Achievable Rates and Resource Allocation Strategies for Imperfectly Known Fading Relay Channels

Achievable rates and resource allocation strategies for imperfectly known fading relay channels are studied. It is assumed that communication starts with the network training phase in which the receivers estimate the fading coefficients. Achievable rate expressions for amplify-and-forward and decode-and-forward relaying schemes with different degrees of cooperation are obtained. We identify efficient strategies in three resource allocation problems: (1) power allocation between data and training symbols, (2) time/bandwidth allocation to the relay, and (3) power allocation between the source and relay in the presence of total power constraints. It is noted that unless the source-relay channel quality is high, cooperation is not beneficial and noncooperative direct transmission should be preferred at high signal-to-noise ratio (SNR) values when amplify-and-forward or decode-and-forward with repetition coding is employed as the cooperation strategy. On the other hand, relaying is shown to generally improve the performance at low SNRs. Additionally, transmission schemes in which the relay and source transmit in nonoverlapping intervals are seen to perform better in the low-SNR regime. Finally, it is noted that care should be exercised when operating at very low SNR levels, as energy efficiency significantly degrades below a certain SNR threshold value

Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

A Trust-Based Relay Selection Approach to the Multi-Hop Network Formation Problem in Cognitive Radio Networks

One of the major challenges for today’s wireless communications is to meet the growing demand for supporting an increasing diversity of wireless applications with limited spectrum resource. In cooperative communications and networking, users share resources and collaborate in a distributed approach, similar to entities of active social groups in self organizational communities. Users’ information may be shared by the user and also by the cooperative users, in distributed transmission. Cooperative communications and networking is a fairly new communication paradigm that promises significant capacity and multiplexing gain increase in wireless networks. This research will provide a cooperative relay selection framework that exploits the similarity of cognitive radio networks to social networks. It offers a multi-hop, reputation-based power control game for routing. In this dissertation, a social network model provides a humanistic approach to predicting relay selection and network analysis in cognitive radio networks

Mathematical optimization and game theoretic methods for radar networks

Radar systems are undoubtedly included in the hall of the most momentous discoveries of the previous century. Although radars were initially used for ship and aircraft detection, nowadays these systems are used in highly diverse fields, expanding from civil aviation, marine navigation and air-defence to ocean surveillance, meteorology and medicine. Recent advances in signal processing and the constant development of computational capabilities led to radar systems with impressive surveillance and tracking characteristics but on the other hand the continuous growth of distributed networks made them susceptible to multisource interference. This thesis aims at addressing vulnerabilities of modern radar networks and further improving their characteristics through the design of signal processing algorithms and by utilizing convex optimization and game theoretic methods. In particular, the problems of beamforming, power allocation, jammer avoidance and uncertainty within the context of multiple-input multiple-output (MIMO) radar networks are addressed. In order to improve the beamforming performance of phased-array and MIMO radars employing two-dimensional arrays of antennas, a hybrid two-dimensional Phased-MIMO radar with fully overlapped subarrays is proposed. The work considers both adaptive (convex optimization, CAPON beamformer) and non-adaptive (conventional) beamforming techniques. The transmit, receive and overall beampatterns of the Phased-MIMO model are compared with the respective beampatterns of the phased-array and the MIMO schemes, proving that the hybrid model provides superior capabilities in beamforming. By incorporating game theoretic techniques in the radar field, various vulnerabilities and problems can be investigated. Hence, a game theoretic power allocation scheme is proposed and a Nash equilibrium analysis for a multistatic MIMO network is performed. A network of radars is considered, organized into multiple clusters, whose primary objective is to minimize their transmission power, while satisfying a certain detection criterion. Since no communication between the clusters is assumed, non-cooperative game theoretic techniques and convex optimization methods are utilized to tackle the power adaptation problem. During the proof of the existence and the uniqueness of the solution, which is also presented, important contributions on the SINR performance and the transmission power of the radars have been derived. Game theory can also been applied to mitigate jammer interference in a radar network. Hence, a competitive power allocation problem for a MIMO radar system in the presence of multiple jammers is investigated. The main objective of the radar network is to minimize the total power emitted by the radars while achieving a specific detection criterion for each of the targets-jammers, while the intelligent jammers have the ability to observe the radar transmission power and consequently decide its jamming power to maximize the interference to the radar system. In this context, convex optimization methods, noncooperative game theoretic techniques and hypothesis testing are incorporated to identify the jammers and to determine the optimal power allocation. Furthermore, a proof of the existence and the uniqueness of the solution is presented. Apart from resource allocation applications, game theory can also address distributed beamforming problems. More specifically, a distributed beamforming and power allocation technique for a radar system in the presence of multiple targets is considered. The primary goal of each radar is to minimize its transmission power while attaining an optimal beamforming strategy and satisfying a certain detection criterion for each of the targets. Initially, a strategic noncooperative game (SNG) is used, where there is no communication between the various radars of the system. Subsequently, a more coordinated game theoretic approach incorporating a pricing mechanism is adopted. Furthermore, a Stackelberg game is formulated by adding a surveillance radar to the system model, which will play the role of the leader, and thus the remaining radars will be the followers. For each one of these games, a proof of the existence and uniqueness of the solution is presented. In the aforementioned game theoretic applications, the radars are considered to know the exact radar cross section (RCS) parameters of the targets and thus the exact channel gains of all players, which may not be feasible in a real system. Therefore, in the last part of this thesis, uncertainty regarding the channel gains among the radars and the targets is introduced, which originates from the RCS fluctuations of the targets. Bayesian game theory provides a framework to address such problems of incomplete information. Hence, a Bayesian game is proposed, where each radar egotistically maximizes its SINR, under a predefined power constraint

A Tutorial on the Optimization of Amplify-and-Forward MIMO Relay Systems

The remarkable promise of multiple-input multiple-output (MIMO) wireless channels has motivated an intense research activity to characterize the theoretical and practical issues associated with the design of transmit (source) and receive (destination) processing matrices under different operating conditions. This activity was primarily focused on point-to-point (single-hop) communications but more recently there has been an extensive work on two-hop or multi-hop settings in which single or multiple relays are used to deliver the information from the source to the destination. The aim of this tutorial is to provide an up-to-date overview of the fundamental results and practical implementation issues of designing amplify-and-forward MIMO relay systems

Achievable Rates and Resource Allocation Strategies for Imperfectly Known Fading Relay Channels

Achievable rates and resource allocation strategies for imperfectly known fading relay channels are studied. It is assumed that communication starts with the network training phase in which the receivers estimate the fading coefficients. Achievable rate expressions for amplify-and-forward and decode-and-forward relaying schemes with different degrees of cooperation are obtained. We identify efficient strategies in three resource allocation problems: (1) power allocation between data and training symbols, (2) time/bandwidth allocation to the relay, and (3) power allocation between the source and relay in the presence of total power constraints. It is noted that unless the source-relay channel quality is high, cooperation is not beneficial and noncooperative direct transmission should be preferred at high signal-to-noise ratio (SNR) values when amplify-and-forward or decode-and-forward with repetition coding is employed as the cooperation strategy. On the other hand, relaying is shown to generally improve the performance at low SNRs. Additionally, transmission schemes in which the relay and source transmit in nonoverlapping intervals are seen to perform better in the low-SNR regime. Finally, it is noted that care should be exercised when operating at very low SNR levels, as energy efficiency significantly degrades below a certain SNR threshold value

Outage Probability in Multimodal Networks

In the mid 1990\u27s wireless researchers discovered that additional antennas located at the transmitter, receiver or both could help combat the unpredictable nature of the wireless channel. This field of research, known as MIMO (Multiple-Input Multiple-Output), became very active and has been thoroughly studied. Manufacturers have sought to incorporate these performance gains into their devices by including multiple transmit and receive antennas. However, as wireless devices such as mobile phones become smaller it becomes impractical to design a handset with multiple antennas.;Cooperative diversity is a technique that may be employed when device sizes are too small to incorporate a local antenna array. Using cooperative diversity, multiple wireless nodes cooperate to pass a message from a source to a destination. This leads to a virtual antenna array, allowing single-antenna devices to enjoy the benefits of a MIMO system. While cooperative diversity offers benefits, it motivates additional wireless nodes in the network. Even without cooperative diversity, our lives are increasingly dependent on a growing number of wireless devices. It\u27s obvious that the density of wireless devices in daily use will increase, and that rise in popularity demands the most optimal use of node resources.;Unfortunately, it has been shown that as the density of wireless devices for a given area increases, in the limit, the capacity of the network goes to zero. Even with advances such as MIMO and cooperative diversity, it\u27s obvious that a wireless-only future is impossible. For non-diminishing throughput, as wireless networks continue to grow in size, networks of the future will continue to incorporate additional modes of communication; wired, infrared, ultrasonic or other. In our work, we provide a strategy for harnessing these additional modes and optimizing across all the available modes of communication.;In this thesis, we present a protocol for wireless relay networks with an additional non- fading mode of communication available. As an example, we assume the presence of an additional wired channel in a relay network operating under the Laneman protocol, and we find analytical expressions for outage probability assuming communications over the wired and wireless channels are jointly optimized. We consider two cases: adding a channel between the source and a relay, and adding a channel between a relay and the destination. We show that a channel placed between the source and a relay separated by a poor wireless channel improves performance with few assumptions on the characteristics of the wire and over a wide range of wire channel transmit powers