Mismatched decoding and the multiple-access channel

An achievable region is derived for the multiple-access channel under decoding mismatch conditions. It is shown that achievable rates higher than the random coding capacity of the single-user mismatched channel can sometimes be demonstrated by treating the single-user channel as a multiple-access channel. Refining these ideas we derive a lower bound on the capacity of the mismatched single-user channel, which is tighter than previously published bounds. Using this bound, we are able to answer in the negative the question raised by Csiszar and Narayan (see ibid., vol.41, no.1, p.35, 1995) as to whether equality between the mismatch capacity and the matched capacity implies that the random coding lower bound to the mismatch capacity is tight     

On the reliability function of the ideal Poisson channel withnoiseless feedback

A coding scheme for the channel under peak power and average power constraints on the input is presented, and its asymptotic error exponent is shown to coincide, at all rates below capacity, with the sphere packing error exponent, which, for the case at hand, is known to be unachievable without feedback for rates below the critical rate. An upper bound on the error exponent achievable with feedback is also derived and shown, under a capacity reducing average power constraint, to coincide with the error exponent achieved by the proposed coding scheme; in such a case the coding scheme is asymptotically optimal. Thus, the ideal Poisson channel, limited by a capacity-reducing average power constraint, provides a nontrivial example of a channel for which the reliability function is known exactly both with and without feedback. It is shown that a slight modification of the coding scheme to one of random transmission time can achieve zero-error probability for any rate lower than the ordinary average-error channel capacity     

Underwater Acoustic Networks: Channel Models and Network Coding Based Lower Bound to Transmission Power for Multicast

The goal of this paper is two-fold. First, to establish a tractable model for the underwater acoustic channel useful for network optimization in terms of convexity. Second, to propose a network coding based lower bound for transmission power in underwater acoustic networks, and compare this bound to the performance of several network layer schemes. The underwater acoustic channel is characterized by a path loss that depends strongly on transmission distance and signal frequency. The exact relationship among power, transmission band, distance and capacity for the Gaussian noise scenario is a complicated one. We provide a closed-form approximate model for 1) transmission power and 2) optimal frequency band to use, as functions of distance and capacity. The model is obtained through numerical evaluation of analytical results that take into account physical models of acoustic propagation loss and ambient noise. Network coding is applied to determine a lower bound to transmission power for a multicast scenario, for a variety of multicast data rates and transmission distances of interest for practical systems, exploiting physical properties of the underwater acoustic channel. The results quantify the performance gap in transmission power between a variety of routing and network coding schemes and the network coding based lower bound. We illustrate results numerically for different network scenarios.     

A lower bound on the probability of decoding error for the finite-state channel (Corresp.)

A new lower bound on the probability of decoding error for transmission at high rates over a finite-state channel is obtained. It is a dual to the random coding bound of Yudkin and is a generalization of the Arimoto converse to the coding theorem for discrete memoryless channels. It also implies the strong converse to the coding theorem for indecomposable channels.     

The random coding bound is tight for the average code (Corresp.)

The random coding bound of information theory provides a well-known upper bound to the probability of decoding error for the best code of a given rate and block length. The bound is constructed by upper-bounding the average error probability over an ensemble of codes. The bound is known to give the correct exponential dependence of error probability on block length for transmission rates above the critical rate, but it gives an incorrect exponential dependence at rates below a second lower critical rate. Here we derive an asymptotic expression for the average error probability over the ensemble of codes used in the random coding bound. The result shows that the weakness of the random coding bound at rates below the second critical rate is due not to upperbounding the ensemble average, but rather to the fact that the best codes are much better than the average at low rates.     

获取高斯MIMO广播信道和容量域的一种方法

针对脏纸编码方法很难直接计算广播信道和容量域边界值问题,提出了一种计算多接入信道和容量的迭代注水算法以及获取最大和容量的次优传输策略,利用广播信道与多接入信道的对偶性,将该和容量结果和传输策略通过简单的映射关系转换成广播信道和容量的边界值和优化传输策略。数值结果表明所提的迭代算法简单有效,给出的传输策略可以有效逼近广播信道理论和容量边界,在MIMO下行链路中可得到应用。     

On coding without restrictions for the AWGN channel

Many coded modulation constructions, such as lattice codes, are visualized as restricted subsets of an infinite constellation (IC) of points in the n-dimensional Euclidean space. The author regards an IC as a code without restrictions employed for the AWGN channel. For an IC the concept of coding rate is meaningless and the author uses, instead of coding rate, the normalized logarithmic density (NLD). The maximum value C_∞ such that, for any NLD less than C_∞, it is possible to construct an PC with arbitrarily small decoding error probability, is called the generalized capacity of the AWGN channel without restrictions. The author derives exponential upper and lower bounds for the decoding error probability of an IC, expressed in terms of the NLD. The upper bound is obtained by means of a random coding method and it is very similar to the usual random coding bound for the AWGN channel. The exponents of these upper and lower bounds coincide for high values of the NLD, thereby enabling derivation of the generalized capacity of the AWGN channel without restrictions. It is also shown that the exponent of the random coding bound can be attained by linear ICs (lattices), implying that lattices play the same role with respect to the AWGN channel as linear-codes do with respect to a discrete symmetric channel     

Coding theorems for the nonsynchronized channel

Capacity and error bounds are derived for a memoryless binary symmetric channel with the receiver having no a priori information as to the starting time of the code words. The channel capacity is the same as the capacity of the synchronized channel. For all rates below capacity, the minimum probability of error for the nonsynchronized channel decreases exponentially with the code-block length. For rates near channel capacity, the exponent in the upper bound on the probability of error for the nonsynchronized channel is the same as the corresponding exponent for the synchronized channel. For low rates, the largest exponent obtained for the nonsynchronized channel with conventional block coding is inferior to the exponent obtained for the synchronized channel. Stronger results are obtained for a new form of coding that allows for a Markov dependency between successive code words. Bounds on the minimum probability of error are obtained for unconstrained binary codes and for several classes of parity-check codes and are used to obtain asymptotic distance properties for various classes of binary codes. At certain rates there exist codes whose minimum distance, in the comma-free sense, is not only greater than one, but is proportional to the block length.     

On the capacity region of wireless ad hoc relay networks

I. Introduction Wireless ad hoc network regarded as a risingnetwork model has been discussed widely. Thestudy of the capacity of wireless ad hoc networkshas received significant attention recently. Guptaand Kumar in Ref.[1] proposed a model for studyingthe capacity of fixed ad hoc networks, where nodesare randomly located but are stationary. They madea somewhat pessimistic conclusion that the trafficrate per Source-to-Destination (S-D) pair will go tozero as the number of nodes per unit are…     

On the error exponent of trellis source coding

In this paper, we develop a single-letter lower bound on the error exponent for the problem of trellis source coding. We demonstrate that for the case of a binary source with the Hamming distortion measure, and for rates close to the rate-distortion curve, this bound is superior to Marton's block-coding exponent, for the same computational complexity.     

物理层网络编码在数据会聚无线自组织网络中的容量增益研究

为研究物理层网络编码.(Physical-layer Network Coding,PNC).方案在数据汇聚无线自组织网络中相对于传统方案能够获得的容量增益,该文通过稀疏割容量分析推导得到PNC方案平均每节点信息传输速率的上界和下界。与传统路由方案及传统网络编码方案相比,在数据汇聚无线自组织网络中应用PNC方案能够提升网络容量的数量级。     

Improved bit-stuffing bounds on two-dimensional constraints

We derive lower bounds on the capacity of certain two-dimensional (2-D) constraints by considering bounds on the entropy of measures induced by bit-stuffing encoders. A more detailed analysis of a previously proposed bit-stuffing encoder for (d,/spl infin/)-runlength-limited (RLL) constraints on the square lattice yields improved lower bounds on the capacity for all d /spl ges/ 2. This encoding approach is extended to (d,/spl infin/)-RLL constraints on the hexagonal lattice, and a similar analysis yields lower bounds on the capacity for d /spl ges/ 2. For the hexagonal (1,/spl infin/)-RLL constraint, the exact coding ratio of the bit-stuffing encoder is calculated and is shown to be within 0.5% of the (known) capacity. Finally, a lower bound is presented on the coding ratio of a bit-stuffing encoder for the constraint on the square lattice where each bit is equal to at least one of its four closest neighbors, thereby providing a lower bound on the capacity of this constraint.     

SVD iterative detection of turbo-coded multiantenna unitary differential modulation

A new suboptimal demodulator based on a singular value decomposition for estimation of unitary matrices is introduced. Noncoherent communication over the Rayleigh flat fading channel with multiple transmit and receive antennas, where no channel state information is available at the receiver is investigated. Codes achieving bit-error rate (BER) lower than 10/sup -4/ at bit energy over the noise spectral density ratio (E/sub b//N/sub 0/) of 1.6-1.9 dB from code restricted capacity limit were found. At higher data rates, computation of code restricted capacity is impractical. Therefore, the mutual information upper bound of the capacity attaining isotropically random unitary transmit matrices was used. The codes achieve BER lower than 10/sup -4/ at E/sub b//N/sub 0/ of 3.2-6 dB from this bound, with coding rates of 1.125-5.06 bits per channel use, and different modulation decoding complexities. The codes comprise a serial concatenation of turbo code and a unitary matrix differential modulation code. The receiver employs the high-performance coupled iterative decoding of the turbo code and the modulation code. Information theoretic arguments are harnessed to form guidelines for code design and to evaluate performance of the iterative decoder.     

Capacity and zero-error capacity of Ising channels

Simple binary symmetric one- and two-dimensional channel systems called Ising channels are investigated. The one-dimensional version is a certain binary finite-state channel with input intersymbol interference. Its zero-error capacity is determined together with lower and upper bounds to its Shannon capacity. For the two-dimensional channel system, a lower bound is obtained for the zero-error capacity, and an efficient zero-error coding scheme is developed     

Bounds on capacity and minimum energy-per-bit for AWGN relay channels

Upper and lower bounds on the capacity and minimum energy-per-bit for general additive white Gaussian noise (AWGN) and frequency-division AWGN (FD-AWGN) relay channel models are established. First, the max-flow min-cut bound and the generalized block-Markov coding scheme are used to derive upper and lower bounds on capacity. These bounds are never tight for the general AWGN model and are tight only under certain conditions for the FD-AWGN model. Two coding schemes that do not require the relay to decode any part of the message are then investigated. First, it is shown that the "side-information coding scheme" can outperform the block-Markov coding scheme. It is also shown that the achievable rate of the side-information coding scheme can be improved via time sharing. In the second scheme, the relaying functions are restricted to be linear. The problem is reduced to a "single-letter" nonconvex optimization problem for the FD-AWGN model. The paper also establishes a relationship between the minimum energy-per-bit and capacity of the AWGN relay channel. This relationship together with the lower and upper bounds on capacity are used to establish corresponding lower and upper bounds on the minimum energy-per-bit that do not differ by more than a factor of 1.45 for the FD-AWGN relay channel model and 1.7 for the general AWGN model.     

Random coding theorems for the general discrete memoryless broadcast channel

Three different communication situations are considered for the general nondegraded discrete memoryless broadcast channel with two components. In the most general situation, common and separate information is sent to both receivers. In another situation, only separate information is sent, and in a third, one Common and one separate message is sent. For each communication situation a random coding inner bound on the capacity region is derived. An example is presented which Shows that in the most general situation the inner bound strictly dominates the family of rates obtained by time-sharing. The capacity region for the general situation is characterized by a limiting expression. The relationship with the degraded broadcast channel and the connection with other multiway channels, such as the channel with two senders and two receivers, is shown.     

Capacity Theorems for the “Z” Channel

We consider the two-user "Z" channel (ZC), where there are two senders and two receivers. One of the senders transmits information to its intended receiver (without interfering with the unintended receiver), while the other sender transmits information to both receivers. The complete characterization of the discrete memoryless ZC remains unknown to date. For the Gaussian ZC, the capacity has only been established for a crossover link gain of 1. In this work, we study both the discrete memoryless ZC and the Gaussian ZC. We first establish achievable rates for the general discrete memoryless ZC. The coding strategy uses rate-splitting and superposition coding at the sender with information for both receivers. At the receivers, we use joint decoding. We then specialize the rates obtained to two different types of degraded discrete memoryless ZCs and also derive respective outer bounds to their capacity regions. We show that as long as a certain condition is satisfied, the achievable rate region is the capacity region for one type of degraded discrete memoryless ZC. The results are then extended to the two-user Gaussian ZC with different crossover link gains. We determine an outer bound to the capacity region of the Gaussian ZC with strong crossover link gain and establish the capacity region for moderately strong crossover link gain     

Optimal training for MIMO frequency-selective fading channels

High data rates give rise to frequency-selective propagation effects. Space-time multiplexing and/or coding offer attractive means of combating fading and boosting capacity of multi-antenna communications. As the number of antennas increases, channel estimation becomes challenging because the number of unknowns increases, and the power is split at the transmitter. Optimal training sequences have been designed for flat-fading multi-antenna systems or for frequency-selective single transmit antenna systems. We design a low-complexity optimal training scheme for block transmissions over frequency-selective channels with multiple antennas. The optimality in designing our training schemes consists of maximizing a lower bound on the ergodic (average) capacity that is shown to be equivalent to minimizing the mean square error of the linear channel estimator. Simulation results confirm our theoretical analysis that applies to both single- and multicarrier transmissions.     

Turbo space-time processing to improve wireless channel capacity

By deriving a generalized Shannon capacity formula for multiple-input, multiple-output Rayleigh fading channels, and by suggesting a layered space-time architecture concept that attains a tight lower bound on the capacity achievable. Foschini (see Wireless Pers. Commun., vol.6, no.3, p.311-35, 1998) has shown a potential enormous increase in the information capacity of a wireless system employing multiple-element antenna arrays at both the transmitter and receiver. The layered space-time architecture allows signal processing complexity to grow linearly, rather than exponentially, with the promised capacity increase. This paper includes two important contributions. First, we show that Foschini's lower bound is, in fact, the Shannon bound when the output signal-to-noise ratio (SNR) of the space-time processing in each layer is represented by the corresponding "matched filter" bound. This proves the optimality of the layered space-time concept. Second, we present an embodiment of this concept for a coded system operating at a low average SNR and in the presence of possible intersymbol interference. This embodiment utilizes the already advanced space-time filtering, coding and turbo processing techniques to provide yet a practical solution to the processing needed. Performance results are provided for quasi-static Rayleigh fading channels with no channel estimation errors. We see for the first time that the Shannon capacity for wireless communications can be both increased by N times (where N is the number of the antenna elements at the transmitter and receiver) and achieved within about 3 dB in average SNR about 2 dB of which is a loss due to the practical coding scheme we assume-the layered space-time processing itself is nearly information-lossless.     

Reliability function of a discrete memoryless channel at rates above capacity (Corresp.)

Asymptotically coincident upper and lower bounds on the exponent of the largest possible probability of the correct decoding of block codes are given for all rates above capacity. The lower bound sharpens Omura's bound. The upper bound is proved by a new and simple combinatorial argument.