which are correlated with their complex conjugate. When the secondary base station performs zero-forcing, we show that improper signaling is optimal if the sum of the interference channel gains (in an equivalent canonical model) is above a certain threshold. Additionally, we derive an efficient algorithm to compute the transmission parameters that attain the rate region boundary for this scenario. The proposed algorithm exploits a single-user representation of the secondary MAC along with new results on the optimality of improper signaling in the single-user case when the PU is corrupted by an improper noise. [ABSTRACT FROM AUTHOR]

This paper presents a joint typicality framework for encoding and decoding nested linear codes in multi-user networks. This framework provides a new perspective on compute–forward within the context of discrete memoryless networks. In particular, it establishes an achievable rate region for computing a linear combination over a discrete memoryless multiple-access channel (MAC). When specialized to the Gaussian MAC, this rate region recovers and improves upon the lattice-based compute–forward rate region of Nazer and Gastpar, thus providing a unified approach for discrete memoryless and Gaussian networks. Furthermore, our framework provides some valuable insights on establishing the optimal decoding rate region for compute–forward by considering joint decoders, progressing beyond most previous works that consider successive cancellation decoding. Specifically, this paper establishes an achievable rate region for simultaneously decoding two linear combinations of nested linear codewords from $K$ senders. [ABSTRACT FROM AUTHOR]

We consider strongly secure communication over a discrete memoryless multiple access wiretap channel with two transmitters. No degradation or symmetry assumptions are made on the channel. Our main result is that any rate pair known to be achievable with a random coding like proof, is also achievable with anexplicitand low-complexity polar coding scheme. Moreover, if the rate pair is known to be achievable without time-sharing, then time-sharing is not needed in our polar coding scheme as well. Our proof technique relies on rate-splitting, which introduces two virtual transmitters, and cooperative jamming strategies implemented by these virtual transmitters. Specifically, our coding scheme combines point-to-point codes that either aim at secretly conveying a message to the legitimate receiver or at performing cooperative jamming. Each point-to-point code relies on block Markov encoding to be able to deal with an arbitrary channel and strong secrecy. Consequently, our coding scheme is the combination of inter-dependent block Markov constructions. We assess reliability and strong secrecy through a detailed analysis of the dependencies between the random variables involved in the scheme. [ABSTRACT FROM AUTHOR]

In this paper we review the theoretical and practical principles of the broadcast approach to communication over state-dependent channels and networks in which the transmitters have access to only the probabilistic description of the time-varying states while remaining oblivious to their instantaneous realizations. When the temporal variations are frequent enough, an effective long-term strategy is adapting the transmission strategies to the system’s ergodic behavior. However, when the variations are infrequent, their temporal average can deviate significantly from the channel’s ergodic mode, rendering a lack of instantaneous performance guarantees. To circumvent a lack of short-term guarantees, the broadcast approach provides principles for designing transmission schemes that benefit from both short- and long-term performance guarantees. This paper provides an overview of how to apply the broadcast approach to various channels and network models under various operational constraints.

Here, the authors propose an energy‐efficient strategy using multiple antennas for secure distributed detection in wireless sensor networks (WSNs). In multiple access channel, it is possible to communicate between sensors and ally fusion centre with perfect secrecy by an encryption with channel state information (CSI). However, the sensors in an active group may need to constantly report in the encryption as long as the CSI remains unchanged, which deteriorates the energy efficiency in terms of the lifetime of WSN. The authors solve the problem by using random beamforming (e.g. antenna subset modulation). Furthermore, the authors investigate the impact of the number of active antennas on the network lifetime. Through the analysis and simulation, the authors demonstrate that the proposed strategy has a higher energy efficiency than the conventional strategy, while maintaining the same reliability and security. [ABSTRACT FROM AUTHOR]

We establish that the capacity regions of the discrete memoryless and vector Gaussian multiple access channels with general message sets are achievable with hierarchical successive group decoding, where groups of messages are successively decoded in accordance with the following rule: for each pair of messages known to nested sets of transmitters, the message known to more transmitters is decoded prior to—and not jointly with—the message known to fewer transmitters. This conclusion requires neither rate-splitting nor time-sharing, and is agnostic to whether or not the messages were encoded dependently. For instance, with private messages, hierarchical successive group decoding includes jointly decoding all messages at once, while for degraded messages, it is successive decoding in only one order. A consequence of our main result is that the capacity region of the multiple access channel with general message sets is achievable by time-sharing between only those successive decoding vertices whose decoding order respects the rule described as earlier. [ABSTRACT FROM PUBLISHER]

This paper studies channel coding for the discrete memoryless multiple-access channel with a given (possibly suboptimal) decoding rule. A multi-letter successive decoding rule depending on an arbitrary non-negative decoding metric is considered, and achievable rate regions and error exponents are derived both for the standard MAC (independent codebooks), and for the cognitive MAC (one user knows both messages) with superposition coding. In the cognitive case, the rate region and error exponent are shown to be tight with respect to the ensemble average. The rate regions are compared with those of the commonly considered decoder that chooses the message pair maximizing the decoding metric, and numerical examples are given for which successive decoding yields a strictly higher sum rate for a given pair of input distributions. [ABSTRACT FROM AUTHOR]

Recently, it has been shown that the time-varying multiple-access channel (MAC) with perfect channel state information (CSI) at the receiver and delayed feedback CSI at the transmitters can be modeled as the finite state MAC (FS-MAC) with delayed state feedback, where the time variation of the channel is characterized by the statistics of the underlying state process. To study the fundamental limit of the secure transmission over multi-user wireless communication systems, we re-visit the FS-MAC with delayed state feedback by considering an external eavesdropper, which we call the finite state multiple-access wiretap channel (FS-MAC-WT) with delayed feedback. The main contribution of this paper is to show that taking full advantage of the delayed channel output feedback helps to increase the secrecy rate region of the FS-MAC-WT with delayed state feedback. Moreover, by a degraded Gaussian fading example, we show the effects of feedback delay and channel memory on the secrecy sum rate of the FS-MAC-WT with delayed feedback. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of separately modulating and jointly estimating two independent continuous-valued parameters sent over a Gaussian multiple-access channel (MAC) under the mean square error (MSE) criterion without bandwidth constraints. To this end, we first improve an existing lower bound on the MSE that is obtained using the parameter modulation-estimation techniques for the single-user additive white Gaussian noise (AWGN) channel. As for the main contribution of this paper, this improved modulation-estimation analysis is generalized to the model of the two-user Gaussian MAC. We present outer bounds to the achievable region in the plane of the MSE’s of the two user parameters, which provides a trade-off between the MSE’s, where we used zero-rate lower bounds on the error probability of Gaussian channels by Shannon and Polyanskiy et al. Numerical results showed that, the multi-user adaptation of the zero-rate lower bound by Polyanskiy et al. provides a tighter overall lower bound on the MSE pairs than the classical Shannon bound. In addition, we introduced upper bounds on the MSE exponents, namely, the exponential decay rates of these MSE’s in the asymptotic regime of long blocks that could make use of any bound on the error exponent of a single-user AWGN channel. The obtained results are numerically evaluated for three different bounds on the reliability function of the Gaussian channel. It is shown that the adaptation of the reliability function by Ashikhmin et al. to the MAC provides a significantly tighter characterization than Shannon’s sphere-packing bound and the divergence bound. [ABSTRACT FROM AUTHOR]

This paper investigates the minimum mean square error (MMSE) of communicating a pair of Gaussian sources over a a bandwidth-matched Gaussian multiple-access channel with block Rayleigh fading in the absence of channel state information (CSI) at the transmitters. The achievable MMSE is not known. To this end, we derive several upper-bounds to the minimum achievable average MMSE as a function of the transmitter powers, the average channel fading power-to-noise ratio, and the correlation coefficient of the two sources. To derive nontrivial upper bounds which improve on those of separate source-channel coding and uncoded transmission, we incorporate ideas from joint source-channel coding and hybrid digital−analog coding to construct specific coding schemes for which the achievable MMSE can be determined.

Consider a group of stations connected through a multiple-access channel, with the constraint that if at a time instant exactly one station transmits a message, then the message is successfully received by any other station, whereas if two or more stations simultaneously transmit their messages then a conflict occurs and all messages are lost. Let us assume that $n$ is the number of stations and that an (arbitrary) subset $A$ of them, $|A|\leq k\leq n$ , is active, that is, there are at most $k$ stations that have a message to send over the channel. In the classical conflict resolution problem, the issue is to schedule the transmissions of each station to let every active station use the channel alone (i.e., without conflict) at least once, and this requirement must be satisfied whatever might be the set of active stations $A$ . The parameter to optimize is, usually, the worst case number of transmissions that any station has to attempt before all message transmissions are successful. In this paper, we study the following question: is it possible to obtain a significant improvement on the protocols that solve the classical conflict resolution problem if we allow the protocols to fail over a “small” fraction of all possible subsets of active stations? In other words, is it possible to significantly reduce the number of transmissions that must be attempted if the set of active stations is chosen uniformly at random and the conflict resolution algorithm is only required to work correctly with “high” probability? In this paper, we will show that this is indeed the case. Our main technical tool is a generalization of selectors, a recently introduced combinatorial structure that has found applications in several areas. As it turned out for selectors, we believe that our new combinatorial structures are likely to be useful also outside the present context. [ABSTRACT FROM PUBLISHER]

In the scalar dirty multiple-access channel, in addition to Gaussian noise, two additive interference signals are present, each known non-causally to a single transmitter. It was shown by Philosof et al. that for strong interferences, an independent identically distributed ensemble of codes does not achieve the capacity region. Rather, a structured-codes approach was presented that was shown to be optimal in the limit of high signal-to-noise ratios, where the sum capacity is dictated by the minimal (“bottleneck”) channel gain. In this paper, we consider the multiple-input multiple-output (MIMO) variant of this setting. In order to incorporate structured codes in this case, one can utilize matrix decompositions that transform the channel into effective parallel scalar dirty multiple-access channels. This approach, however, suffers from a “bottleneck” effect for each effective scalar channel and, therefore, the achievable rates strongly depend on the chosen decomposition. It is shown that a recently proposed decomposition, where the diagonals of the effective channel matrices are equal up to a scaling factor, is optimal at high signal-to-noise ratios, under an equal rank assumption. This approach is then extended to any number of transmitters. Finally, an application to physical-layer network coding for the MIMO two-way relay channel is presented. [ABSTRACT FROM AUTHOR]

For ergodic fading, a lattice coding and decoding strategy is proposed and its performance is analyzed for the single-input single-output (SISO) and multiple-input multiple-output (MIMO) point-to-point channel as well as the multiple-access channel (MAC), with channel state information available only at the receiver (CSIR). At the decoder a novel strategy is proposed consisting of a time-varying equalization matrix followed by decision regions that depend only on channel statistics, not individual realizations. Our encoder has a similar structure to that of Erez and Zamir. For the SISO channel, the gap to capacity is bounded by a constant under a wide range of fading distributions. For the MIMO channel under Rayleigh fading, the rate achieved is within a gap to capacity that does not depend on the signal-to-noise ratio (SNR), and diminishes with the number of receive antennas. The analysis is extended to the $K$ -user MAC where similar results hold. Achieving a small gap to capacity while limiting the use of CSIR to the equalizer highlights the scope for efficient decoder implementations, since decision regions are fixed, i.e., independent of channel realizations. [ABSTRACT FROM PUBLISHER]

Consider a single-user or multiple-access channel with a large output alphabet. A method to approximate the channel by an upgraded version having a smaller output alphabet is presented and analyzed. The original channel is not necessarily symmetric and does not necessarily have a binary input alphabet. Also, the input distribution is not necessarily uniform. The approximation method is instrumental when constructing capacity achieving polar codes for an asymmetric channel with a non-binary input alphabet. Other settings in which the method is instrumental are the wiretap setting as well as the lossy source coding setting. [ABSTRACT FROM PUBLISHER]

Two different random coding techniques, both referred to as superposition coding in the literature, have been widely used to obtain inner bounds for the capacity regions of various communication networks. In one, auxiliary codewords are generated independently, and in the other, they are generated in a dependent manner. Using the multiple-access channel with general message sets as a case study, we place the two techniques under a common, order-theoretic framework. The key attribute of this framework is that it explicitly accounts for the acyclic direction and transitivity of the possible auxiliary codeword dependencies, leading to three significant discoveries. First, with respect to a fixed coding distribution, the set of rates achievable by superposition coding with dependent auxiliary codeword generation forms a polymatroid, thereby generalizing the same previously known result for superposition coding with independent auxiliary codewords. Second, we obtain a large class of superposition coding schemes by intermingling dependent and independent auxiliary codeword generation, and demonstrate that the constituent polyhedral achievable rate regions are also polymatroids in each case. The third discovery is that, in the multiple-access channel with general message sets, each associated superposition coding inner bound attains the capacity region. These results demonstrate a tradeoff between the complexity of dependencies in auxiliary codeword generation and that of the function that maps them into transmitted codewords. [ABSTRACT FROM PUBLISHER]

In this paper, we study a new bus communication model, where two transmitters wish to send their corresponding private messages and a common message to a destination, while they also wish to send the common message to another receiver connected to the same wire. From an information-theoretical point of view, we first study a general case of this new model (with discrete memoryless channels). The capacity region composed of all achievable (R0,R1,R2) triples is determined for this general model, where R1 and R2 are the transmission rates of the private messages and R0 is the transmission rate of the common message. Then, the result is further explained via the Gaussian example. Finally, we give the capacity region for the new bus communication model with additive Gaussian noises and attenuation factors. This new bus communication model captures various communication scenarios, such as the bus systems in vehicles, and the bus type of communication channel in power line communication (PLC) networks.

A simple partially repeated spatially coupled low-density parity-check (SC-LDPC) code is proposed for a multiple-access channel (MAC) with a large number of users. This code is constructed by selecting part of bits of an SC-LDPC code to be repeated. Since the decoding increment is only a log-likelihood ratio (LLR) combination, compared with the original SC-LDPC code, the decoding complexity scarcely increases. It is shown that this LLR combination is effective to overcome the multi-user interference. By optimizing the ratio of coded bits for repetition, the decoding threshold of the partially repeated SC-LDPC code can be close to the MAC capacity. Experimental results show that the partially repeated SC-LDPC codes have better performance than the graph-extended and parallelly connected SC-LDPC codes over the MAC. [ABSTRACT FROM PUBLISHER]

In this paper, the throughput of relay networks with multiple source–destination pairs under queueing constraints has been investigated for both variable-rate and fixed-rate schemes. When channel side information (CSI) is available at the transmitter side, transmitters can adapt their transmission rates according to the channel conditions, and achieve the instantaneous channel capacities. In this case, the departure rates at each node have been characterized for different system parameters, which control the power allocation, time allocation, and decoding order. In the other case of no CSI at the transmitters, a simple automatic repeat request (ARQ) protocol with fixed rate transmission is used to provide reliable communication. Under this ARQ assumption, the instantaneous departure rates at each node can be modeled as an ON–OFF process, and the probabilities of ON and OFF states are identified. With the characterization of the arrival and departure rates at each buffer, stability conditions are identified, and an effective capacity analysis is conducted for both cases to determine the system throughput under statistical queueing constraints. In addition, for the variable-rate scheme, the concavity of the sum rate is shown for certain parameters, helping to improve the efficiency of parameter optimization. Finally, through numerical results, the influence of system parameters and the behavior of the system throughput are identified. [ABSTRACT FROM PUBLISHER]

Consider an interleave-division multi-user coding model for a Gaussian multiple-access channel (MAC). Each user’s message is encoded by a separate channel encoder followed by a user-interleaver, which is employed for user separation. All the users’ codewords are jointly regarded as one multi-user codeword, and the distance between two multi-user codewords is defined as the Euclidean distance after the inter-user superposition caused by the MAC. A distance enumerator analysis estimates the multi-user maximum likelihood decoding performance. By introducing user-scramblers, a multi-user code ensemble is defined, and its distance enumerator is calculated as concatenated multiple single-user codes and a superposition code. Both finite-length and asymptotic analyses are given and it is shown that interleave-division multi-user codes have much better distance properties than conventional random direct-sequence code-division multiple-access. In fact, the codes achieve almost the same asymptotic uniquely decodable performance as a multi-user random code. [ABSTRACT FROM PUBLISHER]

This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with respect to the ensemble average, and positive within the interior of Lapidoth’s achievable rate region. This exponent proves the ensemble tightness of the exponent of Liu and Hughes in the case of maximum-likelihood decoding. An equivalent dual form of Lapidoth’s achievable rate region is given, and the latter is shown to immediately extend to channels with infinite and continuous alphabets. In the setting of single-user mismatched decoding, similar analysis techniques are applied to a refined version of superposition coding, which is shown to achieve rates at least as high as standard superposition coding for any set of random-coding parameters. [ABSTRACT FROM PUBLISHER]

Three transmission schemes over a new type of multiple-access channel (MAC) model with inter-source communication links are proposed and investigated in this paper. This new channel model is well motivated by, e.g., wireless distributed storage networks, where communication to repair a lost node takes place from helper nodes to a repairing node over a wireless channel. Since in many wireless networks nodes can come and go in an arbitrary manner, there must be an inherent capability of inter-node communication between every pair of nodes. Assuming that communication is possible between every pair of helper nodes, the newly proposed schemes are based on various smart time-sharing and relaying strategies. In other words, certain helper nodes will be regarded as relays, thereby converting the conventional uncooperative multiple-access channel to a multiple-access relay channel (MARC). The diversity-multiplexing gain tradeoff (DMT) of the system together with efficient sphere-decodability and low structural complexity in terms of the number of antennas required at each end is used as the main design objectives. While the optimal DMT for the new channel model is fully open, it is shown that the proposed schemes outperform the DMT of the simple time-sharing protocol and, in some cases, even the optimal uncooperative MAC DMT. While using a wireless distributed storage network as a motivating example throughout the paper, the MAC transmission techniques proposed here are completely general and as such applicable to any MAC communication with inter-source communication links. [ABSTRACT FROM AUTHOR]