Research On Turbo-BLAST Iterative Detection And Adaptive Resource Allocation In MIMO Communication

MIMO (Multiple Input Multiple Output) wireless channels are capable of improving the reliability and data rate of the wireless link. If no channel knowledge is available at the transmitter, technologies such as space time codes and spatial multiplexing may be employed to improve the system performance by exploiting diversity and multiplexing gains. If full or partial channel information is available, technologies such as precoding technique may be applied to enhance the link reliability and improve data rate. In multiuser environment, adaptive resource allocation technique will be exploited to improve the throughput of the system by allocating the subcarriers, power and bits adaptively. This thesis studies the open-loop MIMO transmission technique and the corresponding receiver, Turbo-BLAST iterative detection technique, multiuser adaptive resource allocation technique in the closed-loop MIMO communication system. The main contributions of this thesis are listed as follows:1. An enhanced detection scheme for Turbo-BLAST in MIMO-OFDM system in proposed. In this scheme, a new V-BLAST detector includes the error propagation effect is presented to prevent the error propagation from affecting the signal detection in subsequent layers. Also, combined with the iterative detection algorithm based on hard decision inference cancellation, the proposed scheme achieves obvious performance gains while the increased complexity is low.2. A low complexity space-time multiuser Turbo-BLAST iterative receiver scheme is proposed. In this scheme, instead of performing Symbol-Level cancellation, Bit-Level Cancellation (BLC) and detection is performed by decomposing of an M-QAM constellation into a linear combination of binary constellations and partial MAP detection based on partial hard decision cancellation algorithm is exploited. This scheme has a low complexity with little performance degradation compared with conventional iterative receiver, while the high spectral efficiency of the system from BLAST is retained.3. A new scheme based on proportional fairness for MIMO-OFDM downlink resource allocation is proposed. The basestation allocation of subcarriers and power to each user to maximize the sum of user data rates is considered, subject to constraints on total power, bit error rate, and proportionality among user data rates. Based on MIMO channel state information, eigen-channels are intelligently used to determine subcarriers allocation and power allocation, which forms the foundation of the new scheme. Also, a linear non-iterative power allocation method with low complexity is deduced that is made by our relaxation of strict user rate proportionality constraints. This new adaptive allocation scheme proposed can achieve good tradeoff between capacity and fairness as well as provide much better capacity gain than the conventional allocation methods, while requiring significantly less computation.4. An optimal resource allocation scheme for ergodic rates maximization with proportional fairness is proposed. Pervious research efforts to optimization OFDMA with respect to communication performance, the formulation and algorithms only consider instantaneous performance metrics and the temporal dimension is not being exploited when the resource allocation is performed. This scheme exploits frequency, time, and multiuser dimensions while enforcing various fairness though weighting factors to each user. A resource allocation scheme with proportional ergodic rate constraints is presented though imposing ratio constraints among the users'rates. When ergodic rates considered, obvious rates gains can be obtained, while the complexity is reduced when performing the actual resource allocation during data transmission versus instantaneous optimization.