Competition, cooperation and cognition in wireless resource allocation

Abstract

Efficient wireless resource allocation is becoming increasingly important with the growing demand of wireless services. Wireless devices in a battery-limited ad hoc network use a shared resource for communication. Thus, an energy-efficient Medium Access Control (MAC) is necessary to control the contention among different links to decrease intra-network interference and maintain efficient and fair resource allocation. The coupled variables due to interference across wireless links challenge the MAC design. In addition, to mitigate the crowded spectrum occupancy in unlicensed frequency bands, the forthcoming paradigm shifts from fixed spectrum allocation to dynamic spectrum access with the support of cognitive radio technology. Then inter-network interference and Quality of Service (QoS) issues should be addressed in cognitive radio networks. However, the QoS provision and interference limit are two conflicting constraints. How to deal with these conflicting constraints with competitive users is also a great challenge. For the wideband wireless services, relay-based cooperative communication combined with the Orthogonal Frequency-Division Multiple Access (OFDMA) can further increase the network capacity by exploiting spatial diversity and multi-user diversity. Efficient approach with a high network capacity at the lowest cost is desired to solve the integer/combinatorial optimization problem in cooperative communications. This thesis addresses the wireless resource allocation problems from single-channel to multi-channel networks with methods involving game theory and optimization. In the case of intra-network interference management, the fairness, collision, and energy efficiency issues in MAC design are studied within game theoretic framework. The first is a cooperative game theoretic MAC, where each user adapts its channel access strategy towards a stable Pareto optimal Nash equilibrium (NE). In the second non-cooperative MAC, each user updates its channel access strategy based on its local information and a Pareto dominant NE can be achieved. We further design rate control and MAC jointly to maximize the network lifetime. Then a cross-layer algorithm is developed to arrive at a global optimal solution to the formulated nonconvex optimization problem. In the case of inter-network spectrum sharing, secondary users’ QoS provision with interference temperature constraint is formulated as a non-convex optimization problem. A joint random access and power control is proposed to find the global optimal solution to the formulated problem with cooperative users. We also investigate the issue of competitive multiple users’ access to the shared spectrum based on measured signal to interference ratio and interference temperature. Then a channelaware access algorithm is developed, which guarantees that a unique fixed point can be reached. Furthermore, it can be interpreted as a non-cooperative game. We then extend the non-cooperative game model to incorporate more general utility functions and cost functions. A distributed iteration algorithm is proved to converge to the unique NE with both continuous and discrete manners. In the case of multi-channel network, we focus on the cooperative resource allocation for a uplink cellular network, with OFDMA technology. To satisfy the heterogeneous rate requirement of each user while considering the fairness and efficiency as performance indices, the bargaining theory is applied to allocate resource at a relay node to multiple source nodes. Motivated by the fact that each source’s achievable rate on individual subcarrier is limited by decodability constraint, we apply the Kalai-Smorodinsky bargaining (KSB) theory to allocate resource at the relay fairly. By employing time-division techniques, the scheduling and power allocation problem is solved efficiently and simply, while KSB solution fairness criterion is maintained. To improve system efficiency, the Nash bargaining (NB) problem is formulated to maximize NB solution fairness criterion by exploiting multiuser diversity. A simple yet efficient algorithm is derived to assign subcarrier and power at the relay for multiple users.