Spectrum efficiency maximization in multiband OFDM ultra wideband cognitive radio systems

UltraWideband is a high-speed, short-range and low-power wireless technology. UWB system is overlapped with wireless systems such as WLAN, WiMax and UMTS, which limits the use of UWB. Cognitive radio technology enables the UWB system to efficiently use the overlapped spectrum without causing interference to other wireless systems. The thesis focuses on the design of the cognitive radio resource allocation algorithms for spectrum efficiency maximization in the multiband OFDM UWB system. The spectrum efficiency of a cognitive UWB system depends on the cognitive algorithms used in spectrum sensing, spectrum sharing and spectrum management. The spectrum efficiency maximization problem is formulated to a multi-dimensional knapsack problem with constraints in the transmit power of the UWB subcarriers, the average bit error rate and the interference to the primary users. New cognitive algorithms for spectrum sensing and spectrum management are developed to solve the optimization problem. The proposed low-complexity cognitive algorithms include: primary and advanced power allocation algorithm, group power allocation algorithm and spectrum sensing time optimization algorithm. In a cognitive UWB system, the primary and advanced power allocation algorithm as well as the group power allocation algorithm are used for spectrum management, while spectrum sensing time optimization algorithm is used for spectrum sensing. The spectrum sensing time optimization algorithm computes the optimal spectrum sensing period which maximizes the cognitive UWB system’s data transmission period while guaranteeing a target probability of detection/false-alarm. During the data transmission period, the primary and advanced power allocation algorithm achieves the optimal spectrum efficiency by equally allocating the transmit power and distributing the excessively allocated power to the subcarriers in a greedy manner. Also, the group power allocation algorithm can obtain the optimal spectrum efficiency by adaptively assigning the transmit power to the subcarrier groups according to the effective signal-to-noise ratio of each subcarrier group whose bandwidth is less than the coherence bandwidth of the UWB channel. For energy-limited cognitive UWB system, the proposed cognitive algorithms maximize the spectrum efficiency with lower order-of-growth than the traditional dynamic radio resource allocation algorithms.