Radio resource management in wireless communication : beamforming, transmission power control, and rate allocation

OF DOCTORAL DISSERTATION HELSINKI UNIVERSITY OF TECHNOLOGY P.O. BOX 1000, FI-02015 TKK http://www.tkk.fi Author Vesa Hasu Name of the dissertation Radio Resource Management in Wireless Communication: Beamforming, Transmission Power Control, and Rate Allocation Manuscript submitted 11.12.2006 Manuscript revised 18.5.2007 Date of the defence 14.6.2007 Monograph Article dissertation (summary + original articles) Department Automation and Systems Technology Laboratory Control Engineering Laboratory Field of research Control engineering Opponent(s) Prof. Tapani Ristaniemi, D.Sc. (Tech.) Zekeriya Uykan Supervisor Prof. Heikki Koivo Instructor Prof. Heikki Koivo Abstract Effective sharing of the radio spectrum in current and future multi-user radio communication systems is important for the maximisation of communication capacity. Efficient sharing requires obtaining the target ratio between signal and interference powers defined by the requested services for every user with minimum use of resources. In this thesis, three radio resource management techniques – transmission power control, adaptive beamforming, and transmission rate management – are considered separately and jointly in attacking the problem of radio channel sharing. Transmission power control balances the signal-to-interference ratios of the connections, adaptive beamforming performs spatial filtering of signal in antenna arrays, and transmission rate management controls communication speeds of all connections in the system. This thesis proposes an algorithm for block proportional–integral transmission power control. It combines the ideas of updating the transmission powers of different connections in blocks of chosen connections and using a multiple-input, multiple-output proportional–integral controller in the transmission power balancing. The algorithm is compared to the single-input, single-output proportional–integral controller scenario and is seen to offer faster convergence to the optimal transmission powers. Adaptive beamforming weight vector prediction algorithms are introduced for decreasing the negative impact of the beamformer delay on the system performance. The prediction algorithms are based on autoregressive-moving average models, where parameters are updated using recursive least squares technique. This thesis takes practical approaches to joint beamforming and power control. Separate solutions are proposed for the receiving and transmission beamforming systems. Both solutions are based on making SINR estimates according to the covariance matrices of desired signals, which can be applied in transmission power control of corresponding connections. For transmission rate management, the feasibility of applying the power control point of view is taken. Solutions are based on the channel measurements and allocation of rates on the basis of the interference. The approach results in rate allocations that are fairer between users than those obtained via maximisation of communications capacity. In addition to cellular radio systems, this thesis addresses radio resource management of wireless sensor networks. Antenna array beamforming solutions are considered in receivers and transmitters of star-topology sensor networks.