MIMO networking with imperfect channel state information

The shortage of radio spectrum has become the bottleneck of achieving broadband wire-less access. Overcoming this bottleneck in next-generation wireless networks hinges on successful implementation of multiple-input-multiple-output (MIMO) technologies, which use antenna arrays rather than additional bandwidth for multiplying data rates. The most efficient MIMO techniques require channel state information (CSI). In practice, such information is usually inaccurate due to overhead constraints on CSI acquisition as well as mobility and delay. CSI inaccuracy can potentially reduce the performance gains provided by MIMO. This dissertation investigates the impact of CSI inaccuracy on the performance of increasing complex MIMO networks, starting with a point-to-point link, continuing to a multiuser MIMO system, and ending at a mobile ad hoc network. Furthermore, this dissertation contributes algorithms for efficient CSI acquisition, and its integration with beamforming and scheduling in multiuser MIMO, and with interference cancelation in ad hoc networks. First, this dissertation presents a design of a finite-rate CSI feedback link for point-to-point beamforming over a temporally correlated channel. We address various important design issues omitted in prior work, including the feedback delay, protocol, bit rate, and compression in time. System parameters such as the feedback bit rate are derived as functions of channel coherence time based on Markov chain theory. In particular, the capacity gain due to beamforming is proved to decrease with feedback delay at least at an exponential rate, which depends on channel coherence time. This work provides an efficient way of implementing beamforming in practice for increasing transmission range and throughput. Second, several algorithms for multiuser MIMO systems are proposed, including CSI quantization, joint beamforming and scheduling, and distributed feedback scheduling. These algorithms enable spatial multiple access and multiuser diversity in a cellular system under the practical constraint of finite-rate multiuser CSI feedback. Moreover, this dissertation shows analytically that the throughput of the MIMO uplink and downlink using the proposed algorithms scales optimally as the number of users increases. Finally, the transmission capacity of a MIMO ad hoc network is analyzed for the case where spatial interference cancelation is applied at receivers. Most important, this dissertation shows that this MIMO technique contributes significant network capacity gains even if the required CSI is inaccurate. In addition, opportunistic CSI estimation is shown to provide a tradeoff between channel training overhead and CSI accuracy.