Yossef Steinberg

The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel

The Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC) is considered. The dirty-paper coding (DPC) rate region is shown to coincide with the capacity region. To that end, a new notion of an enhanced broadcast channel is introduced and is used jointly with the entropy power inequality, to show that a superposition of Gaussian codes is optimal for the degraded vector broadcast channel and that DPC is optimal for the nondegraded case. Furthermore, the capacity region is characterized under a wide range of input constraints, accounting, as special cases, for the total power and the per-antenna power constraints

The capacity region of the Gaussian MIMO broadcast channel

The dirty paper coding rate region is shown to be the capacity region of the Gaussian MIMO broadcast channel. To that end, a new notion of an enhanced broadcast channel is introduced.

Coding for the degraded broadcast channel with random parameters, with causal and noncausal side information

In this work, coding for the degraded broadcast channel controlled by random parameters is studied. Two main paradigms are considered: where side information on the random parameters is provided to the transmitter in a noncausal manner (termed here noncausal coding), and where side information is provided in a causal manner (termed causal coding). Inner and outer bounds are derived on the capacity region with noncausal coding. For the special case where the nondegraded user is informed about the channel parameters, it is shown that the inner bound is tight, thus deriving the capacity region for that case. For causal coding, a single-letter characterization of the capacity region is derived. This characterization is expressed via auxiliary random variables (RVs), and can also be interpreted by means of Shannon strategies, as the formula for the capacity of the single-user channel with causal coding derived by Shannon. The capacity region of a class of binary broadcast channels with causal coding is computed, as an example. Applications to watermarking are suggested. In particular, the results on noncausal coding can be used to derive the capacity region of a watermarking system where the channel (attacker) is fixed, and the watermark is subject to several stages of attack, or a watermarking system where the encoder is required to encode watermarks for both private and public users

Communication Via Decentralized Processing

The problem of a nomadic terminal sending information to a remote destination via agents with lossless connections to the destination is investigated. Such a setting suits, e.g., access points of a wireless network where each access point is connected by a wire to a wireline-based network. The Gaussian codebook capacity for the case where the agents do not have any decoding ability is characterized for the Gaussian channel. This restriction is demonstrated to be severe, and allowing the nomadic transmitter to use other signaling improves the rate. For both general and degraded discrete memoryless channels, lower and upper bounds on the capacity are derived. An achievable rate with unrestricted agents, which are capable of decoding, is also given and then used to characterize the capacity for the deterministic channel.

The Capacity Region of the Degraded Multiple-Input Multiple-Output Compound Broadcast Channel

The capacity region of a compound multiple-antenna broadcast channel is characterized when the users exhibit a certain degradedness order. The channel under consideration has two users, each user has a finite set of possible realizations. The transmitter transmits two messages, one for each user, in such a manner that regardless of the actual realizations, both users will be able to decode their messages correctly. An alternative view of this channel is that of a broadcast channel with two common messages, each common message is intended to a different set of users. The degradedness order between the two sets of realizations/users is defined through an additional, fictitious, user whose channel is degraded with respect to all realizations/users from one set while all realizations/users from the other set are degraded with respect to him.

Achievable rates for the broadcast channel with states known at the transmitter

In this paper we study coding for the general broadcast channel, controlled by random parameters, where the parameters are provided to the encoder only, in a non-causal manner. We give an achievable region which is an extension of the Marion region to the current model. The region we derive is shown to be tight for the Gaussian broadcast channel with additive interference at the two channels

Distributed MIMO Receiver—Achievable Rates and Upper Bounds

A multiple-input multiple-output (MIMO) system with a distributed receiver is considered. The system consists of a nomadic transmitter with several antennas, whose signal is received by multiple agents, exhibiting independent channel gains and an additive circular-symmetric Gaussian noise. In the nomadic regime, we assume that the agents do not have any decoding ability. These agents process their channel observations and forward them to the final destination through unidirectional lossless links with a fixed capacity. We propose new achievable rates based on elementary compression and on Wyner-Ziv (WZ)or chief executive officer (CEO) processing, for both fast-fading and block-fading channels, as well as for general discrete channels. The simpler two agents scheme is solved, up to an implicit equation with a single variable. Limiting the nomadic transmitter to circular-symmetric Gaussian signaling, new upper bounds are derived, based on the vector version of the entropy power inequality. Several asymptotic settings are analyzed. In addition, the upper bounds are analytically shown to be tight for several examples, while numerical calculations reveal a rather small gap in a finite 2 times 2 setting. The advantage of the WZ approach over elementary compression is shown, where only the former can achieve the optimal diversity-multiplexing tradeoff (DMT).

On the Capacity Region of the Multi-Antenna Broadcast Channel with Common Messages

In this paper we discuss a two user multi-antenna Gaussian broadcast channel with common messages and explore the achievable region suggested by Jindal and Goldsmith. We present simple outer-bounds which are shown to be tight at certain regions. We investigate the aligned channel with common messages and show that beyond a certain threshold on the common rate, the achievable region coincides with the capacity region and we also give a full characterization of the capacity region of the degraded message sets case

Coding and Common Reconstruction

This work studies problems of source and joint source-channel coding under the requirement that the encoder can produce an exact copy of the compressed source constructed by the decoder. This requirement, termed here as the common reconstruction constraint (CR), is satisfied automatically in rate-distortion theory for single sources. However, in the common formulation of problems of lossy source coding with side information at the decoder (the Wyner-Ziv problem), distributed source coding, and joint source-channel coding for networks, the destination can exploit the information it receives in a manner that cannot be exactly reproduced at the sender side. Some applications, like the transmission of sensitive medical information, may require that both sides-the sender and the receiver-will share a common version of the compressed data, for the purpose of future discussions or consulting. The purpose of this work is to study the implications of CR constraints on the achievable rates in scenarios of lossy source coding and lossy transmission of sources. Three problems are examined: source coding with side information at the decoder, simultaneous transmission of data and state over state-dependent channels, and joint source-channel coding for the degraded broadcast channel. Single-letter characterizations of the optimal performance are developed for these problems, under corresponding CR constraints. Implications of this constraint on problems of joint source-channel coding in networks are discussed.

Gaussian codes and weighted nearest neighbor decoding in fading multiple-antenna channels

We investigate the fading multiple-antenna channel. The decoder is assumed to possess imperfect channel fading information. A modified nearest neighbor decoder with an innovative weighting factor is introduced and an expression for the generalized mutual information (GMI), the achievable rate, is obtained. We show that under certain conditions the achievable rate is equivalent to that of a fading multiple-antenna Gaussian channel where fading is known to the receiver and is equal to the channel estimation, and where noise is due to both the channel noise and the channel estimation error. We show that for our communication scheme, the minimum mean square error (MMSE) channel estimator is optimal in the sense that it achieves the highest value of GMI, and hence the highest communication rate. Additionally, a training based multiple-input multiple-output (MIMO) scheme in a block-fading channel is investigated and it is shown that the number of degrees of freedom depends on the signal-to-noise ratio (SNR).