A Theoretical And Algorithmic Research On User-Cooperation-Based Spectrum Sensing And Dynamic Access

In the last decade, the rapid growth of all kinds of wireless services and networks has led to an explosive demand onradio spectrum. Oppositely, large portion of the licensed spectrum is unused for a large amount of both time and space. To address the spectrum scarcity and the spectrum under-utilization, Cognitive Radio (CR) has been proposed to effectively utilize the spectrum. Spectrum sensing and access are essential components in CR networks to use the underutilized spectrum opportunities. Currently, many substantial contributions to the cooperative spectrum sensing and dynamic access have been made. However, some important theoretical and practical issues are still unsolved and they will be focused in this dissertation. The main contributions of this dissertation include:1. a new parallel spectrum sensing. In this scheme, several SUs are optimally selected to perform sensing. During a sensing period, each of the selected SUs senses a different channel. As a consequence, multiple channels can be simultaneously sensed in one sensing period and the sensing efficiency is envisioned to improve significantly. An analytical model is presented to investigate the tradeoff between the transmitted data and the sensing overhead. A throughput maximization problem is formulated to find key design parameters: the number of SUs that perform parallel sensing and the threshold in stopping the sensing. Both saturation and non-saturation situations are investigated with respect to throughput, transmission gain, overhead, and delay.2. the design of a group-based cooperative Medium Access Control (MAC) protocol called GC-MAC, which addresses the tradeoff between sensing accuracy and efficiency. In GC-MAC, the cooperative SUs are grouped into several teams. During a sensing period, each team senses a different channel while the SUs in a same team provide the joint detection of the targeted channel. The sensing process will not stop unless an available channel is discovered. To reduce the sensing overhead, an SU-selecting algorithm is presented to selectively choose the cooperative SUs based on the channel dynamics and usage patterns. Then, an analytical model is built to study the sensing accuracy-efficiency tradeoff under two types of channel conditions: time-invariant channel and time-varying channel. The achievable throughput maximization is formulated to optimize the important design parameters. Both saturation and non-saturation situations are investigated with respect to throughput and sensing overhead.3. an asynchronous cooperative sensing scheme in which each SU only provides its energy information in stead of ceasing its own transmission to perform the cooperative sensing. Each energy information is assigned an appropriate weight by considering the temporal and spatial diversities of each SU. We first investigate the two-user networks and formulate the probabilities of detection and false alarm as an optimization problem to find the optimal weight for every energy information. The achievable throughput has been derived. Then, we evaluate the scheme in the multiple-user networks. The specifications of the asynchronous cooperative protocols are elaborated in both centralized and decentralized networks for the sake of practical implementation.4. a new Time-Division Energy Efficient (TDEE) sensing scheme to significantly reduce the power consumption in CR networks. In the TDEE scheme, the total sensing period of each SU is divided into an optimal number of timeslots. In each timeslot, each SU is assigned to detect a different channel in one timeslot. After sensing, all SUs shall send the sensing results to the fusion center to make the final decision based on a fusion rule. An important advantage of TDEE is that the SUs do not need to exchange the control messages for the acknowledgement of a successful cooperation, leading to substantial energy saving without comprising sensing accuracy. It is clear that more divided timeslots may lead to more spectrum opportunities in one sensing period. Unfortunately, larger consumed energy will be incurred since each sensing SU is not able to transmit its own data during the sensing period. Hence, the number of divided timeslots is a crucial design parameter to balance the energy consumption and achievable throughput.5. a Triple Threshold Energy Detection (TTED) to identify the PUEA for the sensing model. Different to the single threshold in conventional energy detection, we use three thresholds not only to identify the presence of the PUs (determined by the first threshold) but also the presence of the fake PUs (determined by the next two thresholds). The channel is claimed be unavailable only when the received energy lies to the real PUs' energy range. An optimization problem is formulated to find the optimal thresholds to maximize the detection probability and minimize the false alarm probability of real PU. Then, based on the TTED, SUs are allowed to access the available channels when the licensed channel is idle or occupied by fake PUs. To evaluate our proposed access scheme, we derive the achievable throughput in the case while the average transmission time of each SU is fixed and exponential distributed, respectively.To summary, this thesis is focused on the theoretical analysis and algorithms development for the cooperative spectrum sensing and dynamic access in CR networks. Particularly, we perform in-depth study on the dynamic spectrum sensing in multiple uers CR networks.