Feedback And Interference Alignment In Networks

The increasing complexity of communication networks in size and density provides us enormous opportunities to exploit interaction among multiple nodes, thus enabling higher date 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 we exploit the opportunities, as well as how we overcome the challenges. In the first part, we find that feedback - one of the common ways to enable interaction in networks - has a promising role in improving the capacity performance of networks. Earlier results on feedback capacity were somewhat discouraging. This is mainly due to Shannon's original result on feedback capacity where he showed that in point-to-point communication, feedback does not increase capacity. Hence, traditionally it is believed that feedback has had little impact on increasing capacity of communication links. Therefore, the use of feedback has been limited to improving the reliability of communications, usually in the form of ARQ. In this dissertation, we show that in stark contrast to the point-to-point case, feedback can improve the capacity of interference-limited network. In fact, the improvement can be unbounded. This result shows that feedback can have a potentially significant role to play in mitigating interference. Also in the process of deriving this conclusion, we characterize the feedback capacity of the two-user Gaussian interference channel to within 2 bits, one of the longstanding open problems in network information theory. In the second part, we propose a new interference management technique for widely deployed cellular networks. Inspired by a recent breakthrough, the concept of interference alignment, we develop an interference alignment technique for cellular networks. Our technique promises almost interference-free communication with the increase of the number of clients in cellular networks. It shows substantial gain (around 30% to 60%) as compared to one of the interference management techniques in current cellular systems. In addition, it comes with implementation benefits: it can actually be implemented with small changes to emerging 4G cellular standards and architectures at the base-stations and clients. In particular, the required signal-processing circuitry, software control, and channel-state feedback mechanisms are extensions of existing implementations and standards. Lastly, we extend the interference alignment principle, developed in the context of wireless networks, into other fields of network research such as storage networks. In an effort to protect information against node failures, storage networks employ coding techniques, such as maximum distance separable (MDS) erasure codes, known as optimal codes in reliability with respect to redundancy. However, these MDS codes come with prohibitive maintenance cost when it comes to repairing failed storage nodes. While only partial information stored in the failed node needs to be recovered, the conventional MDS codes focus on the complete data recovery (including unwanted data, corresponding to interference) by downloading too much information from survivor storage encoded nodes, thus causing the high repair cost. Building on the connection between wireless and wireline networks, we leverage the interference alignment principle to develop a new class of MDS codes that significantly reduces the repair cost over the conventional MDS codes and also achieves information-theoretic optimal bound on the repair cost for all admissible code parameters.

Interference Alignment: A New Look at Signal Dimensions in a Communication Network provides both a tutorial and a survey of the state-of-art on the topic.

Wireless networks are increasingly interference-limited, which motivates the development of sophisticated interference management techniques. One recently discovered approach is interference alignment, which attains the maximum sum rate scaling (with signal-to-noise ratio) in many network configurations. Interference alignment is not yet well understood from an engineering perspective. Such design considerations include (i) partial rather than complete knowledge of channel state information, (ii) correlated channels, (iii) bursty packet-based network traffic that requires the frequent setup and tear down of sessions, and (iv) the spatial distribution and interaction of transmit/receive pairs. This dissertation aims to establish the benefits and limitations of interference alignment under these four considerations. The first contribution of this dissertation considers an isolated group of transmit/receiver pairs (a cluster) cooperating through interference alignment and derives the signal-to-interference-plus-noise ratio distribution at each receiver for each stream. This distribution is used to compare interference alignment to beamforming and spatial multiplexing (as examples of common transmission techniques) in terms of sum rate to identify potential switching points between them. This dissertation identifies such switching points and provides design recommendations based on severity of the correlation or the channel state information uncertainty. The second contribution considers transmitters that are not associated with any interference alignment cooperating group but want to use the channel. The goal is to retain the benefits of interference alignment amid interference from the out-of-cluster transmitters. This dissertation shows that when the out-of-cluster transmitters have enough antennas, they can access the channel without changing the performance of the interference alignment receivers. Furthermore, optimum transmit filters maximizing the sum rate of the out-of-cluster transmit/receive pairs are derived. When insufficient antennas exist at the out-of-cluster transmitters, several transmit filters that trade off complexity and sum rate performance are presented. The last contribution, in contrast to the first two, takes into account the impact of large scale fading and the spatial distribution of the transmit/receive pairs on interference alignment by deriving the transmission capacity in a decentralized clustered interference alignment network. Channel state information uncertainty and feedback overhead are considered and the optimum training period is derived. Transmission capacity of interference alignment is compared to spatial multiplexing to highlight the tradeoff between channel estimation accuracy and the inter-cluster interference; the closer the nodes to each other, the higher the channel estimation accuracy and the inter-cluster interference.

This book explores the different strategies regarding limited feedback information. The book analyzes the impact of quantization and the delay of CSI on the performance. The author shows the effect of the reduced feedback information and gives an overview about the feedback strategies in the standards. This volume presents theoretical analysis as well as practical algorithms for the required feedback information at the base stations to perform adaptive resource algorithms efficiently and mitigate interference coming from other cells.

Wireless systems in which multiple users simultaneously access the propagation medium suffer from co-channel interference. Untreated interference limits the total amount of data that can be communicated reliably across the wireless links. If interfering users allocate a portion of the system's resources for information exchange and coordination, the effect of interference can be mitigated. Interference alignment (IA) is an example of a cooperative signaling strategy that alleviates the problem of co-channel interference and promises large gains in spectral efficiency. To enable alignment in practical wireless systems, channel state information (CSI) must be shared both efficiently and accurately. In this dissertation, I develop low-overhead CSI feedback strategies that help networks realize the information-theoretic performance of IA and facilitate its adoption in practical systems. The developed strategies leverage the concepts of analog, digital, and differential feedback to provide IA networks with significantly more accurate and affordable CSI when compared to existing solutions. In my first contribution, I develop an analog feedback strategy to enable IA in multiple antenna systems; multiple antennas are one of IA's key enabling technologies and perhaps the most promising IA use case. In my second contribution, I leverage temporal correlation to improve CSI quantization in limited feedback single-antenna systems. The Grassmannian differential strategy developed provides several orders of magnitude in CSI compression and ensures almost-perfect IA performance in various fading scenarios. In my final contribution, I complete my practical treatment of IA by revisiting its performance when CSI acquisition overhead is explicitly accounted for. This last contribution settles the viability of IA, from a CSI acquisition perspective, and demonstrates the utility of the proposed feedback strategies in transitioning interference alignment from theory to practice.

Cognitive Radio Communications and Networks gives comprehensive and balanced coverage of the principles of cognitive radio communications, cognitive networks, and details of their implementation, including the latest developments in the standards and spectrum policy. Case studies, end-of-chapter questions, and descriptions of various platforms and test beds, together with sample code, give hands-on knowledge of how cognitive radio systems can be implemented in practice. Extensive treatment is given to several standards, including IEEE 802.22 for TV White Spaces and IEEE SCC41 Written by leading people in the field, both at universities and major industrial research laboratories, this tutorial text gives communications engineers, R&D engineers, researchers, undergraduate and post graduate students a complete reference on the application of wireless communications and network theory for the design and implementation of cognitive radio systems and networks Each chapter is written by internationally renowned experts, giving complete and balanced treatment of the fundamentals of both cognitive radio communications and cognitive networks, together with implementation details Extensive treatment of the latest standards and spectrum policy developments enables the development of compliant cognitive systems Strong practical orientation – through case studies and descriptions of cognitive radio platforms and testbeds – shows how real world cognitive radio systems and network architectures have been built Alexander M. Wyglinski is an Assistant Professor of Electrical and Computer Engineering at Worcester Polytechnic Institute (WPI), Director of the WPI Limerick Project Center, and Director of the Wireless Innovation Laboratory (WI Lab) Each chapter is written by internationally renowned experts, giving complete and balanced treatment of the fundamentals of both cognitive radio communications and cognitive networks, together with implementation details Extensive treatment of the latest standards and spectrum policy developments enables the development of compliant cognitive systems Strong practical orientation – through case studies and descriptions of cognitive radio platforms and testbeds – shows how "real world" cognitive radio systems and network architectures have been built

In this thesis, we study the stream selection based interference alignment (IA) algorithms, which can provide large multiplexing gain, to deal with the interference in the heterogeneous networks. Firstly, different deployment scenarios for the pico cells are investigated assuming perfect channel state information (CSI) at the transmitters.Two different stream selection IA algorithms are proposed for fully and partially connected interference networks and selecting at least one stream is guaranteed for each user. A stream sequence is selected among a predetermined set of sequences that mostly contribute to the sum-rate while performing an exhaustive search. In the proposed algorithms, the complexity of the exhaustive search is significantly decreased while keeping the performance relatively close. After selecting a stream, the interference generated between the selected and the unselected streams is aligned by orthogonal projections. Then, the influence of the imperfect CSI on the proposed algorithms is analyzed and it is observed that the intra-stream interference causes a significant degradation in the performance due to the quantization error. Therefore, we propose an algorithm for the limited feedback scheme. Finally, adaptive bit allocation schemes are presented to maximize the overall capacity for all the proposed algorithms. The performance evaluations are carried out considering different scenarios with different number and placements of pico cells. It is shown that the proposed algorithm for the limited feedback is more robust to channel imperfections compared to the existing IA algorithms.

The emergence of very capable mobile terminals, e.g. smartphones or tablets, has dramatically increased the demand of wireless data traffic in recent years. Current growth forecasts elucidate that wireless communication standards will not be able to afford future traffic demands, thus many research efforts have been oriented towards increasing the efficiency of wireless networks. MIMO technologies, entailing the use of multiple antennas, stand as one of the candidates. This solution allows increasing not only the reliability and robustness (diversity gain), but also the efficiency of the communication (multiplexing gain or degrees of freedom (DoF)). The DoF describe the slope of channel capacity at very high signal-to-noise-ratio (SNR) regime, and for the point-to-point (P2P) channel are equal to the minimum between the number of antennas at the transmitter and the receiver. Consequently, the throughput may be scaled in a promising way. However, the DoF behavior in case of having interference is still an open problem in general. This thesis studies the DoF of interference networks. The most trivial way of tackling this problem is by means of orthogonalization, either in time, frequency or space. However, it does not allow that the scaling of DoF with the number of users. For example, if transmissions are orthogonalized in time each user is served only a fraction of time inversely proportional to the number of users. Likewise, if transmissions are orthogonalized in space, transmitters must be equipped with a large number of antennas, which is costly and not practical. For dimensionally-limited systems, the interference alignment (IA) principle proposes that instead of forcing the design to null the interference terms at the receivers, make the receiver observe them overlapped. This way the number of dimensions occupied by interference is reduced, thus allowing the allocation of more desired signals, thus symbols per user, and also relaxing the constraint on the number of required antennas. Following IA allows that "each user achieves half the cake independently of the number of users", where the cake represents the DoF of the P2P channel. At first, full channel state information was assumed to be available at the transmitter side (full CSIT), i.e. the information is acquired instantaneously, and with perfect quality. The first part of this thesis studies this case and completes the DoF characterization of the 3-user MIMO interference channel for some antenna configurations when channel coefficients are assumed constant. In practice, CSIT should be obtained from channel feedback, thus incurring delays and errors. In this context, and especially intended to scenarios with high mobility, IA concepts were extended to networks where only outdated information of the channels is available, a framework known as delayed CSIT where the channel feedback delay may be larger than the channel coherence time. This form of IA is denoted as retrospective interference alignment, since the transmission is carried out in multiple phases, and signals may be aligned along space and the different phases. The second part of the thesis deepens into the DoF of two network topologies with delayed CSIT, for which linear precoding strategies are proposed. Moreover, it is shown that the proposed strategies are better than state-of-the-art in terms of DoF-delay trade-off, which is relevant as most strategies based on delayed CSIT entail long communication delays. The concluding part of the thesis analyses how one of schemes proposed in the second part performs in terms of DoF with delayed CSIT with errors, and net DoF. This last metric describes the DoF as a function of the coherence time, and taking into account all issues related to channel acquisition at both the transmitter and receiver side: consumption of resources for channel training, for feedback transmission, and feedback waits.