COOPERATION, COMPETITION AND COGNITION IN WIRELESS NETWORKS From Theory to Implementation

Nodes and/or clusters of a wireless network operating on the same frequency can operate using three different paradigms: 1) Competition: Traditionally, this is information theoretically casted in the framework of interference channels. 2) Cooperation: Silent transmitters/receivers can help active transmitters/receivers in the transmission/reception of their messages, but have to extract this message from the underlying transmission or by other methods, and 3) Cognitive Radio Transmission: Some devices extract the message(s) of other transmitter(s) from their signals or by other methods, and use it to minimize interference from/to their own transmitted signals. Competition has been well-studied in the literature. Cooperation has been less studied and cognitive radio transmission has not been studied much. For the cooperative case, we demonstrate that most of the multiple-input multiple-output (MIMO) space-time diversity gain can also be achieved through cooperative communications with single-antenna/multiple-antenna nodes when there is one receiving agent. In particular, for the single antenna case, we consider communication to take place between clusters of nearby nodes. We show the existence of cooperative codes for communications for which the intra-cluster negotiation penalty is in principle small and almost all the diversity gain of traditional space-time codes may be realized. For example, for a single transmitter node with two cooperators and one receiver node, if the cooperators have as little as 10 dB path loss advantage over the receiver, the penalty for cooperation over traditional space-time systems is negligible. Furthermore, we demonstrate and discuss the implementation of this idea in an orthogonal frequency division multiplexing (OFDM) system using a software defined ratio (SDR) platform. On the other hand, cooperative beamforming is an alternative way of realizing cooperative gain, particularly for a wireless sensor network. We analyze the statistical average properties and distribution of the beampattern of cooperative beamforming using the theory of random arrays. For cognitive radio transmissions, which captures a form of asymmetric cooperation, we define a generalized cognitive radio channel as an n-transmitter, mreceiver interference channel in which sender i obtains (causally or non-causally) the messages of senders 1 through i− 1. For simplicity, only the two sender, two receiver case is considered. In this scenario, one user, a cognitive radio, obtains (genie assisted, or causally) knowledge of the data to be transmitted by the other user. The cognitive radio may then simultaneously transmit over the same channel, as opposed to waiting for an idle channel as in a traditional cognitive radio channel protocol. Gel’fand-Pinsker coding (and the special case of dirtypaper coding) and ideas from achievable region constructions for the interference channel are used, and an achievable region for the cognitive radio channel is computed. In the Gaussian case, the described achievable region is compared to the upper bound provided by the 2 × 2 Gaussian MIMO broadcast channel, and an interference-free channel. We then extend the results to provide an achievable region for cognitive multiple access networks.