DSP algorithms for MIMO based Systems

Multiple Input Multiple Output (MIMO) systems are an emerging wireless communication technology that gained popularity due to its capability to enhance spectral efficiency and reliability. Although MIMO enhances system capacity and performance, it could be challenging due to the high number of antennas at both the transmitter and receiver. It has been therefore one of the popular research areas during the last decade, meeting ever-increasing demands of data rates. Nevertheless, serving multiple terminals simultaneously is challenging due to interference among them. The main goal of this research is to mitigate interference among users, gain better energy and spectral efficiency by employing different digital signal processing (DSP) based algorithms in the multi-user MIMO communication paradigm. Moreover, we have investigated novel algorithms in order to mitigate inter-terminal interference by employing directional beams. In order to do so, it is imperative to perform channel estimation, which can be obtained by using time or frequency duplexing, although, with an increased number of antennas in large scale MIMO (massive MIMO), the problem becomes very complicated in both types of duplexing schemes. The research problem of reducing training and feedback overhead can be addressed properly if high dimensional signals are reduced to low dimensional, by taking the compressive sensing (CS) paradigm into account. A framework is proposed to reduce training and feedback overhead by considering the MIMO channel as sparse in mobile communication. Another important issue in modern MIMO communication systems is related to phase recovery. For this purpose, a reduced complexity Kalman filtering based solution is proposed to address the phase recovery problem in cross-polar interference cancellation (XPIC) system, which can be viewed as MIMO 2 x 2 channels. Another interesting application of MIMO based systems is presented for multiple implants in the intra-body network which utilized beamforming techniques to communicate in an energy-efficient manner. The comparison with state of the art methods is also exhibited. The research work conducted in this thesis addresses theoretical, methodological and empirical contributions to MIMO based system research problem and attempted to achieve better performance by employing different DSP based algorithms.

Multiple Input Multiple Output (MIMO) systems are an emerging wireless communication technology that gained popularity due to its capability to enhance spectral efficiency and reliability. Although MIMO enhances system capacity and performance, it could be challenging due to the high number of antennas at both the transmitter and receiver. It has been therefore one of the popular research areas during the last decade, meeting ever-increasing demands of data rates. Nevertheless, serving multiple terminals simultaneously is challenging due to interference among them. The main goal of this research is to mitigate interference among users, gain better energy and spectral efficiency by employing different digital signal processing (DSP) based algorithms in the multi-user MIMO communication paradigm. Moreover, we have investigated novel algorithms in order to mitigate inter-terminal interference by employing directional beams. In order to do so, it is imperative to perform channel estimation, which can be obtained by using time or frequency duplexing, although, with an increased number of antennas in large scale MIMO (massive MIMO), the problem becomes very complicated in both types of duplexing schemes. The research problem of reducing training and feedback overhead can be addressed properly if high dimensional signals are reduced to low dimensional, by taking the compressive sensing (CS) paradigm into account. A framework is proposed to reduce training and feedback overhead by considering the MIMO channel as sparse in mobile communication. Another important issue in modern MIMO communication systems is related to phase recovery. For this purpose, a reduced complexity Kalman filtering based solution is proposed to address phase recovery problem in cross-polar interference cancellation (XPIC) system, which can be viewed as MIMO 2 x 2 channels. Another interesting application of MIMO based systems is presented for multiple implants in the intra-body network, which utilized beamforming techniques to communicate in an energy-efficient manner. The comparison with state of the art methods is also exhibited. The research work conducted in this thesis addresses theoretical, methodological and empirical contributions to MIMO based system research problem and attempted to achieve better performance by employing different DSP based algorithms.