Memoryless Multiple-access Channel Research Articles

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.

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.

Error Exponents for Asynchronous Multiple Access Channels, Controlled Asynchronism May Outperform Synchronism

Exponential error bounds achievable by universal coding and decoding are derived for frame-asynchronous discrete memoryless multiple access channels with two senders, via the method of subtypes, a refinement of the method of types. An empirical entropy decoder is employed. A key tool is an improved packing lemma, that overcomes the technical difficulty caused by codeword repetitions via an induction based new argument. The asymptotic form of the bounds admits numerical evaluation. This demonstrates that error exponents achievable by synchronous transmission can be superseded via controlled asynchronism, i.e. a deliberate shift of the codewords.

Cooperative Resolvability and Secrecy in the Cribbing Multiple-Access Channel

We study channel resolvability for the discrete memoryless multiple-access channel with cribbing, i.e., the characterization of the amount of randomness required at the inputs to approximately produce a chosen i.i.d. output distribution according to Kullback-Leibler divergence. We analyze resolvability rates when one encoder cribs (i) the input of the other encoder; or the output of the other encoder, (ii) non-causally, (iii) causally, or (iv) strictly-causally. For scenarios (i)-(iii), we exactly characterize the channel resolvability region. For (iv), we provide inner and outer bounds for the channel resolvability region; the crux of our achievability result is to handle the strict causality constraint with a block-Markov coding scheme in which dependencies across blocks are suitably hidden. Finally, we leverage the channel resolvability results to derive achievable secrecy rate regions for each of the cribbing scenarios under strong secrecy constraints.

Covert Communication Over a $K$ -User Multiple-Access Channel

We consider a scenario in which $K$ transmitters attempt to communicate covert messages reliably to a legitimate receiver over a discrete memoryless multiple-access channel (MAC) while simultaneously escaping detection from an adversary who observes their communication through another discrete memoryless MAC. We assume that each transmitter may use a secret key that is shared only between itself and the legitimate receiver. We show that each of the $K$ transmitters can transmit on the order of $\sqrt {n}$ reliable and covert bits per $n$ channel uses, exceeding which, the warden will be able to detect the communication. We identify the optimal pre-constants of the scaling, which leads to a complete characterization of the covert capacity region of the $K$ -user binary-input MAC. We show that, asymptotically, all sum-rate constraints are inactive unlike the traditional MAC capacity region. We also characterize the channel conditions that have to be satisfied for the transmitters to operate without a secret key.

A Joint Typicality Approach to Compute–Forward

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.

Mismatched Multi-Letter Successive Decoding for the Multiple-Access Channel

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.

The $K$ -User Vector Gaussian Multiple-Access Channel With General Messages Sets: Capacity, Polymatroidal Structure, and Efficient Computation

The capacity region of the $K$ -user vector Gaussian multiple-access channel with general message sets is established. Furthermore, due to the presence of convexity, both in the discrete and continuous senses, it is shown that this capacity region is efficiently computable. The capacity result is obtained by specializing recent results by the authors for the discrete memoryless multiple-access channel and demonstrating that it suffices to only consider jointly Gaussian input and auxiliary random variables. For this second conclusion, it is shown that jointly Gaussian random variables maximize entropy subject to lattice conditional independence and covariance constraints, a result that is of interest in its own right. Discrete convexity arises since the capacity region is a union of polymatroids . Over each polymatroid, computing the maximal weighted sum rates is simple due to submodularity—a discrete analog of concavity—of the set function associated with the linear inequalities that define the polymatroid. Continuous convexity arises as the set of admissible covariance matrices is convex and the polymatroidal bounds are concave in these covariances.

Multiuser Random Coding Techniques for Mismatched Decoding

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 extend immediately 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.

Impact of the relay on the coverage region of multiple‐access channels

From practical and theoretical viewpoints, performance analysis of communication systems by using information-theoretic results is important. In this study, first, the authors obtain a general achievable rate region for three-user discrete memoryless multiple-access relay channel (MARC) via partial decode and forward strategy and regular block Markov encoding/backward decoding. Also by extending the discrete alphabet results to the continuous alphabet channel, an inner bound for three-user Gaussian MARC (GMARC) is achieved. Next, based on the inner bound of three-user GMARC, they analyse the impact of a relay on the coverage region of MARC, as a basic model for uplink communications between a base station and users with the help of a relay. This analysis includes the coverage region for the multiple-access channel and two-user GMARC as special cases. Considering rate regions for the GMARC and fading GMARC, it is proved that in a fixed transmission rate, the relay extends coverage region of the MARC. Numerical illustrations confirm their theoretical results.

Second-Order Rate Region of Constant-Composition Codes for the Multiple-Access Channel

This paper studies the second-order asymptotics of coding rates for the discrete memoryless multiple-access channel (MAC) with a fixed target error probability. Using constant-composition random coding, coded time-sharing, and a variant of Hoeffding's combinatorial central limit theorem, an inner bound on the set of locally achievable second-order coding rates is given for each point on the boundary of the capacity region. It is shown that the inner bound for constant-composition random coding includes that recovered by independent identically distributed random coding, and that the inclusion may be strict. The inner bound is extended to the Gaussian MAC via an increasingly fine quantization of the inputs.

Feedback, Cribbing, and Causal State Information on the Multiple-Access Channel

The benefits afforded by feedback and/or causal state information (SI) on the state-dependent discrete memoryless multiple-access channel (SD-MAC) with cribbing encoder/s are studied. Capacity regions are derived for communication scenarios whose capacities without cribbing are still unknown. It is shown that when the encoders can crib, the SD-MAC behaves less like a MAC and more like a single-user channel: 1) feedback does not help; 2) strictly causal SI does not help; and 3) causal SI to both encoders is best utilized using Shannon strategies. However, in asymmetric settings, the single-user-like behavior may or may not occur. For example, the SD-MAC with only one cribbing encoder is single-user-like when the state is revealed to the cribbing encoder, but not if it is revealed to the noncribbing encoder.

Memoryless Multiple Access Channel With Asymmetric Noisy State Information at the Encoders

The problem of reliable communication over the memoryless state-dependent multiple-access channel (MAC) is considered, where the encoders and the decoder are provided with various degrees of asymmetric noisy channel state information (CSI). For the case where the encoders observe causal, asymmetric noisy CSI and the decoder observes complete CSI, inner and outer bounds to the capacity region, which are tight for the sum-rate capacity, are provided. Next, single-letter characterizations for the channel capacity regions under each of the following system settings are established: 1) the CSI at the encoders are asymmetric deterministic functions of the CSI at the decoder and the encoders have noncausal noisy CSI; 2) the encoders observe asymmetric noisy CSI with asymmetric delays and the decoder observes complete CSI; 3) a degraded message set scenario with asymmetric noisy CSI at the encoders and complete and/or noisy CSI at the decoder. The main component in these results is a generalization of a recently introduced converse coding approach for the MAC with asymmetric quantized CSI at the encoders and herein considerably extended and adapted for the noisy CSI setup.

Discrete Memoryless Multiple-Access Wiretap Channel with Non-Cooperative Encoders

In this paper, the discrete memoryless multiple-access wiretap channel (MAC-WT) with non-cooperative encoders is studied, where two users (cooperation between the users is not allowed) transmit their corresponding confidential messages (no common message) to a legitimate receiver, while an additional wiretapper wishes to obtain the messages via a wiretap channel. The inner and outer bounds on the capacity-equivocation region are provided forthis new model, and the result is further explained via a binary example.

The Multiple-Access Channel With Causal Side Information: Double State

We consider a memoryless multiple-access channel (MAC) that is governed by two independent memoryless state sequences, each of which is revealed to a different encoder in a strictly causal or causal way. The special case where one of the state sequences is deterministic (null) corresponds to an MAC governed by a single state that is revealed to only one of the encoders. We show that, even in the strictly causal case, the state information at the encoders can increase the capacity region. It cannot, however, increase the sum-rate capacity. We provide general inner and outer bounds on the capacity region, and we also study a Gaussian example where they coincide. We show that in the causal case, naïve Shannon strategies may be suboptimal.

The Multiple-Access Channel With Causal Side Information: Common State

We show that if a memoryless multiple-access channel (MAC) is governed by an independent and identically distributed state sequence, then-unlike the single-user case-the capacity region is typically increased if the state is revealed to the encoders in a strictly causal way. For this scenario, we derive inner and outer bounds on the capacity region. For the Gaussian MAC whose state sequence comprises the channel noise, we compute the capacity region and propose a variation on the Schalkwijk-Kailath scheme that achieves capacity with a double-exponential decay of the maximal probability of error. We also study the causal case for which we derive an achievable region, which is typically strictly larger than the region achievable with naïve Shannon strategies.

Key Agreement over a Generalized Multiple Access Channel Using Noiseless and Noisy Feedback

A secret key agreement framework involving three users is considered in which each of the users 1 and 2 intends to share a secret key with user 3 and users 1 and 2 are eavesdroppers with respect to each other. There is a generalized discrete memoryless multiple access channel (GDMMAC) from users 1 and 2 to user 3 where the three users receive outputs from the channel. Furthermore, there is a feedback channel from user 3 to users 1 and 2 through which user 3 sends information extracted from the received output from the GDMMAC to increase the key rates. We consider both noiseless and noisy feedback. In the case of noiseless feedback, a public channel of unlimited capacity from user 3 to users 1 and 2 is used only once. In the case of noisy feedback, a noisy broadcast channel (BC) from user 3 to users 1 and 2 can be repeatedly used, like GDMMAC. In both setups, inner bounds of the secret key capacity region are derived. The secret key capacity region is derived in some special cases where the channel inputs and outputs form Markov chains in certain orders. For illustration, the corresponding results are also derived and discussed for Gaussian channels. The cases with noiseless feedback, noisy feedback, and no feedback at all are compared with each other.

Multiple-access channel with correlated states and cooperating encoders

In this study, a two-user discrete memoryless multiple-access channel with two correlated states known non-causally at the corresponding encoder is considered. Each encoder transmits a message independent of the other encoder's and tries to cooperate with it. To consider cooperative encoders, it is assumed that each encoder strictly-causally receives and finds out the other encoder's transmitted signals and tries to cooperate with the other encoder by transmitting its message. A special case is also studied in which the common part of the states is known at the both encoders, resulting in a larger rate region. For these two scenarios, achievable rate regions are derived using a combination of block-Markov and Gel'fand-Pinsker coding techniques, and outer bounds are also established. For the second scenario, the achievable rate region of the Gaussian model is derived, and some implications of the results are discussed.

Distributed Structure: Joint Expurgation for the Multiple-Access Channel

In this work we show how an improved lower bound to the error exponent of the memoryless multiple-access (MAC) channel is attained via the use of linear codes, thus demonstrating that structure can be beneficial even in cases where there is no capacity gain. We show that if the MAC channel is modulo-additive, then any error probability, and hence any error exponent, achievable by a linear code for the corresponding single-user channel, is also achievable for the MAC channel. Specifically, for an alphabet of prime cardinality, where linear codes achieve the best known exponents in the single-user setting and the optimal exponent above the critical rate, this performance carries over to the MAC setting. At least at low rates, where expurgation is needed, our approach strictly improves performance over previous results, where expurgation was used at most for one of the users. Even when the MAC channel is not additive, it may be transformed into such a channel. While the transformation is lossy, we show that the distributed structure gain in some "nearly additive" cases outweighs the loss, and thus the error exponent can improve upon the best known error exponent for these cases as well. Finally we apply a similar approach to the Gaussian MAC channel. We obtain an improvement over the best known achievable exponent, given by Gallager, for certain rate pairs, using lattice codes which satisfy a nesting condition.

On the Structure of the Capacity Region of Asynchronous Memoryless Multiple-Access Channels

The asynchronous capacity region of memoryless multiple-access channels is the union of certain polytopes. It is well-known that vertices of such polytopes may be approached via a technique called successive decoding. It is also known that an extension of successive decoding applies to the dominant face of such polytopes. The extension consists of forming groups of users in such a way that users within a group are decoded jointly whereas groups are decoded successively. This paper goes one step further. It is shown that successive decoding extends to every face of the above mentioned polytopes. The group composition as well as the decoding order for all rates on a face of interest are obtained from a label assigned to that face. From the label one can extract a number of structural properties, such as the dimension of the corresponding face and whether or not two faces intersect. Expressions for the the number of faces of any given dimension are also derived from the labels.