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Beamforming Based On Limited Feedback In Multiple-Antenna Systems

Posted on:2010-12-15Degree:DoctorType:Dissertation
Country:ChinaCandidate:L ZhangFull Text:PDF
GTID:1118360275979998Subject:Communication and Information System
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In wireless communications multiple antenna transmission (viz. Multi-Input Multi-Output, MIMO) has received increasing attention in recent years, thanks to its potential for high spectral efficiency and improved quality of service. A predominant characteristic in a practical downlink is unsymmetrical structure of many transmit antennas and a few (even single) receive antennas. If no channel information is known to the transmitter, conventional spatial multiplexing or space-time coding can not explore space resource fully to improve performance. In contrast, if perfect channel information is available at the transmitter, some super precoding or beamforming techniques can be utilized to realize full diversity and array gains; however, this assumption is probably a utopia for most wireless environments. Consequently, multiple-antenna communications with partial channel information promise to have great practical value, because they are capable of offering the "jack of both trades." On the other hand, the total equivalent channel in practice is not strictly uplink-downlink reciprocal. So a reasonable approach for the transmitter obtaining channel information is to feedback the estimated one at the receiver. Furthermore, due to the rate constraint of the feedback link and requirement of digital realization, the channel information should be quantized by using some bits before feedback. Naturally, compared to the ideal case, precoding or beamforming with limited feedback has some loss in the performance and some different designs. This thesis focuses on beamforming with limited feedback in multiple antenna wireless systems.Most of prior research on beamforming in fiat fading channels includes several ideal conditions, such as block-fading channels, perfect channel information at the receiver, or error-free and zero-delay feedback link. We first study single user Multiple-Input Single-Output (MISO) systems over more realistic time-varying channels with imperfect feedback including estimation errors and feedback delay. An analytical framework is developed for evaluating average bit error rate (BER) of square/rectangle Quadrature Amplitude Modulation (QAM) constellations and ergodic capacity. Not only the close-form expressions of both exact BER and tighter capacity bounds are presented, but also the frame length is optimized according to the derived simple looser lower bound of BER/capacity from the viewpoint of system design.We further investigate beamforming in frequency-selective fading channels. By using Orthogonal Frequency Division Multiplexing (OFDM), the original broadband channels can be converted into many narrow-band subchannels (subcarreirs) with different frequency responses. We adopt rather subcarrier-clustering feedback than subcarrier-by-subcarrier one to reduce the immense overhead. Within one cluster, two optimal beamforming vector selection criteria are presented based on directly minimizing the average BER and maximizing the ergodic capacity, respectively. A simple sub-optimal algorithm is then proposed by exploiting the correlation of channel frequency responses at different subcarriers to reduce the computational complexity. The proposed schemes outperform other competitors in terms of BER or capacity. Furthermore, by integrating them into the existing adaptive quantization, a full feedback scheme corresponding to one OFDM symbol is developed to reduce feedback cost further without performance loss.We next extend our study to the multiuser case. The sum throughput is analyzed for multiuser MIMO broadcast systems using zero-forcing beamforming with limited feedback, and the close-form expression of its lower bound is given. We finally conclude the thesis by discussing some promising research directions.
Keywords/Search Tags:Beamforming, bit error rate (BER), capacity, limited feedback, multiple input multiple output (MIMO), multiple input single output (MISO)
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