Antenna Selection And Blind Adaptive Signal Processing Algorithms For MIMO Communication Systems

Along with the development of the service requirements, Wireless communications have developed from only voice service to multi-media service such as image,video and data. The rich media content leads to demand for high access data rate. High data rate wireless communication,nearing Gbps transmission rates, is of interest in emerging WLAN (Wireless Local Area Networks). Additionally,future home Audio/Visual networks will be required to support multiple high-speed HDTV(High Definition Television),which again demand near Gbps data rates. So high transmission rate is a big challenge to the limited frequency spectral. The research of information theory has demonstrated that MIMO(Multi-Input-Multi-Output) system which employs multiple antennas both at the transmit side and the receive side can increase heavily the capacity of wireless communication systems,also can improve the system performance. So MIMO is very fit for the high data service in B3G/4G wireless communications. Therefore,MIMO has been the key technology for next generation wireless communications.MIMO can provide both multiplex gain and diversity gain, spatial multiplex gain is regarded as the most important avail of MIMO, spatial multiplex extend the channel dimensions,and offer a linear increase scaled to the antenna number for no additional power or bandwidth expenditure,which enlarge frequency spectral efficiency by a long way. spatial multiplex is achieved by Layered Space-Time Code, such as D-BLAST,V-BLAST and H-BLAST.Diversity technique is a powerful technique to mitigate fading in wireless links. Diversity techniques rely on transmitting the signal over multiple independently fading paths(in time/frequency/space). Spatial (or antenna) diversity is preferred over time/frequency diversity as it does not incur an expenditure in transmission time or bandwidth. Diversity improve the transmission reliability and enhance Qos(Quality of Service). If the M_TM_R links composing the MIMO channel fade independently and the transmitted signal is suitably constructed, the receiver can combine the arriving signals with considerably reduced amplitude fade in comparison to a SISO link and get M_TM_Rth-order diversity. Extracting spatial diversity gain in the absence of channel knowledge at the transmitter is possible using suitably designed transmit signals. The corresponding technique is known as space-time code. STBC and STTC are the most famous code until now.The core idea of MIMO is space-time processing. Here "time" is the time dimension the same as the traditional data communications. And the "space" is the constructed spatial distributing dimension by multiple antennas both at the transmitter and the receiver. Such system can be regarded as a extent from traditional smart antennas, which is a popular technology to improve the wireless communication system performance.The hot topics of MIMO include information theory and code design, antenna subset selection, antenna design and channel modeling, MIMO-OFDM, precode, multi-user MIMO and so on. This paper mainly focuses on MIMO antenna subset selection algorithm and blind adaptive algorithm of Orthogonal Space-Time Block Coded MIMO system.Transmit/receive antenna selection barters little lost of system performance for great decreasing of RF cost, making MIMO system not fully limited by RF cost. To quickly select transmit/receiver antenna subset making the system capacity best, we proposes a fast iterative antenna selection algorithm. The algorithm is based on greedy method: Based on the current system capacity, get rid of the antenna which makes least system capacity degradation. The algorithm reduces the computation complexity by updating the quantities in real time. Simulation results indicate that the algorithm decreases computation time a lot without any system capacity lost.Based on OSTBC(Orthogonal Space-Time Block Code) MIMO system model and Constellation Invariance character, we present a blind adaptive receiver for Orthogonal Space-Time Block Coded Multi-input-Multi-Output Antenna System, which exploits the Orthogonality of Space-Time Block Code. An unconstrained cost function is provided for the Orthogonal Space-Time Block Coded Multi-input-Multi-Output Antenna System. The global minima of the cost function are analyzed: in fact the global minima of the cost function is the normalized channel vector. Based on this result, by projection approximation method the original cost function is approximately changed from second order to forth order. Then LMS and RLS adaptive algorithm realizations are given built on the new unconstrained cost function. Simulation results demonstrate that this receiver can track the changes of the fading channel and decode the transferred symbols without pilot symbols.