| The business of data communication and cloud computation has shown explosivegrowth, and doubled the energy consumption. Designing energy-efficient datatransmission becomes an important direction of wireless communication research.Cognitive radio was designed to relieve the shortage of spectrum resource, which couldchange the parameters of the transmitter in real time by detecting the communicationenvironment and feedback information. Therefore, cognitive radio network, cognitiveability and learning ability can be a flexible solution to energy-efficient transmission inwireless communication.There are two problems when designing energy-efficient transmission in cognitiveradio network: one is the cognitive network itself should achieve energy efficiency, theother is wireless communication network should attain energy-efficient with the help ofcognitive function. In this thesis, the energy efficiency analysis consists of twoperspectives: the cognitive network itself and the wireless communication networkbased on cognitive function.Energy-efficient transmission design purpose is to adjustthe transmission parameters to maximizenumber of transmitted data per Joule of energyor minimize energy consumption per unit of transmitted data bit, namely optimal energyefficiency.For cognitive network, single-channel model is used to analyze the influence ofsensing time and transmission time on energy efficiency and energy efficiencyoptimization model is established to get the optimal time for sensing and transmissionwith the method of alternative optimization. Besides, the average idle period of PU isstudied by simulation as well as the transmission power influence on optimal sensingtime and transmission time.Meanwhile, multi-channel model is used to analyze theinfluence of sensing time and access power allocation on energy efficiency underaverage interference power and average transmit power constraint，based on WSSS andWOSA mode, using nonlinear fractional programming to get the optimal sensing timeand access power allocation. The idle prior probability of PU and the number of accesschannel’sinfluence on energy efficiency are also investigated. For the wireless communication based on cognitive function, we analyze thecomposition of system energy consumption and the influence of encoding andmodulation mode on energy efficiency. Optimization model is established to comparewith energy efficiency in the coded and uncoded systems.Simulation verifies the impactof optimal modulation order and optimal coding scheme on energy efficiency withdifferent distance and coding gain’s influence on transmission power when adoptingdifferent coding schemes. |
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