Competition Versus Cooperation on the MISO Interference Channel

By Erik G. Larsson, Eduard Axel Jorswieck. IEEE Journal on Selected Areas in Communications, 2008

321 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Multi-Cell MIMO Cooperative Networks: A New Look at Interference (2010, unknown): “altruistic points of view [109], [93], [110].”
Cooperative Multicell Precoding: Rate Region Characterization and Distributed Strategies With Instantaneous and Statistical CSI (2010, unknown): “Unlike the MISO IC [13]–[17], we assume that the data symbols intended for all receivers are available at all transmitters.”
An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel (2011, methodology): “2: Average sum-rate Vs. SNR in the MIMO IFC case.”
Game Theory in Wireless and Communication Networks (2008, methodology): “In fact, the Nash bargaining solution outperforms theNash equilibrium in any given scenario, and, in some cases of thismodel, this solution is as good as the sum-ratemaximizing centralized solution, as shown through extensive numerical simulations in [281].”
Complete Characterization of the Pareto Boundary for the MISO Interference Channel (2008, methodology): “For example, the choice for all (i.e., all users do pure MRT) was shown in [ 12 ] to be far from the boundary for high SNR.”
Convex Optimization in Signal Processing and Communications (2009, background): “Extension of the basic problem to ad-hoc frequencyselective and MIMO networks were given in [6, 7, 8, 9, 21] and [10, 22, 23, 24], respectively.”