On Sensing Scheduling Strategy Of Dynamic Spectrum Access System

The current communication systems are characterized by a static spectrum allocationpolicy according to the spectrum allocation bodies around the world, and few spectrum re-sources are currently available for future wireless applications. However, the current spec-trum utilization is much inefficient according to recent surveys. As more and more wirelessservices appear, the contradiction between large demand for spectrum resource and ineffi-cient spectrum utilization becomes more and more sharp. As one of effective schemes tomitigate this contradiction, dynamic spectrum access has obtained widely attention fromacademia and industry. In dynamic spectrum access system, when primary users (i.e., theusers that have static allocated spectrum) are inactive, secondary users (i.e., the users thathave no static allocated spectrum) could utilize the spectrum for communications. There-fore, spectrum sensing scheduling strategies, which are commonly recognized as two of themost fundamental elements in dynamic spectrum access system, are also widely discussedby researchers.This thesis studies effective spectrum sensing scheduling strategies in dynamic spec-trum access system, which are suitable for different application scenarios. The contents ofthis thesis are listed as follows.The adaptive collaborate sensing scheduling scheme in dynamic spectrum access basedcellular network is studied to acquire more spectrum opportunities in a limited sensing time.We construct a novel MAC-layer sensing framework for efficient acquisition of spectrumopportunities. Specifically, we employ the sequential probability ratio test and develop anew collaboration sensing scheme for multiuser to collaborate during multi-slot, in whichwe effectively utilize the resources of unlicensed users to sense the channels for efficientacquisition of spectrum opportunities. Subsequently, we formulate the proposed scheme asan optimization problem and derive an optimal solution with low complexity, which is basedon dynamic programming theory.The spectrum sensing scheduling strategy in dynamic spectrum access based highspeed vehicle communication network is studied to maximize the available spectrum re- source utilized by the unlicensed users. Specifically, we propose the dynamic spectrumaccess based high speed vehicle network (DSA-HSVN), where high speed vehicles couldeffectively sense and access the TV white spaces under the scheduling of the unlicensedbase station. Subsequently, we formulate the scheduling and allocation of spectrum re-source as an optimization problem to maximize the available spectrum resource utilized bythe DSA-HSVN, and investigate the property of the DSA-HSVN to reduce the complexityby separation computing method without loss of optimality. Furthermore, we analyze theoptimal solution based on branch and bound method and the suboptimal solution based onlinear programming.The impact of spectrum sensing and access strategies on electricity load shaping indynamic spectrum access based smart grid is studied. First of all, we propose a novelload shaping strategy for energy storage-enabled smart grid. In the proposed strategy, theutility obtains the load information of all consumers via dynamic spectrum access basedwireless communications. Then, according to the load information, the price of electricityis determined by a proposed dynamic pricing scheme, called as load differentiation dynamicpricing, to encourage the consumers to rationally use the energy storage for reducing thepeak of the total electricity load and increasing the valley of the total electricity load.Meanwhile, the full experiences of the consumers are guaranteed. More importantly, basedon the proposed load shaping strategy and dynamic pricing scheme, each consumer canindividually decide its own action policy of using electricity, i.e., the concrete action policyof using electricity can be implemented in a distributed fashion. In the dynamic spectrumaccess based communication module, we propose two spectrum sensing schedule strategieswhich are suitable for two different scenarios, and analyze the impact on the performanceof the proposed electricity load shaping scheme.