No abstract

Accurate and fast algorithms for the local mean signal level estimation are very important for the successful implementation of many wireless communication enabling techniques such as handoff, power control, and adaptive gain control schemes. In this paper, we present on-line simple-to-implement (i) minimum variance unbiased and (ii) maximum likelihood estimators for the local mean signal power estimation in the decibel domain. We consider a generalized Nakagami-m fading environment and show that these estimators are asymptotically efficient in the number of samples and in the fading parameter m. Numerical and simulation results confirm that these estimators outperform the sample mean estimator and quickly approach the Cramer-Rao lower bounds.

This paper considers an uplink multiuser hybrid beamforming system where a base station (BS) communicates with multiple users simultaneously. The performance of the uplink multiuser hybrid beamforming system depends on the effective channel which is given by the product of channel matrix and the analog beams. Therefore, to maximize the performance, we need to acquire information of the channels and select the appropriate analog beams from the set of predefined analog beams. In this paper, we propose the channel estimation methods and analog beam selection algorithm for the uplink multiuser hybrid beamforming system. First, we design the estimation methods to exploit the channel information of the users by considering Rayleigh fading and millimeter wave (mmWave) channel models. Then, using the estimated channel information, we propose a low-complexity analog beam selection algorithm for the uplink multiuser hybrid beamforming system. We compare the complexity to show that the proposed analog beam selection algorithm has much less complexity than the exhaustive search-based optimum analog beam selection while the performance loss of the proposed analog beam selection algorithm is not significant compared to the optimum analog beam selection, which is shown by the numerical results.

No abstract

No abstract