摘 要
隨著現(xiàn)代無(wú)線(xiàn)通信技術(shù)的快速發(fā)展，人們對(duì)高速數(shù)據(jù)通信服務(wù)的需求日益增長(zhǎng)，常規(guī)單天線(xiàn)收發(fā)通信系統(tǒng)的容量性能已經(jīng)遠(yuǎn)遠(yuǎn)不能滿(mǎn)足實(shí)際應(yīng)用的需求，通信系統(tǒng)的可靠性也有待進(jìn)一步提高。MIMO技術(shù)可以有效利用多徑效應(yīng)，在有限帶寬內(nèi)提高了傳輸速率和通信質(zhì)量，成為新一代無(wú)線(xiàn)通信系統(tǒng)中的關(guān)鍵技術(shù)之一。但由于MIMO系統(tǒng)需要配置多個(gè)RF鏈路，大幅度增加了系統(tǒng)硬件成本和信號(hào)處理的復(fù)雜度，這個(gè)問(wèn)題極大的限制了MIMO技術(shù)的發(fā)展和推廣。天線(xiàn)選擇技術(shù)通過(guò)選擇較優(yōu)的天線(xiàn)子集進(jìn)行收發(fā)，以較小的性能損失換取硬件成本和處理復(fù)雜度的大幅度降低，成為MIMO無(wú)線(xiàn)通信領(lǐng)域的一個(gè)研究熱點(diǎn)。
對(duì)于現(xiàn)有MIMO系統(tǒng)天線(xiàn)選擇算法而言，窮盡搜索算法能夠達(dá)到最優(yōu)的性能，但包含較多矩陣運(yùn)算，計(jì)算復(fù)雜度較高；為降低算法復(fù)雜度，許多次優(yōu)天線(xiàn)選擇算法應(yīng)運(yùn)而生，但這些算法大多造成了較大性能損失或復(fù)雜度仍較高，并主要集中于對(duì)非相關(guān)信道下天線(xiàn)選擇的研究。
針對(duì)這一問(wèn)題，本文以容量性能最大化為目標(biāo)，提出了基于相異度的天線(xiàn)選擇算法和針對(duì)相關(guān)信道下基于CSA的改進(jìn)選擇算法，并討論了幾種基于智能算法的收發(fā)聯(lián)合天線(xiàn)選擇技術(shù)。主要研究成果如下：
1．介紹了復(fù)高斯隨機(jī)信道和相關(guān)信道情況下MIMO的系統(tǒng)模型；對(duì)MIMO系統(tǒng)容量進(jìn)行分析，研究信道相關(guān)性對(duì)系統(tǒng)容量性能的影響，對(duì)幾種經(jīng)典天線(xiàn)選擇算法的容量性能進(jìn)行比較，仿真結(jié)果表明窮盡搜索算法能夠獲得最優(yōu)的容量性能，但復(fù)雜度非常高，經(jīng)典的遞增遞減算法獲得了接近最優(yōu)的容量性能，同時(shí)降低了系統(tǒng)復(fù)雜度。
2．以實(shí)現(xiàn)容量性能最優(yōu)為目標(biāo)提出了一種基于相異度的天線(xiàn)選擇算法。分析了采用相對(duì)誤差、絕對(duì)誤差對(duì)相異度算法性能的影響，同時(shí)通過(guò)對(duì)幾種算法的復(fù)雜度計(jì)算分析，證明所提算法保持了較低的運(yùn)算復(fù)雜度。通過(guò)仿真將其與窮盡搜索、基于相關(guān)度和相似度等天線(xiàn)選擇算法進(jìn)行了容量性能比較，仿真結(jié)果驗(yàn)證了所提算法在容量性能上的改進(jìn)。
3．針對(duì)相關(guān)信道，對(duì)基于相關(guān)性的天線(xiàn)選擇算法進(jìn)行改進(jìn)，通過(guò)選擇具有最小平均相關(guān)性和最大相關(guān)矩陣行列式的天線(xiàn)作為最優(yōu)天線(xiàn)子集。在選擇較少天線(xiàn)的情況，所提算法降低了計(jì)算復(fù)雜度，達(dá)到幾乎與相關(guān)性選擇算法相同的性能，且非常接近最優(yōu)選擇算法。仿真結(jié)果證明了該算法的有效性和可靠性。
4．介紹了基于遺傳算法和模擬退火算法的收發(fā)聯(lián)合天線(xiàn)選擇技術(shù)，并將遺傳算法與模擬退火算法結(jié)合得到一種新的基于智能算法的天線(xiàn)選擇方法。同時(shí)，對(duì)幾種算法的原理和性能進(jìn)行了討論，并給出其實(shí)驗(yàn)仿真結(jié)果。
關(guān)鍵詞 多輸入多輸出；天線(xiàn)選擇；相異度；相關(guān)性；遺傳算法；模擬退火
Abstract
Along with the development of wereless communication, the demand of high speed data communication is increasing, conventional single antenna communication system capacity can not meet the requirement of practial application, and the communication system reliability has yet to be further improved. Multiple-Input Multiple-Output (MIMO) technology can utilize multipath effect, and improve the transmission rate and communication quality. It becomes one of key technologies for new generation wireless communication systems. However, MIMO system needs multiple radio frequency (RF) chains for employing multiple antennas, this increase the cost of additional hardware and the complexity of signal processing substantially, and limits development and generalization of MIMO technology to a great extent. Antenna selection technology is to use only an antenna subset of transmit and receive with better performance, it can reduce the expense of hardware and complexity of processing with less performance loss, becomes research focus of MIMO wereless communication field.
As existing antenna selection algorithms in MIMO systems, the exhaustive search algorithm gets the optimum performance, but it requires lots of matrix operations, so leads to very high complexity. Some sub-optimal antenna selection algorithms emerge in order to decrease the complexity of algorithm, but most of these algorithms result in a greater performance loss or still higher complexity, and mainly concentrate on the antenna selection research in the non-correlated channels.
According to the problem, this paper takes the capacity performance maximize for a target, proposes an antenna selection algorithm based on dissimilarity, an improved selection algorithm based on CSA for correlated channel, and discussed several joint transmit/receive antenna selection technology based on smart algorithm. The main results are as follows:
1. MIMO system model in complex Gaussian random channel and correlated channel is introduced, then an analysis of MIMO system capacity and the impact of the channel correlation is given, several classical algorithms capacity performance are compared, the simulation results proved exhaustive search algorithm can obtain the optimal capacity, but the complexity is very high, the decremental algorithm and incremental algorithm get the closed optimal capacity, and lower the system complexity at the meantime.
2. The paper proposes an antenna selection algorithm based on dissimilarity, the algorithm goal is to maximize capacity. It analyzes the impact of relative error and absolute error to the property of dissimilarity algorithm; meanwhile the complexity is computed and analyzed to prove that the proposed algorithm maintains lower computation complexity. The capacity performance of the proposed algorithm, exhaustive search, the algorithms based on ..