Beamforming for multiuser MIMO systems

Wireless communications systems use a multiple user scheme such as time- or frequency-division,but these do not allow truly simultaneous use of the spectrum. By deploying multiple antennas andbeamforming, it is possible, in principle, for users to share the spectrum simultaneously, and thisscenario is called the multiuser MIMO interference channel. This thesis presents new beamfomingdesign methods for this channel, derived from the convergence criteria for multi-objective optimization.Beamforming is proven to be possible for any combination of communications objectivefunctions such as mean-square error, signal-to-interference plus noise ratio, and leakage interference.Relationships are found between the number of users and number of antennas, for different objectivefunctions. The existence of a Nash equilibrium is guaranteed and the important networkingproperties of quality of service and fairness among users are accounted for. A new optimizationalgorithm, which is an extension of alternating optimization, is formulated for the design process.Its advantage over existing approaches is its significantly lower computational complexity. Severaloptimized, multi-user OFDM systems are formulated and demonstrated by simulation using statisticalchannel models in a multipath environment. The feedback overhead required for deploying thebeamforming is quantified, showing the trade-off among complexity, minimum number of antennasrequired, error performance, capacity, feedback rate, and the ability to extract multi-path diversityfor multiple users. When one of the users has priority access to the spectrum, the channel takes ona form of cognitive radio. This scenario is formulated as an optimization which requires solution viaan evolutionary algorithm, and convergence is shown to be faster when more antennas are deployed.Finally, an architecture is presented that enables a secondary (i.e., low priority) user, whose terminalscannot directly ”see” each other, to communicate in the presence of multiple primary users.The cost is the need for all the primary users to be modified to collaborate with the secondary user,and for several MIMO relays to be installed. The secondary capacity is maximized under constraintsof transmission power and interference to the primary receivers, and relay selection. This conceptshowcases several communications techniques including eigen-beamforming, channel selection andcapacity optimization.