This article focuses on the compressed representations of the pictures

We consider a user communicating over a fading channel with perfect channel state information. Data is assumed to arrive from some higher layer application and is stored in a buffer until it is transmitted. We study adapting the user's transmission rate and power based on the channel state information as well as the buffer occupancy; the objectives are to regulate both the long-term average transmission power and the average buffer delay incurred by the traffic. Two models for this situation are discussed; one corresponding to fixed-length/variable-rate codewords and one corresponding to variable-length codewords. The trade-off between the average delay and the average transmission power required for reliable communication is analyzed. A dynamic programming formulation is given to find all Pareto optimal power/delay operating points. We then quantify the behavior of this tradeoff in the regime of asymptotically large delay. In this regime we characterize simple buffer control policies which exhibit optimal characteristics. Connections to the delay-limited capacity and the expected capacity of fading channels are also discussed.

Abstract—Multiple description (MD) coding is source coding in which several descriptions of the source are produced such that various reconstruction qualities are obtained from different subsets of the descriptions. Unlike multiresolution or layered source coding, there is no hierarchy of descriptions; thus, MD coding is suitable for packet erasure channels or networks without priority provisions. Generalizing work by Orchard, Wang, Vaishampayan, and Reibman, a transform-based approach is developed for producing descriptions of an-tuple source,. The descriptions are sets of transform coefficients, and the transform coefficients of different descriptions are correlated so that missing coefficients can be estimated. Several transform optimization results are presented for memoryless Gaussian sources, including a complete solution of the aP, aPcase with arbitrary weighting of the descriptions. The technique is effective only when independent components of the source have differing variances. Numerical studies show that this method performs well at low redundancies, as compared to uniform MD scalar quantization. Index Terms—Erasure channels, integer-to-integer transforms, packet networks, robust source coding.

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We study di#erent notions of capacity for time-slotted ALOHA systems. In these systems multiple users synchronously send packets in a bursty manner over a common additive white Gaussian noise (AWGN) channel. The users do not coordinate their transmissions, which may collide at the receiver. For such a system we define both single-slot capacity and multiple-slot capacity. We then construct a coding and decoding scheme for single-slot capacity that achieves any rate within this capacity region. This coding and decoding scheme for a single time slot combines aspects of multiple access rate splitting and of broadcast codes for degraded AWGN channels. This design allows some bits to be reliably received even when collisions occur, and more bits to be reliably received in the absence of collisions. The exact number of bits reliably received under both of these scenarios is part of the code design process, which we optimize to maximize the expected rate in each slot.

Abstract — We consider three capacity definitions for general channels with channel side information at the receiver, where the channel is modeled as a sequence of finite dimensional conditional distributions not necessarily stationary, ergodic, or information stable. The Shannon capacity is the highest rate asymptotically achievable with arbitrarily small error probability. The outage capacity is the highest rate asymptotically achievable with a given probability of decoder-recognized outage. The expected capacity is the highest expected rate asymptotically achievable with a single encoder and multiple decoders, where the channel side information determines the decoder in use. Expected capacity equals Shannon capacity for channels governed by a stationary ergodic random process but is typically greater for general channels. These alternative definitions essentially relax the constraint that all transmitted information must be decoded at the receiver. We derive equations for these capacity definitions through information density. Examples are also provided to demonstrate their implications. I.

. We consider the capacity of time-slotted ALOHA systems, where multiple users synchronously send packets, which may collide at the receiver. Specific coding for ALOHA systems had previously been proposed to avoid complete loss of packets involved in collisions, but the capacity of ALOHA systems had not been previously determined. We consider capacity in terms of reliably received rate rather than transmitted rate. We consider capacity achieving strategies under AWGN for transmission of a single packet which is long enough to achieve capacity over the duration of the packet. We combine concepts from multi-access channels and broadcast channels to determine the capacity region for a single transmission of a packet in an ALOHA system. The coding for each user takes into account the possibility of collisions with other users in order to establish a capacity region. We derive, according to the users' energies and their probabilities of transmission, the coding and decosing schemes which ac...

The problem of placing known symbols in a data stream for a slowly varying frequency selective channel is considered from an information-theoretic perspective. Given the amount of redundancy associated with known symbols, placement schemes that minimize the outage probability are derived by assuming that the transmitted codewords consist of packets that are constrained to have the same known symbol placement. Under the assumption that each known symbol cluster is at least as large as a _ 2L + 1 (where L is the channel order), we show that the optimal placement is obtained by arranging the known symbols into as many clusters as possible and placing them such that the unknown symbol blocks are as equal as possible. It is shown that the optimal placement of known symbol clusters does not depend on the probability density of the channel. Under some further constraints, it is shown that the placement schemes derived are optimal in the frame work of error exponents as well. Numerical examples are used to illustrate the ideas and potential gains of using optimal known symbol placement.

Abstract — We compare two strategies for lossy source description across a pair of unreliable channels. In the first strategy, we use a broadcast channel code to achieve a different rate for each possible channel realization, and then use a multiresolution source code to describe the source at the resulting rates. In the second strategy, we use a channel coding strategy for two independent channels coupled with a multiple description source code. In each case, we choose the coding parameters to minimize the expected end-to-end distortion in the source reconstruction. We demonstrate that in point-to-point communication across a pair of non-ergodic channels, multiple description coding can provide substantial gains relative to mulitresolution and broadcast coding. We then investigate this comparison in a simple MIMO channel. We demonstrate the inferior performance of space time coding with multiresolution source coding and broadcast channel coding relative to multiple description codes and a time sharing channel coding strategy. These results indicate that for non-ergodic channels, the traditional definition of channel capacity does not necessarily lead to the best channel code from the perspective of end-to-end source distortion. I.

We provide an information theoretic perspective on the problem of throughput maximization in a block flat fading wireless data system with codeword lengths restricted to be less than the fade block duration. We assume no channel state information at the transmitter (CSIT) and perfect channel state information at the receiver (CSIR). We explore the tradeoffs between using a single codebook vs multiple codebooks (ratesplitting) on Single Input Single Output (SISO) channels, and scalar coding vs vector coding for diagonal Multiple Input Multiple Output (MIMO) channels. For all log-concave scalar channel fade distributions, we show that using multiple codebooks increases the average throughput of the system when the multiple codewords are transmitted simultaneously in time, frequency and space over the same channel. Splitting the channel orthogonally in time, frequency, or among the inputs of a MIMO system and then transmitting different codewords on each orthogonal sub-channel significantly reduces the achievable average throughput. I.