MIMO B-MAC Interference Network Optimization Under Rate Constraints by Polite Water-Filling and Duality

Liu, An; Liu, Youjian; Xiang, Haige; Luo, Wu

doi:10.1109/tsp.2010.2088394

Cited by 21 publications

(32 citation statements)

References 35 publications

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“…We consider a general interference network named MIMO B-MAC network with multiple transmitters and receivers [2], [16]. A transmitter in the MIMO B-MAC network may send independent data to different receivers, like in BC, and a receiver may receive independent data from different transmitters, like in MAC.…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

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A new algorithm for the weighted sum rate maximization in MIMO interference networks

Xing

You

Chen

et al. 2015

2015 IEEE Wireless Communications and Networking Conference (WCNC)

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MIMO interference network optimization is important for increasingly crowded wireless communication networks. This paper presents a new algorithm, named Dual Link Algorithm, for weighted sum-rate maximization where the interference is efficiently managed. We consider general MIMO interference channels with Gaussian input and a total power constraint. Two of the previous state-of-the-art algorithms are the WMMSE algorithm and the polite water-filling (PWF) algorithm. The WMMSE algorithm is provably convergent, while the PWF algorithm takes the advantage of the optimal transmit signal structure and converges the fastest in most situations but is not guaranteed to converge in all situations. Therefore, it is highly desirable to design an algorithm that has the advantages of both algorithms. The proposed dual link algorithm is such an algorithm. Its fast and guaranteed convergence is important to distributed implementation and time varying channels. In addition, the technique and a scaling invariance property used in the convergence proof may find applications in other non-convex problems in communication networks.

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Section: System Model and Problem Formulationmentioning

confidence: 99%

“…It is well known that equality L l=1 Tr (Σ l ) = P T holds when Σ 1:L is a stationary point of problem (4), e.g., [16,Theorem 8 (item 3)]. This indicates that the full power should always be used.…”

Section: A a Review Of The Polite Water-filling Structurementioning

confidence: 99%

A new algorithm for the weighted sum rate maximization in MIMO interference networks

Xing

You

Chen

et al. 2015

2015 IEEE Wireless Communications and Networking Conference (WCNC)

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“…This demonstrates the advantage of the proposed MDS-coded random cache data structure. As the BS cache size 5 If the distance between a user and its serving BS is less than 80 m, even the path gain of the strongest cross link is about 28 dB smaller than the path gain of the direct link. Such users are essentially free from the inter-cell interference and we have excluded this uninteresting degenerate case in the simulations.…”

Section: Baseline 3: (Algorithm Sp With Uniform Caching)mentioning

confidence: 99%

Mixed-Timescale Precoding and Cache Control in Cached MIMO Interference Network

Liu

Lau

2013

IEEE Trans. Signal Process.

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103

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Consider media streaming in MIMO interference networks whereby multiple base stations (BS) simultaneously deliver media to their associated users using fixed data rates. The performance is fundamentally limited by the cross-link interference. We propose a cache-induced opportunistic cooperative MIMO (CoMP) for interference mitigation. By caching a portion of the media files, the BSs opportunistically employ CoMP to transform the cross-link interference into spatial multiplexing gain. We study a mixed-timescale optimization of MIMO precoding and cache control to minimize the transmit power under the rate constraint. The cache control is to create more CoMP opportunities and is adaptive to the long-term popularity of the media files. The precoding is to guarantee the rate requirement and is adaptive to the channel state information and cache state at the BSs. The joint stochastic optimization problem is decomposed into a short-term precoding and a long-term cache control problem. We propose a precoding algorithm which converges to a stationary point of the short-term problem. Based on this, we exploit the hidden convexity of the long-term problem and propose a low complexity and robust solution using stochastic subgradient. The solution has significant gains over various baselines and does not require explicit knowledge of the media popularity.

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“…For instance, a game theoretical approach was investigated in [9], [10] to maximize the sum rate. On the other hand, alternating algorithms for power minimization were developped in [11], [12] by using the SINR duality or reciprocity concept. Since this later only works with a sum power constraint, it is not suitable for distributed MIMO networks such as multihop networks.…”

Section: Introductionmentioning

confidence: 99%

Distributed Optimization of Transceiver Weights in MIMO Two-Way Multihop Networks

Ramamonjison

Tran

Sakaguchi

et al. 2012

2012 IEEE 75th Vehicular Technology Conference (VTC Spring)

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We investigate the joint optimization of power allocation and transceiver weights in multiple-input multipleoutput (MIMO) two-way multihop networks. The objective is to maximize the minimum weighted signal-to-interference-plus noise power ratio (SINR) of the multihop links while satisfying general linear power constraints at the transmit nodes. First, we derive a distributed power allocation algorithm by extending the notion of link SINR metric and analyze its convergence and optimality. Using that result, we propose an alternating optimization algorithm for solving the more complex MIMO transceiver weight optimization. We compare its performance against those of centralized and conventional schemes through numerical simulations. Our results show that the proposed algorithm provides considerable improvement to the end-toend rate of multihop networks. In fact, it achieves, with low complexity and low coordination overhead, a rate performance close to an upper-bound that was obtained from a centralized optimization with a relaxed power constraint.

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MIMO B-MAC Interference Network Optimization Under Rate Constraints by Polite Water-Filling and Duality

Cited by 21 publications

References 35 publications

A new algorithm for the weighted sum rate maximization in MIMO interference networks

A new algorithm for the weighted sum rate maximization in MIMO interference networks

Mixed-Timescale Precoding and Cache Control in Cached MIMO Interference Network

Distributed Optimization of Transceiver Weights in MIMO Two-Way Multihop Networks

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