Journal ArticleDOI
Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization
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TLDR
This paper addresses the joint design of transmit and receive beamforming or linear processing for multicarrier multiple-input multiple-output (MIMO) channels under a variety of design criteria by developing a unified framework based on considering two families of objective functions that embrace most reasonable criteria to design a communication system.Abstract:
This paper addresses the joint design of transmit and receive beamforming or linear processing (commonly termed linear precoding at the transmitter and equalization at the receiver) for multicarrier multiple-input multiple-output (MIMO) channels under a variety of design criteria. Instead of considering each design criterion in a separate way, we generalize the existing results by developing a unified framework based on considering two families of objective functions that embrace most reasonable criteria to design a communication system: Schur-concave and Schur-convex functions. Once the optimal structure of the transmit-receive processing is known, the design problem simplifies and can be formulated within the powerful framework of convex optimization theory, in which a great number of interesting design criteria can be easily accommodated and efficiently solved, even though closed-form expressions may not exist. From this perspective, we analyze a variety of design criteria, and in particular, we derive optimal beamvectors in the sense of having minimum average bit error rate (BER). Additional constraints on the peak-to-average ratio (PAR) or on the signal dynamic range are easily included in the design. We propose two multilevel water-filling practical solutions that perform very close to the optimal in terms of average BER with a low implementation complexity. If cooperation among the processing operating at different carriers is allowed, the performance improves significantly. Interestingly, with carrier cooperation, it turns out that the exact optimal solution in terms of average BER can be obtained in closed form.read more
Citations
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Journal ArticleDOI
Spatially Sparse Precoding in Millimeter Wave MIMO Systems
TL;DR: This paper considers transmit precoding and receiver combining in mmWave systems with large antenna arrays and develops algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware.
Journal ArticleDOI
A tutorial on geometric programming
TL;DR: This tutorial paper collects together in one place the basic background material needed to do GP modeling, and shows how to recognize functions and problems compatible with GP, and how to approximate functions or data in a formcompatible with GP.
Journal ArticleDOI
Hybrid Digital and Analog Beamforming Design for Large-Scale Antenna Arrays
Foad Sohrabi,Wei Yu +1 more
TL;DR: This paper establishes that if the number of RF chains is twice the total number of data streams, the hybrid beamforming structure can realize any fully digital beamformer exactly, regardless of the numberOf antenna elements, and shows that such an architecture can approach the performance of a fully digital scheme with much fewer number ofRF chains.
Journal ArticleDOI
Linear precoding via conic optimization for fixed MIMO receivers
TL;DR: The proposed precoder design is general, and as a special case, it solves the transmit rank-one beamforming problem and can significantly outperform existing linear precoders.
References
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Book
Elements of information theory
Thomas M. Cover,Joy A. Thomas +1 more
TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Book
Matrix Analysis
Roger A. Horn,Charles R. Johnson +1 more
TL;DR: In this article, the authors present results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrate their importance in a variety of applications, such as linear algebra and matrix theory.
Journal ArticleDOI
Fundamentals of statistical signal processing: estimation theory
TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
Journal ArticleDOI
Capacity of Multi‐antenna Gaussian Channels
TL;DR: In this paper, the authors investigate the use of multiple transmitting and/or receiving antennas for single user communications over the additive Gaussian channel with and without fading, and derive formulas for the capacities and error exponents of such channels, and describe computational procedures to evaluate such formulas.