Distributed Multicell Beamforming With Limited Intercell Coordination

Huang, Yongming; Zheng, Gan; Bengtsson, Mats; Wong, Kai-Kit; Yang, Liu; Ottersten, Björn

doi:10.1109/tsp.2010.2089621

Cited by 117 publications

(90 citation statements)

References 23 publications

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“…In DAS, the distributed antennas/nodes are interconnected, via a coaxial cable or optical fibre, to the BS, where the main management and signal processing tasks take place. A related approach is given in MCC systems [2]. The BSs of different cells act themselves as the elements of the MIMO system by exchanging information between them.…”

Section: A Backgroundmentioning

confidence: 99%

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System level simulation and radio resource management for distributed antenna systems with cognitive radio and multi-cell cooperation

Sámano‐Robles¹,

Gameiro

Pereira

2015

2015 Fourth International Conference on Future Generation Communication Technology (FGCT)

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The performance of wireless networks will experience a considerable improvement by the use of novel technologies such as distributed antenna systems (DASs), multi-cell cooperation (MCC), and cognitive radio (CR). These solutions have shown considerable gains at the physical-layer (PHY). However, several issues remain open in the system-level evaluation, radio resource management (RRM), and particularly in the design of billing/licensing schemes for this type of system. This paper proposes a system-level simulator (SLS) that will help in addressing these issues. The paper focuses on the description of the modules of a generic SLS that need a modification to cope with the new transmission/economic paradigms. An advanced RRM solution is proposed for a multi-cell DAS with two levels of cooperation: inside the cell (intra-cell) to coordinate the transmission of distributed nodes within the cell, and between cells (inter-cell or MCC) to adapt cell transmissions according to the collected inter-cell interference measurements. The RRM solution blends network and financial metrics using the theory of multiobjective portfolio optimization. The core of the RRM solution is an iterative weighted least squares (WLS) optimization algorithm that aims to schedule in a fair manner as many terminals as possible across all the radio resources of the available frequency bands (licensed and non-licensed), while considering different economic metrics. The RRM algorithm includes joint terminal scheduling, link adaptation, space division multiplexing, spectrum selection, and resource allocation. Abstract-The performance of wireless networks will experience a considerable improvement by the use of novel technologies such as distributed antenna systems (DASs), multi-cell cooperation (MCC), and cognitive radio (CR). These solutions have shown considerable gains at the physical-layer (PHY). However, several issues remain open in the system-level evaluation, radio resource management (RRM), and particularly in the design of billing/licensing schemes for this type of system. This paper proposes a system-level simulator (SLS) that will help in addressing these issues. The paper focuses on the description of the modules of a generic SLS that need a modification to cope with the new transmission/economic paradigms. An advanced RRM solution is proposed for a multi-cell DAS with two levels of cooperation: inside the cell (intra-cell) to coordinate the transmission of distributed nodes within the cell, and between cells (inter-cell or MCC) to adapt cell transmissions according to the collected inter-cell interference measurements. The RRM solution blends network and financial metrics using the theory of multiobjective portfolio optimization. The core of the RRM solution is an iterative weighted least squares (WLS) optimization algorithm that aims to schedule in a fair manner as many terminals as possible across all the radio resources of the available frequency bands (licensed and non-licensed), while considering different economic metrics....

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Section: A Backgroundmentioning

confidence: 99%

“…The BSs of different cells act themselves as the elements of the MIMO system by exchanging information between them. The performance of MCC is thus limited by the accuracy of the exchanged information [2].…”

Section: A Backgroundmentioning

confidence: 99%

System level simulation and radio resource management for distributed antenna systems with cognitive radio and multi-cell cooperation

Sámano‐Robles¹,

Gameiro

Pereira

2015

2015 Fourth International Conference on Future Generation Communication Technology (FGCT)

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“…More recently, several multi-cell processing methods for the downlink of terrestrial systems were devised in [5][6][7]. In particular, assuming data sharing, the authors in [5] studied the design of transmit beamforming by recasting the downlink beamforming problem into a least minimum mean-square-error estimation (MMSE) problem.…”

Section: Transmitter Architectures: Mimo Bcmentioning

confidence: 99%

Linear and nonlinear techniques for multibeam joint processing in satellite communications

Christopoulos

Chatzinotas

Zheng

et al. 2012

J Wireless Com Network

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Existing satellite communication standards such as DVB-S2, operate under highly-efficient adaptive coding and modulation schemes thus making significant progress in improving the spectral efficiencies of digital satellite broadcast systems. However, the constantly increasing demand for broadband and interactive satellite links emanates the need to apply novel interference mitigation techniques, striving towards Terabit throughput. In this direction, the objective of the present contribution is to investigate joint multiuser processing techniques for multibeam satellite systems. In the forward link, the performance of linear precoding is investigated with optimal nonlinear precoding (i.e., dirty article coding) acting as the upper performance limit. To this end, the resulting power and precoder design problems are approached through optimization methods. Similarly, in the return link the concept of linear filtering (i.e., linear minimum mean square error) is studied with the optimal successive interference cancelation acting as the performance limit. The derived capacity curves for both scenarios are compared to conventional satellite systems where beams are processed independently and interbeam interference is mitigated through a four color frequency reuse scheme, in order to quantify the potential gain of the proposed techniques.

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“…Coordinated or cooperative beamforming, where multiantenna reprocessing at neighboring base stations (BSs) are designed cooperatively, has been extensively studied in the existing literatures such as [3][4][5][6][7][8][9] and thereof. To be more specific, the transmit power minimization problem subject to signal-to-interference-and-noise-ratio (SINR) constraints at the remote users was addressed based on *Correspondence: huangym@seu.edu.cn 1 School of Information Science and Engineering, Southeast University, Nanjing 210096, China Full list of author information is available at the end of the article the uplink-downlink duality theorem for multicell multiuser downlink systems [3].…”

Section: Introductionmentioning

confidence: 99%

“…To be more specific, the transmit power minimization problem subject to signal-to-interference-and-noise-ratio (SINR) constraints at the remote users was addressed based on *Correspondence: huangym@seu.edu.cn 1 School of Information Science and Engineering, Southeast University, Nanjing 210096, China Full list of author information is available at the end of the article the uplink-downlink duality theorem for multicell multiuser downlink systems [3]. To maximize the minimum user rate, we proposed an efficient iterative algorithm to optimize the downlink beamforming and power allocation in time-division-duplex systems [4], which only requires limited signaling exchange between BSs. Unlike the aforementioned references where a coordinated beamforming algorithm was designed assuming a fixed coordinated BS cluster, in [5], the authors investigated a novel multicell coordinated beamforming framework with dynamic cooperation clusters where each user is jointly served by a small set of BSs.…”

Section: Introductionmentioning

confidence: 99%

Coordinated beamforming design for multicell systems with transceiver impairments: from perspective of spectral efficiency to energy efficiency

Huang

Zhang

et al. 2015

J Wireless Com Network

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Physical transceiver implementations for wireless communication systems usually suffer from transmit-radio frequency (Tx-RF) and receiver-RF (Rx-RF) impairments. In this paper, we aim to design efficient coordinated beamforming for multicell multiuser multi-antenna systems by fully taking into account the residual transceiver impairments. Our design objectives include both spectral efficiency and energy efficiency. In particular, we first derive the closed-form expression of the mean square error (MSE) which includes the impact of transceiver impairments. Based on that, we propose an alternating optimization algorithm to solve the coordinated multicell beamforming problems with the goal of minimizing the worst user MSE, and the sum MSE. Then, by exploiting the relationship between the minimum mean square error (MMSE) and the achievable rate, we develop a new algorithm to address the sum rate maximization problem. This approach is further generalized to solve the more intractable energy efficiency optimization problem. We prove that all the proposed iterative algorithms guarantee to converge to a stationary point. Numerical results show that our proposed schemes achieve a better performance than conventional coordinated beamforming algorithms that were designed ignoring the transceiver impairments.

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Distributed Multicell Beamforming With Limited Intercell Coordination

Cited by 117 publications

References 23 publications

System level simulation and radio resource management for distributed antenna systems with cognitive radio and multi-cell cooperation

System level simulation and radio resource management for distributed antenna systems with cognitive radio and multi-cell cooperation

Linear and nonlinear techniques for multibeam joint processing in satellite communications

Coordinated beamforming design for multicell systems with transceiver impairments: from perspective of spectral efficiency to energy efficiency

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