MIMO transceiver design via majorization theory
Foundations and Trends in Communications and Information Theory
On performance optimization for multi-carrier MIMO ad hoc networks
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
Near optimum power control under fairness constraints in CoMP systems
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Robust MMSE precoding in MIMO channels with pre-fixed receivers
IEEE Transactions on Signal Processing
A Geometric Proof of Calibration
Mathematics of Operations Research
On the computation of the capacity region of the discrete MAC
IEEE Transactions on Communications
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The design of linear transceivers for multiple-input-multiple-output (MIMO) communication systems with channel state information is particularly challenging for two main reasons. First, since several substreams are established through the MIMO channel, it is not even clear how the quality of the system should be measured. Second, once a cost function has been chosen to measure the quality, the optimization of the system according to such criterion is generally difficult due to the nonconvexity of the problem. Recent results have solved the problem for the wide family of Schur-concave/convex functions, resulting in simple closed-form solutions when the system is modeled as a single MIMO channel. However, with several MIMO channels (such as in multi-antenna multicarrier systems), the solution is generally more involved, leading in some cases to the need to employ general-purpose interior-point methods. This problem is specifically addressed in this paper by combining the closed-form solutions for single MIMO channels with a primal decomposition approach, resulting in a simple and efficient method for multiple MIMO channels. The extension to functions that are not Schur-concave/convex is also briefly considered, relating the present work with a recently proposed method to minimize the average bit error rate (BER) of the system.