Cooperative Communications for Improved Wireless Network Transmission: Framework for Virtual Antenna Array Applications | Date: 28 April 2011, 06:48
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Cooperative Communications for Improved Wireless Network Transmission: Framework for Virtual Antenna Array Applications (Premier Reference Source)
By Murat Uysal
* Publisher: Information Science Reference
* Number Of Pages: 632
* Publication Date: 2009-07-31
* ISBN-10 / ASIN: 1605666653
* ISBN-13 / EAN: 9781605666655
Product Description:
Cooperative communications, an emerging research area spurring tremendous excitement within academia and industry, has experienced an increase in demands for wireless multimedia and interactive services in recent years.
Cooperative Communications for Improved Wireless Network Transmission: Framework for Virtual Antenna Array Applications provides practitioners, researchers, and academicians with fundamental principles of cooperative communication, presenting the latest advances in this rapidly evolving field. Containing research from leading international experts, this Premier Reference Source offers readers diverse findings and exposes underlying issues in the analysis, design, and optimization of wireless systems.
Table of Contents:
Section I: Information Theoretical Results on Cooperative Communications
Chapter I: Information Theoretical Limits on Cooperative Communications
This chapter provides an overview of the information theoretic foundations of cooperative communications. Earlier information theoretic achievements as well as the more recent developments are discussed. The analysis accounts for full/half-duplex nodes, and for multiple relays. Various channel models such as discrete memory less, additive white Gaussian noise (AWGN) and fading channels are considered. Cooperative communication protocols are investigated using capacity, diversity and diversity-multiplexing tradeoff (DMT) as performance metrics. Overall, this chapter provides a comprehensive view on the foundations of, and the state-of-the-art reached in the theory of cooperative communications.
Chapter II: Overview of Amplify-and-Forward Relaying
Amplify-and-Forward (AF) is a simple cooperative strategy for ad-hoc networks with critical power constraints. It involves an amplification of the received signal in the analogue domain at the relays without further signal processing. This chapter gives an overview of the basic AF protocols in the literature and discusses recent research contributions in this area. Based on some well-defined AF-based cooperative configurations, it focuses on the behaviour of AF in block-fading channels, in power allocation problems, in relay selection and in cross-layer coordination. Mathematical models and outage probability simulations are used in order to show the enhancements of the presented AF techniques.
Chapter III: Power Allocation for Cooperative Communications
In this chapter, we review the optimal power allocation policies for fading channels, in single user and multiple access scenarios. We present some background on cooperative communications, starting with the relay channel, and moving onto mutually cooperative systems. Then, we consider power control and user cooperation jointly, and for a fading Gaussian multiple access channel (MAC) with user cooperation, we present a channel adaptive encoding policy which relies on block Markov superposition coding. We obtain the power allocation policies that maximize the average rates achievable by this policy, subject to average power constraints. The optimal policies result in a coding scheme that is simpler than the one for a general multiple access channel with generalized feedback. This simpler coding scheme also leads to the possibility of formulating an otherwise non-concave optimization problem as a concave one. Using the perfect channel state information (CSI) available at the transmitters to adapt the powers, we demonstrate gains over the achievable rates for existing cooperative systems. We consider both backwards and window decoding, and show that, window decoding, which incurs less decoding delay, achieves the same sum rate as backwards decoding, when the powers are optimized.
Chapter IV: Capacity Limits of Base Station Cooperation in Cellular Networks
In the information-theoretic literature, it has been widely shown that multicell processing is able to provide high capacity gains in the context of cellular systems. What is more, it has been proved that the per-cell sum-rate capacity of multicell processing systems grows linearly with the number of Base Station (BS) receive antennas. However, the majority of results in this area has been produced assuming that the fading coefficients of the MIMO subchannels are completely uncorrelated. In this direction, this chapter investigates the ergodic per-cell sum-rate capacity of the Gaussian MIMO Cellular Channel under correlated fading and BS cooperation (multicell processing). More specifically, the current channel model considers Rayleigh fading, uniformly distributed User Terminals (UTs) over a planar cellular system and power-law path loss. Furthermore, both BSs and Uts are equipped with correlated multiple antennas, which are modelled according to the Kronecker product correlation model. The per-cell sum-rate capacity is evaluated while varying the cell density of the system, as well as the level of receive and transmit correlation. In this context, it is shown that the capacity performance is compromised by correlation at the BS-side, whereas correlation at the UT-side has a negligible effect on the system’s capacity.
Section II: Practical Coding Schemes for Cooperative Communications
Chapter V: Source and Channel Coding Techniques for Cooperative Communications
This chapter provides a survey of practical cooperative coding schemes currently available in the literature, with focus on those schemes that achieve performance close to capacity or the best known achievable rates. To provide an insight into the construction of practical coding schemes for various cooperative communication scenarios, we first summarize the main design principles and tools that are used. We then present a survey of cooperative communication scenarios, and the progress on practical coding schemes for each of these scenarios is discussed in detail. Throughout the chapter, we demonstrate how the common design principles and tools are exploited to construct the existing practical coding schemes. We hope that the integrated view presented in this chapter can lead to further advances in this area.
Chapter VI: Network Coding for Multi-Hop Wireless Networks
We consider practical network coding, a useful generalization of routing, in multi-hop multicast wireless networks. The model of interest comprises a set of nodes transmitting data wirelessly to a set of destinations across an arbitrary, unreliable and possibly time-varying network. This model is general and subsumes peer-to-peer, ad-hoc, sensory and mobile networks. It is first shown that, in the single-hop case, the idea of adaptively matching code-on-graph with network-on-graph, first developed in the adaptive-network-coded-cooperation (ANCC) protocol, provides a significant improvement over the conventional strategies. To generalize the idea to the multi-hop context, we propose to transform an arbitrarily connected network to a possibly time-varying “trellis network”, such that routing design for the network becomes equivalent to path discovery in the trellis. Then, exploiting the distributed, real-time graph-matching technique in each stage of the trellis, a general network coding framework is developed. Depending on whether or not the intermediate relays choose to decode network codes, three practical network coding categories, progress network coding, concatenated network coding and hybrid network coding, are investigated. Analysis shows that the proposed framework can be as dissemination-efficient as those with random codes, but only more practical.
Section III: Distributed
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