Cooperative strategies design based on the diversity and multiplexing tradeoff

This thesis focuses on designing wireless cooperative communication strategies that are either optimal or near-optimal in terms of the tradeoff between diversity and multiplexing gains. Starting from classical cooperative broadcast, multiple-access and relay channels with unit degree of freedom, to more general cooperative interference channels with higher degrees of freedom, properties of different network topologies are studied and their unique characteristics together with several advanced interference management techniques are exploited to design cooperative transmission strategies in order to enhance data rate, reliability or both at the same time. Moreover, various algorithms are proposed to solve practical implementation issues and performance is analyzed through both theoretical verifications and simulations

Capacity Region and Degrees of Freedom of Bidirectional Networks

The increasing complexity of communication networks in size and density provides us enormous opportunities to exploit interaction among multiple nodes, thus enabling higher rate of data streams. On the flip side, however, this complexity comes with challenges in managing interference that multiple source-destination pairs in the network may cause to each other. In this dissertation, we make progress on how to exploit the opportunities, as well as how to overcome the challenges for various communication networks. In the first part, we focus on developing fundamental principles for communication network design, especially networks with multiple antenna transceivers, with an emphasis on (1) understanding the role of feedback and cooperation, and (2) developing interference management methods. In this part, we find that feedback and cooperation have promising roles in improving the capacity performance of several interference networks. We show that in stark contrast to the point-to-point case, a limited feedback can improve the capacity of interference-limited networks. In fact, the improvement can be unbounded. This result shows that feedback can have a potentially significant role to play in mitigating interference. Then, in part two we study several bidirectional networks. We study the bidirectional diamond network and show that for deterministic and some Gaussian models the capacity is doubled for full-duplex channel in comparison with one-way networks. In addition, we study the degrees of freedom of two-way four-unicast MIMO networks, and provide upper and lower bounds that are tight in several cases. We also study the impact of caching in relay nodes for these models. We find a number of cases that bidirectional links can double the degrees of freedom with the help of relay caching and/or multiple relay antennas

Compute-and-Forward: Harnessing Interference through Structured Codes

Interference is usually viewed as an obstacle to communication in wireless networks. This paper proposes a new strategy, compute-and-forward, that exploits interference to obtain significantly higher rates between users in a network. The key idea is that relays should decode linear functions of transmitted messages according to their observed channel coefficients rather than ignoring the interference as noise. After decoding these linear equations, the relays simply send them towards the destinations, which given enough equations, can recover their desired messages. The underlying codes are based on nested lattices whose algebraic structure ensures that integer combinations of codewords can be decoded reliably. Encoders map messages from a finite field to a lattice and decoders recover equations of lattice points which are then mapped back to equations over the finite field. This scheme is applicable even if the transmitters lack channel state information.Comment: IEEE Trans. Info Theory, to appear. 23 pages, 13 figure

Network Coding for Wireless and Wired Networks: Design, Performance and Achievable Rates

Many point-to-point communication problems are relatively well understood in the literature. For example, in addition to knowing what the capacity of a point-to-point channel is, we also know how to construct codes that will come arbitrarily close to the capacity of these channels. However, we know very little about networks. For example, we do not know the capacity of the two-way relay channel which consists of only three transmitters. The situation is not so different in the wired networks except special cases like multicasting. To understand networks better, in this thesis we study network coding which is considered to be a promising technique since the time it was shown to achieve the single-source multicast capacity. First we design and analyze deterministic and random network coding schemes for a cooperative communication setup with multiple sources and destinations. We show that our schemes outperform conventional cooperation in terms of the diversity-multiplexing tradeoff (DMT). Specifically, it can offer the maximum diversity order at the expense of a slightly reduced multiplexing rate. We derive the necessary and sufficient conditions to achieve the maximum diversity order. We show that when the parity-check matrix for a systematic maximum distance separable (MDS) code is used as the network coding matrix, the maximum diversity is achieved. We present two ways to generate full-diversity network coding matrices: namely using the Cauchy matrices and the Vandermonde matrices. We also analyze a selection relaying scheme and prove that a multiplicative diversity order is possible with enough number of relay selection rounds. In addition to the above scheme for wireless networks, we also study wired networks, and apply network coding together with interference alignment. We consider networks with $K$ source nodes and $J$ destination nodes with arbitrary message demands. We first consider a simple network consisting of three source nodes and four destination nodes and show that each user can achieve a rate of one half. Then we extend the result for the general case which states that when the min-cut between each source-destination pair is one, it is possible to achieve a sum rate that is arbitrarily close to the min-cut between the source nodes whose messages are demanded and the destination node where the sum rate is the summation of all the demanded source message rates plus the biggest interferer\u27s rate