Cooperative Communication System Architectures for Cellular Networks

An ever-growing demand for higher data-rates has facilitated the growth of wireless networks in the past decades. These networks, however, are known to exhibit capacity and coverage problems, hence jeopardizing the promised quality of service towards the end-user. To overcome these problems, prohibitive investment costs in terms of base station or access point rollouts would be required if traditional, non-scalable, cell-splitting, and micro-cell capacity dimension procedures were applied. The prime aim of current R&D initiatives is, hence, to develop innovative network solutions that decrease the cost per bit/s/Hz over the wireless link. To this end, cooperative networks have emerged as an efficient and promising solution. We discuss in this chapter some key research and deployment issues, with emphasis on cooperative architectures, networking, and security solutions. We expose some motivations to use such networks, as well as latest state-of-the-art developments, open research challenges, and business models.

Resource Allocation for a Cooperative Broadband MIMO-OFDM System

In this chapter, a cooperative broadband relay-based resource allocation technique is proposed for adaptive bit and power loading multiple-input-multiple-output/orthogonal frequency division multiplexing (MIMO-OFDM) system. In this technique, sub-channels allocation, M-QAM modulation order, and power distribution among different sub-channels in the relay-based MIMO-OFDM system are jointly optimized according to the channel state information (CSI) of the relay and the direct link. The transmitted stream of bits is divided into two parts according to a suggested cooperative protocol that is based on sub-channel-division. In this protocol, the first part is sent directly from the source to the destination, and the second part is relayed to the destination through an indirect link. Such a cooperative relay-based system enables us to exploit the inherent system diversities in frequency, space and time to maximize the system power efficiency. The BER performance using this cooperative sub-channel-division protocol with adaptive sub-channel assignment and adaptive bit/power loading are presented and compared with a noncooperative ones. The use of cooperation in a broadband relay-based MIMO-OFDM system showed high performance improvement in terms of BER.

Single and Double-Differential Coding in Cooperative Communications

In this chapter, we discuss single and double-differential coding for a two-user cooperative communication system. The single-differential coding is important for the cooperative systems as the data at the destination/relaying node can be decoded without knowing the channel gains. The double-differential modulation is useful as it avoids the need of estimating the channel and carrier offsets for the decoding of the data. We explain single-differential coding for a cooperative system with one relay utilizing orthogonal transmissions with respect to the source. Next, we explain two single-differential relaying strategies: active user strategy (AUS) and passive users relaying strategy (PURS), which could be used by the base-station to transmit data of two users over downlink channels in the two-user cooperative communication network with decode-and-forward protocol. The AUS and PURS follow an improved time schedule in order to increase the data rate. A probability of error based approach is also discussed, which can be used to reduce the erroneous relaying of data by the regenerative relay. In addition, we also discuss how to implement double-differential (DD) modulation for decode-and-forward and amplify-and-forward based cooperative communication system with single source-destination pair and a single relay. The DD based systems work very well in the presence of random carrier offsets without any channel and carrier offset knowledge at the receivers, where the single differential cooperative scheme breaks down. It is further shown that optimized power distributions can be used to improve the performance of the DD system.

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 singlehop 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.

Applications of Majorization Theory in Space-Time Cooperative Communications

This chapter discusses important aspects in cooperative communications such as power allocation and node distributions using majorization theory, spanning both theoretical foundations and practical issues. Majorization theory provides a large amount of tools and techniques which can be used in order to accelerate the pace of developments in this fascinating research area of cooperative communications. The aim of the chapter is to build good intuition and insight into this important field of cooperative communications and how majorization theory can be used in order to solve quite complex problems in a very efficient and elegant way. Although we focus on some specific applications, the tools can be also applied to other setups and processing techniques.

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 provide 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 block Markov coding, 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 significant 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.

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 node, and for multiple relays. Various channel models such as discrete memoryless, 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.

Single-Carrier Frequency Domain Equalization for Broadband Cooperative Communications

Cooperative diversity is an effective technique to combat the fading phenomena in wireless communications without additional complexity of multiple antennas. Multiple terminals in the network form a virtual antenna array in a distributed fashion. Even though each of them is equipped with only one antenna, spatial diversity gain can be achieved through cooperation. In this chapter, we discuss relay-assisted single carrier transmissions extending conventional transmit diversity schemes. We focus on distributed space-frequency block coded single carrier transmission, in order to operate over fast fading channels. A pilot design technique is also discussed for channel estimation of this single carrier cooperative system, which shows better channel tracking performance than conventional block-type channel estimations. In addition, spectral efficient cooperative diversity protocols are presented, where the users access a relay simultaneously or transmit superposed data blocks. Interference from the other user is effectively removed by using an iterative detection technique.

Diversity Combining for Cooperative Communications

A major advantage of cooperative communications is the potential for forming distributed antenna arrays, that is arrays whose elements are not collocated, but carried by independent relaying terminals. This allows for a study and design of cooperative communications under a novel perspective, where the inherent end-to-end paths between the source and destination terminal constitute the multiple branches of a virtual, distributed diversity receiver. As a result, the well-known combining methods used in conventional diversity receivers can be implemented in a distributed fashion, resulting in novel relaying protocols and, generally, in new ways for exploiting the resources available in cooperative relaying setups. This chapter provides an overview of this distributed diversity concept, as well as a performance analysis of the corresponding distributed diversity schemes, with particular emphasis on the analysis of distributed switch-and-stay combining. Further insights regarding the potential of implementing the distributed diversity concept in practical applications are obtained.

Energy Efficient Communication with Random Node Cooperation

In this chapter, we focus on the energy efficient cooperative communication with random node cooperation for wireless networks. By “random,” we mean that the cooperative nodes for each communication event are randomly selected based on the network and channel conditions. Different from the conventional deterministic cooperative communication where cooperative nodes are determined prior to the communication, here the number of cooperative nodes and the cooperation pattern may be random, which is more practical given the random nature of the channels among the source nodes, relay nodes, and destination nodes. In addition, it is more robust to the dynamic wireless network environment. Starting with a thorough literature survey, we then discuss the challenges for random cooperative communication systems. Afterwards, two examples are presented to illustrate the design methodologies. In the first example, we analyze a simple scheme for clustered wireless networks, where cooperative communication is deployed in the long-haul inter-cluster transmissions to improve the energy efficiency. We quantify the energy performance and emphasize its difference from the conventional deterministic ones. In the second example, we consider the cross-layer design between the physical layer and the medium access control (MAC) layer for the one-hop random single-relay networks. We unify the power control and the relay selection at the physical layer into the MAC signaling in a distributed fashion. This example clearly shows the strength of cross-layer design for energy-efficient cooperative systems with random node collaboration. Finally, we conclude with discussions over possible future research directions.