This paper deals with the problem of channel tracking for RAKE receivers in propagation environments characterized by closely spaced multipath components. After outlining why conventional single-path channel tracking algorithms fail in such scenarios, several new estimation algorithms are developed that are tailored to channels with closely spaced multipaths. This is achieved by removing or minimizing self-interference caused by multipath components. Other interfering users are treated as noise. Both timing tracking and phasor tracking and their interaction are covered in this paper. The derived algorithms are benchmarked against perfect channel knowledge on one hand and conventional tracking algorithms on the other hand, both in a UMTS test scenario. In moderate scenarios, the use of these new algorithms leads to performance improvements of up to 2 dB, in terms of signal-to-noise ratio (SNR) at moderate bit error rates, and even manages to track the channel in conditions where conventional tracking algorithms fail completely.

We examine the throughput of an opportunistic beamforming system with proportional fair scheduling and show for normally distributed channel fading states that for large numbers of users the average throughput of each user multiplied by the number of users approaches the maximum possible throughput of this user achievable by coherent beamforming, if round robin scheduling was used. Thus, we extend a proof by Viswanath et al. who showed this for discrete fading states. We give the average SNR of the scheduled user (averaged across the fading states) in closed form and the average throughput in form of an integral as a function of the number of transmit antennas and users. Simulations of this system confirm the analytical results. Finally, we show that for a large number of transmit antennas, the probability density function of the SNR of the scheduled user and therefore also the throughput asymptotically approach those of a system with a max SNR scheduler that always transmits to the user having the largest SNR and thus maximizes the total throughput.

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