Distributed interference alignment and power control for wireless MIMO interference networks

Farhadi, Hamed; Wang, Chao; Skoglund, Mikael

doi:10.1109/wcnc.2013.6555053

Cited by 14 publications

(29 citation statements)

References 11 publications

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“…A deterministic power control algorithm for the case in which CSI is perfectly known at terminals, i.e. σ 2 e = 0, has been proposed in [11]. In this paper, we present a stochastic power control algorithm for the case in which only noisy CSI is known at terminals.…”

Section: Distributed Power Controlmentioning

confidence: 99%

“…[6]- [10]) is required to efficiently use available resources and provide the demanded communication quality. An iterative algorithm for power control and interference alignment based on perfect local CSI has been proposed in [11], and its convergence has been shown.…”

Section: Introductionmentioning

confidence: 99%

“…As shown in [11], the function I l k (p) is a standard interference function, thus, the function in (24) satisfy the mean condition.…”

mentioning

confidence: 99%

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Distributed interference alignment and power control for wireless MIMO interference networks with noisy channel state information

Farhadi¹,

Zaidi²,

Fischione³

et al. 2013

2013 First International Black Sea Conference on Communications and Networking (BlackSeaCom)

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Abstract-This paper considers a multi-input multi-output (MIMO) interference network in which each transmitter intends to communicate with its dedicated receiver at a certain fixed rate. It is known that when perfect CSI is available at each terminal, the interference alignment technique can be applied, to align the interference signals at each receivers in a subspace independent of the desired signal subspace. The impact of interference can hence be eliminated. In practice, however, terminals in general can acquire only noisy CSI. Interference alignment cannot be perfectly performed to avoid interference leakage in the signal subspace. Thus, the quality of each communication link depends on the transmission power of the unintended transmitters. To solve this problem, we propose an iterative algorithm to perform stochastic power control and transceiver design based on only noisy local CSI. The transceiver design is conducted based on the interference alignment concept, and the power control seeks solutions of efficiently assigning transmit powers to provide successful communications for all transmitter-receiver pairs.

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Section: Distributed Power Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Distributed interference alignment and power control for wireless MIMO interference networks with noisy channel state information

Farhadi¹,

Zaidi²,

Fischione³

et al. 2013

2013 First International Black Sea Conference on Communications and Networking (BlackSeaCom)

Self Cite

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show abstract

“…Recently, power allocation and control have also been applied to IA to improve its performance [27], [28], [29]. An improved blind IA was proposed in [27], which can increase the SINR by simply changing the power allocation in the transmitted signal.…”

Section: Introductionmentioning

confidence: 99%

“…An improved blind IA was proposed in [27], which can increase the SINR by simply changing the power allocation in the transmitted signal. The authors of [28] proposed a distributed power control algorithm for IA-based wireless networks, in order to guarantee the data transmission at a fixed data rate for each user. A PA scheme was proposed for IA in [29] through using grid search and game theory, and the sum rate of the network can be optimized.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Energy-Efficient Power Allocation in Green Interference-Alignment-Based Wireless Networks

Zhao

Sun

2015

IEEE Trans. Veh. Technol.

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Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract-Interference alignment (IA) is a promising technique for interference management in wireless networks. However, the sum rate may fall short of the theoretical maximum especially at low signal-to-noise ratio (SNR) levels since IA mainly concentrates on mitigating the interference, instead of improving the quality of desired signal. Moreover, most of the previous works focused on improving spectrum efficiency, but the energy efficiency aspect is largely ignored. In this paper, an adaptive energy-efficient IA algorithm is proposed through power allocation and transmission-mode adaptation for green IAbased wireless networks. The power allocation problem for IA is first analyzed, then we propose a power allocation scheme that optimizes the energy efficiency of IA-based wireless networks. When SNR is low, the transmitted power of some users may become zero. Thus the users with low transmitted power are turned into the sleep mode in our scheme to save energy. The transmitted power and transmission mode of the remaining active users are adapted again to further improve the energy efficiency of the network. To guarantee the interests of all the users, fairness among users is also considered in the proposed scheme. Simulation results are presented to show the effectiveness of the proposed algorithm in improving the energy efficiency of IAbased wireless networks.

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Interference alignment in cognitive radio networks

Rezaei

Tadaion

2014

IET Communications

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Distributed interference alignment and power control for wireless MIMO interference networks

Cited by 14 publications

References 11 publications

Distributed interference alignment and power control for wireless MIMO interference networks with noisy channel state information

Distributed interference alignment and power control for wireless MIMO interference networks with noisy channel state information

Adaptive Energy-Efficient Power Allocation in Green Interference-Alignment-Based Wireless Networks

Interference alignment in cognitive radio networks

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