Beyond white space : robust spectrum sensing and channel statistics based spectrum accessing strategies for cognitive radio network

Abstract

Cognitive radio refers to the technology that the devices can intelligently access unused frequency resources which are originally reserved for legacy services in order to increase the spectrum utilization. At the mean time, the legacy services should not be affected by the access of cognitive radio devices. The common problems in cognitive radio are how to find unused frequency resources (spectrum sensing) and how to access them (spectrum accessing). This dissertation focuses on the robust methods of spectrum sensing as well as spectrum accessing strategies with the statistics of channel availabilities. The first part of the thesis studies non-parametric robust hypothesis testing problem to eliminate the effect of the uncertainty and instability introduced by non-stationary noise, which is constantly observed in communication systems. An empirical likelihood ratio test with density function constraints is proposed. This test outperforms many popular goodness-of-fit tests, including the robust Kolmogorov-Smirnov test and the Cramér-von Mises test, etc. Examples using spectrum sensing data with real-world noise samples are provided to show their performance. The second part focuses on channel idle time distribution based spectrum accessing strategies. Through the study of the real-world wireless local area network traffic, it is identified that the channel idle time distribution can be modeled using hyper-exponential distribution. With this model, the performance of a single cognitive radio, or the secondary user, is studied when the licensed user, or the primary user, does not react to interference. It is also shown that with the complete information of the hyper-exponential distribution, the secondary user can achieve a desirable performance. But when the model exhibits uncertainty and time non-stationarity, which would happen for any kind of wireless traffic, the secondary user suffers from huge performance loss. A strategy that is robust to the uncertainty is proposed. The performance of this strategy is demonstrated using experimental data. Another aspect of the problem is when the PU is reactive. In this case, a spectrum accessing strategy is devised to avoid large-duration interference to the PU. Additionally, the spectrum accessing strategies are also extended to the cognitive radio networks with multiple secondary users. A decentralized MAC protocol is devised which reaches a total secondary capacity performance close to the optimal. A discussion of the engineering aspects with practical consideration of spectrum sensing and accessing is given at the end.