Author:

Keywords:

MISO/ MIMO, Beamforming, Synchronization, CFO

Abstract:

Mobile communications face a capacity crunch. To meet this explosive demand for high capacity, future wireless communication systems must increase the spatial reuse factor to maximize the use of the available bandwidth and reduce the distance between the transmitter and receiver. However, a high spatial reuse factor in dense networks generates a large amount of interference that degrades the per-user capacity, especially for users at cell-edge. To cope with this limitation, intelligent cooperation, or network beamforming, in which multiple cells cooperate to transmit simultaneously towards one or multiple receivers is considered. Such techniques create a virtual giant MIMO transmitter to provide the gain of multi-antenna systems and mitigate the co-channel interference. Theoretical works show that node cooperation ensures constant per-node capacity while increasing the network sum-capacity. Moreover, recent field trial results demonstrated considerable performance improvement in exploiting cooperation in cellular systems compared to conventional schemes. In addition, cooperation can be enabled at a low cost, i.e., no need for new infrastructures or expensive devices. Because cooperation promises huge gains, it is foreseen as a key means to meet the capacity targeted by emerging wireless communication standards. However, such cooperation is difficult to implement in distributed systems. First, it requires the joint computation of the beamforming weights and the sharing of symbol and channel state information across the transmit cells. Second, the transmit data must arrive time and frequency synchronized at the receiver(s) and hence require the tight synchronization of the multiple transmitters. Finally, high spatial reuse factor is challenging to obtain in distributed systems, e.g. wireless mesh networks, due to carrier sensing mechanism of the medium access control protocol. We first develop network beamforming schemes for the interference channel that are simpler to implement than network cooperative schemes. We propose two network beamformers for the single-carrier MISO interference channel that exploit only a limited knowledge of the data and channel information at each cell to locally compute the beamforming weights. Next, in the second part we study the impact of front-end non-idealities on coordinated and cooperative network beamforming. We identify carrier frequency offset as the major source of errors and study its impact on the performance of the coordinated zero forcing and the equal-gain combining beamforming schemes. We propose the derivations of the signal-to-noise ratio gain and the diversity order when a carrier frequency offset is present. In the last part, we address the problem of co-channel interference in wireless mesh networks. We show how beamforming techniques can be implemented on top of the IEEE 802.11s medium access control protocol and cancel the interference to mitigate the inefficiency of carrier sense mechanism and improve the spatial-reuse gain. In addition, we show that a beamformer proposed in Chapter 2 significantly improves the spatial-reuse gain compared to the zero-forcing and the basic IEEE 802.11s access scheme.