Amichai Sanderovich

Uplink Macro Diversity of Limited Backhaul Cellular Network

In this work, new achievable rates are derived for the uplink channel of a cellular network with joint multicell processing (MCP), where unlike previous results, the ideal backhaul network has finite capacity per cell. Namely, the cell sites are linked to the central joint processor via lossless links with finite capacity. The new rates are based on compress-and-forward schemes combined with local decoding. Further, the cellular network is abstracted by symmetric models, which render analytical treatment plausible. For this family of idealistic models, achievable rates are presented for both Gaussian and fading channels. The rates are given in closed form for the classical Wyner model and the soft-handover model. These rates are then demonstrated to be rather close to the optimal unlimited backhaul joint processing rates, even for modest backhaul capacities, supporting the potential gain offered by the joint MCP approach. Particular attention is also given to the low-signal-to-noise ratio (SNR) characterization of these rates through which the effect of the limited backhaul network is explicitly revealed. In addition, the rate at which the backhaul capacity should scale in order to maintain the original high-SNR characterization of an unlimited backhaul capacity system is found.

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.

Uplink Macro Diversity with Limited Backhaul Capacity

In this contribution we present new achievable rates, for the non-fading uplink channel of a cellular network, with joint cell-site processing, where unlike previous results, the error-free backhaul network has finite capacity per-cell. Namely, the cell-sites are linked to the central joint processor via lossless links with finite capacity. The cellular network is modeled by the circular Wyner model, which yields closed form expressions for the achievable rates. For this idealistic model, we present achievable rates for cell-sites that use compress-and forward scheme, combined with local decoding, and inter-cell time-sharing. These rates are then demonstrated to be rather close to the optimal unlimited backhaul joint processing rates, already for modest backhaul capacities, supporting the potential gain offered by the joint cell-site processing approach.

LDPC coded MIMO multiple access with iterative joint decoding

An efficient scheme for the multiple-access multiple-input multiple-output (MIMO) channel is proposed, which operates well also in the single user regime, as well as in a direct-sequence spread-spectrum (DS-CDMA) setting. The design features scalability and is of limited complexity. The system employs optimized low-density parity-check (LDPC) codes and an efficient iterative (belief propagation-BP) detection which combines linear minimum mean-square error (LMMSE) detection and iterative interference cancellation (IC). This combination is found to be necessary for efficient operation in high system loads /spl alpha/>1. An asymptotic density evolution (DE) is used to optimize the degree polynomials of the underlining LDPC code, and thresholds as close as 0.77 dB to the channel capacity are evident for a system load of 2. Replacing the LMMSE with the complex individually optimal multiuser detector (IO-MUD) further improves the performance up to 0.14 dB from the capacity. Comparing the thresholds of a good single-user LDPC code to the multiuser optimized LDPC code, both over the above multiuser channel, reveals a surprising 8-dB difference, emphasizing thus the necessity of optimizing the code. The asymptotic analysis of the proposed scheme is verified by simulations of finite systems, which reveal meaningful differences between the performances of MIMO systems with single and multiple users and demonstrate performance similar to previously reported techniques, but with higher system loads, and significantly lower receiver complexity.

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).

Cooperative Wireless Cellular Systems: An Information-Theoretic View

In this monograph, the impact of cooperation on the performance of wireless cellular systems is studied from an information-theoretic standpoint, focusing on simple formulations typically referred to as Wynertype models. Following ongoing research and standardization efforts, the text covers two main classes of cooperation strategies. The first class is cooperation at the base station (BS) level, which is also known as Multi-Cell Processing (MCP), network Multiple-Input MultipleOutput (MIMO), or Coordinated Multi-Point transmission/reception (CoMP). With MCP, cooperative decoding, for the uplink, or encoding, for the downlink, is enabled at the BSs. MCP is made possible by the presence of an architecture of, typically wired, backhaul links connecting individual BSs to a central processor (CP) or to one another. The second class of cooperative strategies allows cooperation in the form of relaying for conveying data between Mobile Stations (MSs) and BSs in either the uplink or the downlink. Relaying can be enabled by two possible architectures. A first option is to deploy dedicated Relay Stations (RSs) that are tasked with forwarding uplink or downlink traffic. The second option is for the MSs to act as RSs for other MSs. MCP is first studied under ideal conditions on the backhaul links, namely by assuming that all BSs are connected to a CP with unlimitedcapacity links. Both Gaussian (nonfading) and flat-fading channels are analyzed, for the uplink and the downlink, and analytical insights are drawn into the performance advantages of MCP in different relevant operating regimes. Performance comparison is performed with standard Single-Cell Processing (SCP) techniques, whereby each BS decodes, in the uplink, or encodes, in the downlink, independently, as implemented with different spatial reuse factors. Then, practical constraints on the backhaul architecture enabling MCP are introduced. Specifically, three common settings are studied. In the first, all the BSs are connected to a CP via finite-capacity links. In the second, only BSs in adjacent cells are connected via (finite-capacity) backhaul links. In the third, only a subset of BSs is connected to a CP for joint encoding/decoding (clustered cooperation). Achievable rates for the three settings are studied and compared for both the uplink and the downlink. The performance advantages of relaying are analyzed for cellular systems with dedicated RSs and with cooperative MSs. Different techniques are reviewed that require varying degrees of information about system parameters at the MSs, RSs, and BSs. Performance is investigated with both MCP and SCP, revealing a profound interplay between cooperation at the BS level and relaying. Finally, various open problems are pointed out.

Structured superposition for backhaul constrained cellular uplink

In this paper, we demonstrate the advantage of the inherent algebraic structure of lattice codes, for the uplink channel of a cellular deployment. The out-of-cell interference is assumed to be symmetric, as in Wyners model. We employ a new relaying technique, compute-and-forward, which allows cell-sites to decode equations of the transmitted bits by exploiting the channel interference. However, the standard compute-and-forward technique is penalized whenever the channel coefficients are non-integer. We develop a superposition strategy to mitigate this penalty. By using part of the power towards a private message, we can effectively modify the channel seen by compute-and-forward. We demonstrate that, in certain regimes, this mixed strategy significantly outperforms decode-and-forward, compress-and-forward, and ordinary compute-and-forward.

Broadcast Cooperation Strategies for Two Colocated Users

This work considers the problem of communication between a remote single transmitter and a destined user, with helping colocated users, over an independent block Rayleigh-fading channel. The colocation nature of the users allows cooperation, which increases the overall achievable rate, from transmitter to destination. The transmitter is ignorant of the fading coefficients, while receivers have access to perfect channel state information (CSI). We propose, for this setting, a multilayer broadcast transmission approach. The broadcast approach enables enhanced cooperation between the colocated users. That is due to the nature of broadcasting, where the better the channel quality, the more layers that can reliably be decoded. The cooperation between the users is performed over additive white Gaussian noise (AWGN) channels, with a relaying power constraint, and unlimited bandwidth. Three commonly used cooperation techniques are studied: amplify-and-forward (AF), compress-and-forward (CF), and decode-and-forward (DF). These techniques are extended by using the broadcast approach for the case of relaxed decoding delay constraint. For this case, a separate processing of the layers, which includes multisession cooperation is shown to be beneficial. Further, closed-form expressions for infinitely many AF sessions and recursive expressions for the more complex CF are given. Numerical results for the various cooperation strategies demonstrate how the multisession cooperation outperforms conventional relaying techniques.

On extrinsic information of good binary codes operating over Gaussian channels

We show that the extrinsic information about the coded bits of any good (capacity achieving) binary code operating over a Gaussian channel is zero when the channel capacity is lower than the code rate and unity when capacity exceeds the code rate, that is, the extrinsic information transfer (EXIT) chart is a step function of the signal to noise ratio and independent of the code. It follows that, for a common class of iterative receivers where the error correcting decoder must operate at first iteration at rate above capacity (such as in turbo equalization, iterative channel estimation, parallel and serial concatenated coding and the like), classical good codes which achieve capacity over the Additive White Gaussian Noise Channel are not effective and should be replaced by different new ones. Copyright

Information-theoretic implications of constrained cooperation in simple cellular models

Recent information theoretic results on cooperation in cellular systems are reviewed, addressing both multicell processing (cooperation among base stations) and relaying (cooperation at the user level). Two central issues are addressed, namely, first multicell processing is studied with either limited-capacity backhaul links to a central processor or only local (and finite-capacity) cooperation among neighboring cells. The role of codebook information, decoding delay and network planning (frequency reuse) are specifically highlighted along with the impact of different transmission/ reception strategies. Next, multicell processing is considered in the presence of cooperation at the user level, focusing on both out-of-band relaying via conferencing users and in-band relaying by means of dedicated relays. Non-fading and fading uplink and downlink channels adhering to simple Wyner-type, cellular system models are targeted.