Wireless Communication Systems, Random Beam Formation Of The Key Technologies

Multiuser diversity is an inherent diversity form in wireless communication network. Different users experience different channel fadings. When one experiences a deep fading, others may have good channel quality. Based on this observation, the system performance can be improved by exploiting the multiuser diversity. The multiuser diversity gain is determined by the dynamic range of the fluctuation and is thus limited in the environment with little scattering and/or slow fading. In such environment, the opportunistic beamforming is proposed to induce large and fast channel fluctuations so that multiuser diversity can be still exploited. Besides, the adaptive beamforming requires the full channel state information. In multiuser environment, opportunistic beamforming can be used to achieve beamforming gain and multiuser diversity gain using reduced feedback overhead.In this paper, we firstly review some existing opportunisitc beamforming schemes. They are, respectively, the conventional opportunistic beamforming which employs multiple antennas at the transmitter and serves one user at each slot; the opportunisitc beamforming with multiple beams; the memory-based opportunistic beaforming which exploits the channel memory of slow fading channels; and the opportunisitc MIMO.In IEEE 802.22 wireless regional area network (WRAN), the channel is slow fading and wideband. The users are not uniformly distributed around BS and the number of users is relatively small. To exploit the characteristics of the channel and address these problems, we propose several novel opportunistic beamforming schemes. Firstly, we deal with the problem that users are not uniformly distributed around base station and propose the spatial signature based opportunistic beamforming. Secondly, by exploiting the slow fading and wideband features of wireless channel in WRAN, we propose the wideband memory-based opportunistic beamforming. The proposed scheme has a better throughput performance even when the number of users is small. In addition, the amount of feedback is further reduced by feeding back the central subchannels of each cluster of subchannels. In the end, we theoretically analyze the multiple weight vector opportunistic beamforming problem and obtain three conclusions on designing the weight vectors.In a word, by exploiting the multi-user diversity, opportunistic beamforming can increase the system throughput, reduce the amount of feedback and achieve opportunistic nulling which can reduce the interference between cells.