Multiuser diversity is a form of diversity inherent in a wireless network, provided by independent time-varying channels across the different users. The diversity benefit is exploited by tracking the channel fluctuations of the users and scheduling transmissions to users when their instantaneous channel quality is near the peak. The diversity gain increases with the dynamic range of the fluctuations and is thus limited in environments with little scattering and/or slow fading. In such environments, we propose the use of multiple transmit antennas to induce large and fast channel fluctuations so that multiuser diversity can still be exploited. The scheme can be interpreted as opportunistic beamforming and we show that true beamforming gains can be achieved when there are sufficient users, even though very limited channel feedback is needed. Furthermore, in a cellular system, the scheme plays an additional role of opportunistic nulling of the interference created on users of adjacent cells. We discuss the design implications of implementing this scheme in a complete wireless system.

MIMO communication links, i.e. those with multiple transmit and receive antennas, offer significant advantages in terms of rate and reliability. In cellular systems, however, gains may be limited due to fading and interference. One potential solution is known as multiuser diveristy, in which a packet scheduler improves throughput by exploiting the independence of the fading and interference statistics of different users. In this paper, we consider the problem of exploiting multiuser diversity in M1MO systems, especially those with zero-forcing linear receivers. We propose a number of different scheduling disciplines and compare them in terms of average throughput as a function of the number of users and number of antennas.

In wireless fading channels, multiuser diversity can be exploited by scheduling users so that they transmit when their channel conditions are favorable. This leads to a sum throughput that increases with the number of users and, in certain cases, achieves capacity. However, such scheduling requires global knowledge of every user’s channel gain, which may be difficult to obtain in some situations. This paper addresses contention-based protocols for exploiting multiuser diversity with only local channel knowledge. A variation of the classic ALOHA protocol is given in which users attempt to exploit multi-user diversity gains, but suffer contention losses due to the distributed channel knowledge. We characterize the growth rate of the sum throughput for this protocol in a backlogged system under both short-term and long-term average power constraints. A simple “fixed-rate ” system is shown to be asymptotically optimal and to achieve the same growth rate as in a system with a centralized scheduler. Moreover, asymptotically, the fraction of throughput lost due to contention is shown to be 1/e. Also, in a system with random arrivals and an infinite user population, a variation of this ALOHA protocol is shown to be stable for any total arrival rate, given that users can estimate the backlog. I.

In this chapter, we will study how the variation in the sources and channels can be exploited to improve the power and spectral efficiency of wireless networks. A typical multi-hop wireless network is displayed in Figure 1.1, with an inside look into a typical node. At any node, there can be multiple sources with multiple queues, either based on the data generated at the node (a user web-surfing) or generated at other nodes (forwarding traffic in a multi-hop network like ad hoc, sensor or mesh network). Most sources produce information in timevarying bursts. This is clearly evident in multimedia sources like voice, music and video, which when compressed yield a time-varying amount of information. Voice conversations have periods of silence and speech interspersed, clearly de-marking periods of high informa-