Performance of Cognitive Radio Networks with Unknown Dynamic Primary User Signals

The current static assignment of RF spectrum in the United States and other parts of the world has led to a large portion of the RF spectrum to be geographically and temporally underutilized. While the amount of RF spectrum is finite, the demand for spectrum continues to increase making it necessary to increase utilization of many bands. Several innovative methods for allowing licensed primary users (PUs) to share spectrum with unlicensed secondary users (SUs) have being proposed. Of these methods Cognitive Radio (CR) has emerged as a promising technology that enables SUs to dynamically access spectrum after first sensing the spectrum to ensure the PU is not active. Sensing performance is critical to a successful CR implementation, and within the last decade there has been significant CR research examining various sensing challenges and methods to improve sensing performance. The majority of this research has focused on PUs that utilize spectrum with relatively long idle and transmission periods which in turn allows for SU sensing periods with an extended duration. The work presented in this dissertation focuses on CR systems where the PU is highly dynamic and addresses several issues that arise when attempting to access this spectrum. In the case of a highly dynamic PU, it is not possible for the SU to increase the sensing period to improve performance, resulting in suboptimal sensing performance. A proposed hybrid framework is described which allows for suboptimal sensing performance by limiting the SU transmission power dependent on the sensing capabilities. In order to quantify sensing capabilities, a mathematical model for describing the PU activity with respect to the SU sensing period is derived using the mean active and idle durations of the PU. Using this PU activity model, closed form mathematical expressions for sensing performance are provided for two different hypothesis tests. Finally, the PU activity model and corresponding expressions for sensing performance depend on knowing the mean PU active and idle durations; because the SU may not know these PU parameters, a modified expectation maximization algorithm is proposed to estimate these parameters and corresponding sensor performance

Performance analyses and design for cognitive radios

Cognitive radio has been proposed as a promising solution to the conflict between the spectrum scarcity and spectrum under-utilization. As the demand increases for wireless communication services, cognitive radio technology attracts huge attention from both commercial industries and academic researches. The purpose of this thesis is to provide an analytical evaluation of the cognitive radio system performance while taking into consideration of some realistic conditions. Several problems are investigated in this thesis. First, by adopting a dynamic primary user traffic model with one primary user occupancy status change and exponentially distributed channel holding times, its effect on the cognitive radio system performance is evaluated. In the evaluation, the sensing-throughput tradeoff of the cognitive radio is used as the examination criteria, while energy detection is applied during the spectrum sensing. The thesis then takes the investigation further by establishing a primary user multiple changes traffic model which considers multiple primary user occupancy status changes and any reasonable channel holding time distributions. The effect of the primary user multiple changes traffic on the spectrum sensing performance is investigated while the channel holding times are assumed to be exponential, Gamma, Erlang and log-normal distributed. The analytical evaluation of cognitive radio is also carried out from the secondary user transmission perspective, where the performance of the adaptive modulation in cognitive radio system is investigated. The effect of the cognitive radio distinctive features on the performance of both the adaptive continuous rate scheme and the adaptive discrete rate scheme of the adaptive modulation are examined. The BER performance and the link spectral efficiency performance are derived for both schemes. A novel frame structure where the spectrum sensing is performed by using the recovered received secondary frames is also evaluated in this thesis. A realistic scenario which considers the secondary user signal decoding errors is examined for the novel structure, while an ideal upper bound performance is given when the decoding process is assumed perfect. By extending the system to include multiple consecutive secondary frames, the performance of the novel structure is compared to the performance of the traditional frame structure proposed by the IEEE 802.22 WRAN standard. The effect of the primary user multiple changes traffic is also examined for the novel structure. Several major findings are made from the analytical evaluations presented in this thesis. Through numerical examinations, it was shown that, first, the dynamic primary user traffic degrades the performance of cognitive radio systems. Second, the degree of the performance degradation of the cognitive radio systems is related to the number of primary user status changes and the primary user traffic intensity. Different primary user channel holding times distributions also lead to different sensitivities of the system performance to the primary user traffic. Third, cognitive radio distinctive features degrades the performance of the adaptive modulation. When the novel structure is applied for cognitive radio, a higher secondary achievable throughput can be obtained with a limited saturation threshold