Abstract not found

In this paper we review the most peculiar and interesting information-theoretic and communications features of fading channels. We first describe the statistical models of fading channels which are frequently used in the analysis and design of communication systems. Next, we focus on the information theory of fading channels, by emphasizing capacity as the most important performance measure. Both single-user and multiuser transmission are examined. Further, we describe how the structure of fading channels impacts code design, and finally overview equalization of fading multipath channels.

In many communication situations, the transmitter and the receiver must be designed without a complete knowledge of the probability law governing the channel over which transmission takes place. Various models for such channels and their corresponding capacities are surveyed. Special emphasis is placed on the encoders and decoders which enable reliable communication over these channels.

In a point-to-point wireless fading channel, multiple transmit and receive antennas can be used to improve the reliability of reception (diversity gain) or increase the rate of communication for a fixed reliability level (multiplexing gain). In a multiple access situation, multiple receive antennas can also be used to spatially separate signals from different users (multiple access gain). Recent work has characterized the fundamental tradeoff between diversity and multiplexing gains in the point-to-point scenario. In this paper, we extend the results to a multiple access fading channel. Our results characterize the fundamental tradeoff between the three types of gain and provide insights on the capabilities of multiple antennas in a network context. 1

In multiaccess wireless systems, dynamic allocation of resources such as transmit power, bandwidths, and rates is an important means to deal with the time-varying nature of the environment. In this two-part paper, we consider the problem of optimal resource allocation from an information-theoretic point of view. We focus on the multiaccess fading channel with Gaussian noise, and define two notions of capacity depending on whether the traffic is delay-sensitive or not. In Part I, we have analyzed the throughput capacity region which characterizes the long-term achievable rates through the time-varying channel. However, the delay experienced depends on how fast the channel varies. In the present paper, Part II, we introduce a notion of delay-limited capacity which is the maximum rate achievable with delay independent of how slow the fading is. We characterize the delay-limited capacity region of the multiaccess fading channel and the associated optimal resource allocation schemes. We show that successive decoding is optimal, and the optimal decoding order and power allocation can be found explicitly as a function of the fading states; this is a consequence of an underlying polymatroid structure that we exploit.

A simple idealized linear (and planar) uplink, cellular, multiple-access communication model, where only adjacent cell interference is present and all signals may experience fading is considered. Shannon theoretic arguments are invoked to gain insight into the implications on performance of the main system parameters and multiple-access techniques. The model treated in Part I [1] is extended here to account for cell-site receivers that may process also the received signal at an adjacent cell site, compromising thus between the advantage of incorporating additional information from other cell sites on one hand and the associated excess processing complexity on the other. Various settings which include fading, time-division multiple access (TDMA), wideband (WB), and (optimized) fractional inter-cell time sharing (ICTS) protocols are investigated and compared. In this case and for the WB approach and a large number of users per cell it is found, surprisingly, that fading may enhance performance in terms of Shannon theoretic achievable rates. The linear model is extended to account for general linear and planar configurations. The effect of a random number of users per cell is investigated and it is demonstrated that randomization is beneficial. Certain aspects of diversity as well as some features of TDMA and orthogonal code-division multiple access (CDMA) techniques in the presence of fading are studied in an isolated cell scenario.

The transmission capacity of a wireless ad hoc network can be defined as the maximum allowable area spectral efficiency such that the outage probability does not exceed some specified threshold. This work studies the improvement in transmission capacity obtainable with successive interference cancellation (SIC), an important receiver technique that has been shown to achieve the capacity of several classes of multiuser channels, but has not been carefully evaluated in the context of an ad hoc wireless network. This paper develops closedform bounds for the transmission capacity of CDMA ad hoc networks with SIC receivers, for both perfect and imperfect interference cancellation. In addition to providing the first closedform capacity results for SIC in ad hoc networks (or, to our knowledge, any type of multiuser detection), design-relevant insights are made possible. In particular, although the capacity gain from perfect SIC is very large, any imperfections in the interference cancellation rapidly degrade its usefulness. More encouragingly from a receiver complexity standpoint, due to the geographic properties of ad hoc networks, only a few – often just one – interfering nodes need to be cancelled in order to get the vast majority of the available performance gain.

It is shown that the encoding/decoding problem for any asynchronous M-user discrete memoryless multiple-access channel can be reduced to the corresponding problems for at most 2M \Gamma 1 single-user discrete memoryless channels. This result, which extends a similar result for Gaussian channels, reduces the seemingly hard task of finding good multiple-access codes to the much better understood task of finding good codes for single-user channels. As a by-product, some interesting properties of the asynchronous capacity region of M-user discrete memoryless channels are derived. Key words: Multiple Access, Interference Cancellation, Asynchronous Capacity Region, Rate Splitting, Degree. 1 Introduction Rate-splitting multiple access (RSMA) is a new multiple-access technique that allows one to approach any rate in the (asynchronous) capacity region of any discrete memoryless multiple-access channel using (essentially) only two powerful error-control codes at each transmitter and the corresp...

Synchronous code-division multiple-access communication systems with randomly chosen spreading sequences and capacity-achieving forward error correction coding are analyzed in terms of spectral efficiency. Emphasis is on the penalties paid by applying single user coding in conjuction with suboptimal multiuser receivers as opposed to optimal joint decoding which involves complexity that is exponential in the number of users times the codeword length. The conventional, the decorrelating and the (re-encoded) decorrelating decision-feedback detectors are analyzed in the nonasymptotic case for spherical random sequences. The re-encoded minimum mean squared error (MMSE) decision-feedback receiver achieving the same performance as joint multiuser decoding for equal power users is shown to be suboptimal in the case of equal rates.

This paper discusses the Slepian–Wolf problem of distributed near-lossless compression of correlated sources. We introduce practical new tools for communicating at all rates in the achievable region. The technique employs a simple “sourcesplitting” strategy that does not require common sources of randomness at the encoders and decoders. This approach allows for pipelined encoding and decoding so that the system operates with the complexity of a single user encoder and decoder. Moreover, when this splitting approach is used in conjunction with iterative decoding methods, it produces a significant simplification of the decoding process. We demonstrate this approach for synthetically generated data. Finally, we consider the Slepian–Wolf problem when linear codes are used as syndrome-formers and consider a linear programming relaxation to maximum-likelihood (ML) sequence decoding. We note that the fractional vertices of the relaxed polytope compete with the optimal solution in a manner analogous to that observed when the “min-sum ” iterative decoding algorithm is applied. This relaxation exhibits the ML-certificate property: if an integral solution is found, it is the ML solution. For symmetric binary joint distributions, we show that selecting easily constructable “expander”-style low-density parity check codes (LDPCs) as syndrome-formers admits a positive error exponent and therefore provably good performance.