Optimal resource allocation for MIMO ad hoc cognitive radio networks
Seung-Jun Kim,Georgios B. Giannakis +1 more
- Vol. 57, Iss: 5, pp 3117-3131
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TLDR
The stand-alone weighted sum-rate optimal schemes proposed here have merits over interference-alignment alternatives especially for practical SNR values.The novel approach is flexible to accommodate modifications aiming at interference alignment.Abstract:
Maximization of the weighted sum-rate of secondary users (SUs) possibly equipped with multiantenna transmitters and receivers is considered in the context of cognitive radio (CR) networks with coexisting primary users (PUs). The total interference power received at the primary receiver is constrained to maintain reliable communication for the PU. An interference channel configuration is considered for ad hoc networking, where the receivers treat the interference from undesired transmitters as noise. Without the CR constraint, a convergent distributed algorithm is developed to obtain (at least) a locally optimal solution. With the CR constraint, a semidistributed algorithm is introduced. An alternative centralized algorithm based on geometric programming and network duality is also developed. Numerical results show the efficacy of the proposed algorithms. The novel approach is flexible to accommodate modifications aiming at interference alignment. However, the stand-alone weighted sum-rate optimal schemes proposed here have merits over interference-alignment alternatives especially for practical SNR values.read more
Citations
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An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel
TL;DR: This paper proposes a linear transceiver design algorithm for weighted sum-rate maximization that is based on iterative minimization of weighted mean squared error (MSE) and extends the algorithm to a general class of utility functions and establishes its convergence.
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An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel
TL;DR: A linear transceiver design algorithm for weighted sum-rate maximization that is based on iterative minimization of weighted mean-square error (MSE) and can be extended to a general class of sum-utility maximization problem.
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A unified convergence analysis of block successive minimization methods for nonsmooth optimization
TL;DR: This paper studies an alternative inexact BCD approach which updates the variable blocks by successively minimizing a sequence of approximations of f which are either locally tight upper bounds of $f$ or strictly convex local approximation of f.
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TL;DR: In this article, an alternative inexact block coordinate descent (BCD) approach is proposed, which updates the variable blocks by successively minimizing a sequence of approximations of f which are either locally tight upper bounds of f or strictly convex local approximates of f. The convergence properties for a fairly wide class of such methods, especially for the cases where the objective functions are either non-differentiable or nonconvex.
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Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs
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