Abstract
Multiuser orthogonal frequency division multiplexing (MU-OFDM) is one of the promising techniques for next-generation wireless broadband networks. Although the overall capacity of an MU-OFDM system can be maximized by assigning each subchannel to the user with the best channel-to-noise ratio for that subchannel and distributing power subsequently by water-filling, the complexity is too high to be acceptable for practical applications. To avoid the prohibitive complexity for solving the joint subchannel and power allocation problem, many suboptimal algorithms have been studied in the literature. Among them, separating the subchannel allocation from the power allocation is one of the common schemes. In general, such suboptimal resource allocation methods have a tradeoff between the system capacity and computational complexity. This thesis presents a suboptimal resource allocation algorithm for cooperative MU-OFDM systems, where the effect of the spatial diversity on the system capacity is investigated. By simplifying a three-node relay network to a two-node network, the resource allocation problem for cooperative MU-OFDM systems is equivalent to that for the traditional MU-OFDM systems. To use the decode-and-forward scheme in the cooperative network, an additional constraint is put on the resource allocation problem. It is shown that the proposed algorithm increases the system capacity with the same order of computational complexity as a non-cooperative MU-OFDM system. To further improve the spectrum efficiency, we employ the concept of cognitive radio to cooperative MU-OFDM systems. In such cognitive radio systems, the resource allocation problem must include a peak power constraint to protect the primary users. It is demonstrated that the proposed cooperative multiuser OFDM-based cognitive radio system has higher system capacity than that without combining cooperative communications under the same order of computational complexity.