|摘要: ||本論文之研究目的以多輸入多輸出和中繼器來提升通訊品質之研究。利用射線彈跳追蹤法(Shooting and Bouncing Ray/Image Techniques, SBR/Image Techniques)，求得超寬頻（Ultra Wideband, UWB）通訊與無線區域網路（Wireless Local Area Network, WLAN）系統的通道特性參數。第一部份研究求得多輸入多輸出(Multiple-Input Multiple-Output, MIMO) WLAN系統在六種不同走道的頻率響應和脈衝響應，並去計算和比較MIMO-WLAN系統的通道特性。這六種不同的走道分別為：1.矩形截面直線走道、2.矩形截面圓弧走道、3.拱門截面直線走道、4.拱門截面圓弧走道、5.矩形截面L形走道、6.矩形截面T形走道。若SNR定義為接收機前端之信號平均功率對雜訊功率的比值，從模擬結果得到T形走道的通道容量最大，且矩形截面走道的通道容量普遍大於弧形截面的走道。|
第二部份以基因演算法（Genetic Algorithms, GA）、粒子群聚最佳化法（Particle Swarm Optimization, PSO）、非同步粒子群聚最佳化法（Asynchronous Particle Swarm Optimization, APSO）與動態差異型演化法（Dynamic Differential Evolution, DDE）來最佳化室內MIMO-WLAN通訊系統之發射天線位置。計算出發射天線與接收天線間之通道頻率響應，並求出通訊過程中的通道容量。將演算法和射線彈跳追蹤法結合模擬複雜環境。藉由模擬去計算MIMO-WLAN系統在真實環境下之通道容量。以演算法找到最佳發射天線位置，使系統的通道容量提升。選用適當發射天線的位置預測無線電波傳輸時的特性，可以提升通訊品質。
第四部份研究同頻干擾(Co-Channel Interference, CCI)對MIMO-WLAN系統通道容量的影響。首先，在MIMO-WLAN系統中，計算出有無同頻干擾情況下其通道容量，其中，干擾源包括單一干擾和多根干擾。其次，使用均勻線性陣列（Uniform Linear Array, ULA）天線和極化分集陣列（Polarization Diversity Array, PDA）天線，來探討對於系統通道容量的影響。在MIMO-WLAN中傳送端、接收端和多個同頻干擾皆採用此兩種天線陣列探討。研究結果顯示，沒有同頻干擾的情況下，均勻線性陣列天線相較於極化分集陣列天線的通道容量高。有同頻干擾時，極化分集陣列天線的通道容量比均勻線性陣列天線高。
Quality improvement of communication systems by multiple-input multiple-output and relays in real environments are investigated. The channel statistics parameters of ultra wide band (UWB) and wireless local area network (WLAN) are computed by applying shooting and bouncing ray/image (SBR/Image) techniques. First, a comparison of multiple-input multiple-output (MIMO) WLAN communication characteristics for six different geometrical shapes is investigated. These six shapes include the straight shape corridor with rectangular cross section, the straight shape corridor with arched cross section, the curved shape corridor with rectangular cross section, the curved shape corridor with arched cross section, L-shape corridor, and T-shape corridor. The frequency responses and impulse responses of these corridors are computed by applying SBR/Image techniques. By using the frequency responses and impulse response of these multi-path channels, the channel capacity and statistic parameters for these six corridors could be obtained.
The second part, the genetic algorithm （GA）, particle swarm optimization （PSO）, asynchronous particle swarm optimization （APSO） and dynamic differential evolution （DDE） are used to optimizing the objective functions (criterion for measuring the effectiveness of the obtained optimized algorithm solution) and solved in indoor MIMO-WLAN communication system. The optimal locations of the transmitter antenna for channel capacity in indoor environment MIMO-WLAN wireless communication systems are evaluated in the whole indoor environment. The channel capacity is chosen as the objective function. Based on the SBR/Image performance, the channel capacity for any given location of the transmitter can be computed. The optimal transmitting antenna location for maximizing the channel capacity is searched by algorithms. Obtained simulation results illustrate the feasibility of using the integrated ray-tracing, and optimization methods to find the optimal transmitter locations in determining the optimized channel capacity of a wireless network. Numerical results show that the performance for increasing of channel capacity by optimization algorithm is quite good. The investigated results can help communication engineers improve their planning and design of indoor wireless communication.
The third part, an optimization procedure for the location of the transmitter antenna and relay transceiver in UWB wireless communication system is presented. The impulse responses of different transmitter antenna and transceiver locations are computed by SBR/Image techniques and inverse fast Fourier transform (IFFT). By using the impulse responses of these multi-path channels, the bit error rate (BER) performance for binary pulse amplitude modulation (BPAM) impulse radio UWB communication system are calculated. Based on the BER performance, the outage probability for any given transmitter antenna and relay location of the transceiver can be computed. The optimal transmitter antenna and relay antenna location for minimizing the outage probability is searched by GA, PSO, APSO and DDE. Numerical results have shown that our proposed method is effective to find the optimal location for transmitter antenna and relay antenna.
The fourth part, the dissertation focuses on the research of channel capacity of MIMO-WLAN system with co-channel interference (CCI) in indoor environment. The channel capacities are calculated based on the realistic environment. First, channel capacities of the MIMO-WLAN system without and with CCI are calculated for both single and multiple transmitting antennas of the CCI. Next, the channel capacities by using simple uniform linear array (ULA) and polarization diversity array (PDA) deployment are calculated. According to the results, for the case without CCI channel capacity of ULA is better than that of PDA in indoor wireless communication. However, the channel capacity for the PDA is better than that for of ULA when interference exists.