Networked MIMO with clustered linear precoding

Zhang, Jun; Chen, Runhua; Andrews, J.G.; Ghosh, Arunabha; Heath, Robert W.

doi:10.1109/twc.2009.080180

Cited by 499 publications

(407 citation statements)

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“…The topics include from capacity [6,7], joint processing [8][9][10], location optimization [11] to those considering the practical imperfect conditions such as backhaul constraints [12] and asynchronous interference [13].…”

Section: Related Studymentioning

confidence: 99%

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Joint resource allocations for remote radio head deployments with coherent transmitter

Wang

Shi

et al. 2012

J Wireless Com Network

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To deal with the future high demands of wireless traffic and energy consumption, one type of heterogeneous deployments is to distribute the base station antennas throughout the entire cell, which is called remote radio head (RRH). In view of radio resource management, the joint resource allocation in broadband orthogonal frequency division multiple access RRH (OFDMA-RRH) has not been thoroughly studied, which includes the antenna port selection, subcarrier assignment and power allocation under the power constraints per antenna port. This article focuses on the downlink resource allocation in OFDMA-RRH, where the coherent transmitter with phase steering is used. The problem to maximize the system spectrum efficiency (SE) is formulated, and solved by a dual decomposition method, where the decomposed sub-problems in the dual domain are solved by analytic geometry. In the optimal solution, the system power is always exhaustively used. As another contribution, this article further proposes that in the optimal solution, there is a considerable part of system power which makes little contribution to the SE and thus should be saved. Specifically, the energy efficiency is analyzed for an individual subcarrier transmission. A proportional power allocation (PPA) method is proposed to achieve a local optimality for each subcarrier. By applying the PPA to every subcarrier in order to maximize the system SE, a new resource allocation problem is formulated and solved. Discussions are also presented for the proposed algorithms on the computational complexity and feasibility in multi-cell cases. Simulation results show that the optimal algorithm consumes all the system power and has good convergence. The algorithm applying PPA can effectively improves the system power efficiency while achieving the SE optimality.

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Section: Related Studymentioning

confidence: 99%

“…Many insightful researches focus on the optimal PA for single-band multi-user downlink transmission with PCPP [9,10,14,15], where OFDMA is not considered. In [16], the joint problem is decomposed into two sub-problems: antenna-level and user-level scheduling.…”

Section: Related Studymentioning

confidence: 99%

Joint resource allocations for remote radio head deployments with coherent transmitter

Wang

Shi

et al. 2012

J Wireless Com Network

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“…The system is typically divided into clusters of cells, and the joint transmission is implemented within the cells included in each cluster. The cluster formation can be static [10][11][12][13][14], or dynamic [15][16][17]. The static cluster formation specifies a predefined set of clusters of cells which do not change in time, whereas the dynamic clustering approaches form the clusters based on the varying channel conditions that users experience to different cells.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, research has shifted towards the limited coordination case with different cluster formation models, that is, resource allocation with dynamic clustering [24,25] or resource allocation with static clustering [14]. In [24], an inter-cluster interference canceler performing linear processing on the downlink transmission signals is proposed for multi-user MIMO distributed antenna systems.…”

Section: Introductionmentioning

confidence: 99%

“…For a system with a large number of cells and a large number of users, a high computational burden will be caused in the CU. In [14], the authors instead consider a more realistic system model, where the network is divided into a number of disjoint static clusters, and limited inter-cluster coordination is used to pre-cancel interference for the users at the edge of neighboring clusters. In this approach, perfect CSI is available at the cluster side for both the cluster users and edge users in the neighboring clusters.…”

Section: Introductionmentioning

confidence: 99%

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Resource allocation for clustered network MIMO OFDMA systems

Botella

Svensson

2012

J Wireless Com Network

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In this article, we address the resource allocation problem for the downlink of a large network multiple input multiple output orthogonal frequency division multiplexing system with 3-sector base stations. The system is statically divided into a number of disjoint clusters of sectors. A two-step resource allocation scheme is proposed involving the inter-cluster and the intra-cluster levels. As a first step or inter-cluster level, two cooperative frequency reuse approaches are designed to mitigate the inter-cluster interference. A user partition method is proposed to divide the users of each cluster into cluster-edge and cluster-center users. To balance the cell-edge and the cellaverage performance, a fairness jug function is introduced to determine the frequency partition of the cooperative frequency reuse approaches. Then, as a second step or intra-cluster level, a utility-based joint scheduling and power allocation algorithm is proposed for each cluster, to maximize the sum utility of all users in the cluster under per-sector power constraints. Zero-forcing joint transmission is used across multiple sectors within the same cluster. Simulation results show that the proposed scheme can efficiently reduce the inter-cluster interference and provide considerable performance improvement in terms of both the cell-edge and cell-average user data rate. The proposed two-step resource allocation scheme can be implemented independently in each cluster without inter-cluster information exchange, which is an attractive property for practical systems, since it reduces both the network signaling overhead and the computational complexity.

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Cooperative Communications

2015

Wireless Communications

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The motivation of this article is to clarify and help resolve the gap between the link abstraction used in traditional wireless networking and its much broader definition used in the context of cooperative communications, which has received significant interest as an untapped means for improving performance of relay transmission systems operating over the ever-challenging wireless medium. The common theme of most research in this area is to optimize physical layer performance measures without considering in much detail how cooperation interacts with higher layers and improves network performance measures. Because these issues are important for enabling cooperative communications to practice in real-world networks, especially for the increasingly important class of mobile ad hoc networks (MANETs), the goals of this article are to survey basic cooperative communications and outline two potential architectures for cooperative MANETs. The first architecture relies on an existing clustered infrastructure: cooperative relays are centrally controlled by cluster heads. In another architecture without explicit clustering, cooperative links are formed by request of a source node in an ad hoc, decentralized fashion. In either case, cooperative communication considerably improves the network connectivity. Although far from a complete study, these architectures provide modified wireless link abstractions and suggest tradeoffs in complexity at the physical and higher layers. Many opportunities and challenges remain, including distributed synchronization, coding, and signal processing among multiple radios; modeling of new link abstractions at higher layers; and multiaccess and routing protocols for networks of cooperative links. Cooperative Communications in Mobile Ad Hoc Networks[ Rethinking the link abstraction ]

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Networked MIMO with clustered linear precoding

Cited by 499 publications

References 50 publications

Joint resource allocations for remote radio head deployments with coherent transmitter

Joint resource allocations for remote radio head deployments with coherent transmitter

Resource allocation for clustered network MIMO OFDMA systems

Cooperative Communications

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