載波頻率偏移(Carrier Frequency Offset, CFO)會導致正交分頻多工系統(Orthogonal Frequency Division Multiplexing, OFDM)子載波間失去正交性而產生載波間干擾(Inter-Carrier Interference, ICI),因而降低系統效能。另外,上行正交分頻多重存取系統(Orthogonal Frequency Division Multiple Access, OFDMA)中由於基地台同時接收多個用戶之上傳訊號,因而須承受多用戶的載波頻率偏移(CFOs),除造成更嚴重的子載波間干擾(ICI),也引入多用戶干擾(Multiple Access Interference, MAI),因而進一步惡化系統效能,因此近年來CFOs估測技術的研究一直廣受關注。本研究整合粒子群(Particle Swarm Optimization, PSO)與引力搜尋演算法(Gravitational Search Algorithm, GSA)的優點,發展一套演化式演算法(Evolutionary Algorithms),並將之應用在基於空子載波(Null Subcarrier)架構(系統1)及文獻[21,22]架構(系統2)兩種系統中估測CFOs。我們在雷利環境下進行一系列模擬實驗,實驗結果顯示此一演算法的效能優於其他演算法。另外,系統1與系統2的效能互有領先,但系統1可以獲得遠優於系統2的子載波使用效率。
In orthogonal frequency division multiplexing (OFDM) system, carrier frequency offset (CFO) is an important factor that destroys orthogonality among subcarriers. This will lead to inter-carrier interference (ICI) and therefore significantly degrades system performance. Moreover, in the uplink orthogonal frequency division multiple access (OFDMA) system, the base station will receive multiple CFOs from multi-user which causes multiple access interference (MAI), further degrading system performance. Hence the research on CFO estimation has received much attention in recent years. This study develops an evolutionary algorithm by taking the advantages of both the particle swarm optimization (PSO) and gravitational search algorithm (GSA) for CFOs estimation in two different systems, which are null subcarrier-based system (System-1) and [21,22] system (System-2). A series of experiments is conducted over Rayleigh fading channel with various users and the results indicate that performance of the proposed hybrid scheme is superior to other methods. In addition, System-1 and System-2 have comparable performances, but System-1 has much higher subcarrier utilization efficiency.