Transmit diversity generally requires more than one antenna at the transmitter. However, many wireless devices are limited by size or hardware complexity to one antenna. Recently, a new class of methods called cooperative communication has been proposed that enables single-antenna mobiles in a multi-user environment to share their antennas and generate a virtual multiple-antenna transmitter that allows them to achieve transmit diversity. This article presents an overview of the developments in this burgeoning field.

Multiple-antenna systems, also known as multiple-input multiple-output radio, can improve the capacity and reliability of radio communication. However, the multiple RF chains associated with multiple antennas are costly in terms of size, power, and hardware. Antenna selection is a low-cost low-complexity alternative to capture many of the advantages of MIMO systems. This article reviews classic results on selection diversity, followed by a discussion of antenna selection algorithms at the transmit and receive sides. Extensions of classical results to antenna subset selection are presented. Finally, several open problems in this area are pointed out.

When mobiles cannot support multiple antennas due to size or other constraints, conventional space-time coding cannot be used to provide uplink transmit diversity. To address this limitation, the concept of cooperation diversity has been introduced, where mobiles achieve uplink transmit diversity by relaying each other's messages. A particularly powerful variation of this principle is coded cooperation. Instead of a simple repetition relay, coded cooperation partitions the codewords of each mobile and transmits portions of each codeword through independent fading channels. This paper presents two extensions to the coded cooperation framework. First, we increase the diversity of coded cooperation in the fast-fading scenario via ideas borrowed from space-time codes. We calculate bounds for the bit- and block-error rates to demonstrate the resulting gains. Second, since cooperative coding contains two code components, it is natural to apply turbo codes to this framework. We investigate the application of turbo codes in coded cooperation and demonstrate the resulting gains via error bounds and simulations.

Cooperative communication is an emerging paradigm where multiple mobiles share their resources (bandwidth and power) to achieve better overall performance. Coded cooperation is a mechanism where cooperation is combined with-and operates through-channel coding, as opposed to the repetition-based methods. This work develops expressions for outage probability of coded cooperation. In this work, each node acts as both a data source as well as a relay, i.e., only active (transmitting) nodes are available to assist other nodes, and each node operates under overall (source + relay) power and bandwidth constraints. Outage expressions confirm that full diversity is achieved by coded cooperation. This shows that despite superficial similarities, coded cooperation is distinct from decode-and-forward, which has been shown to have diversity one. The outage probability expressions developed in this work characterize coded performance at various rates. Furthermore, outage probabilities yield bounds that are arguably more insightful than the bit-error rate (BER) results previously available for coded cooperation. Numerical comparisons shed light on the relative merits of coded cooperation and various repetition-based methods, under various inter-user and uplink channel conditions.

Various results to date have demonstrated the advantages of one or several relay nodes assisting transmissions in a wireless network. In many practical scenarios, not all nodes in the network are simultaneously involved in every transmission; therefore, protocols are needed to form groups or subsets of nodes for the purposes of cooperation. We consider this problem in the context of regenerative nodes and non-altruistic cooperation (all nodes have data of their own to transmit). For a network-wide diversity advantage, the protocol must provide each transmitting node with enough "partners" that can decode its message with high-enough probability. Assuming that the nodes cannot communicate their control decisions (distributed scenario), and that each node chooses to help n other nodes, we point out a simple, static selection strategy that guarantees diversity n+1 for all transmissions. We then consider centralized control strategies and study the additional gains that arise from a central control, under various amounts of information being available to the central controller.