Multicell OFDMA Downlink Resource Allocation Using a Graphic Framework

Chang, Ronald Y.; Zhang, Tao; Zhang, Jinyun; Kuo, C.-C. Jay

doi:10.1109/tvt.2009.2014384

Cited by 155 publications

(128 citation statements)

References 21 publications

(22 reference statements)

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“…In other words, our problem is that of finding a solution that makes full use of the affordable number of colors for maximizing the utility. Secondly, instead of allocating channels relying on orthogonal RBs using exclusive colors [19], the vertices in our graph represent the user-centric clusters and allow the reuse of colors, since the available number of colors is lower than the number of vertices. Finally, the topology of the constructed graph representing our problem is more complex owing to the overlapped clusters in the particularly dense deployment of APs and UEs considered.…”

Section: Introduction a Motivation And Scopesmentioning

confidence: 99%

Graph-Based Joint User-Centric Overlapped Clustering and Resource Allocation in Ultradense Networks

Lin

Zhang

et al. 2018

IEEE Trans. Veh. Technol.

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Abstract-With the increase of access point (AP) density and the exponential growth of mobile devices supported by ultra dense networks (UDNs), user-centric overlapped clustering relying on AP cooperation is becoming a promising design principle for guaranteeing the quality of service (QoS) required by each UE. This ambitious goal can be achieved by the joint design of user-centric overlapped clustering and resource allocation. In this context, both the traffic-load balancing and the limited availability of orthogonal resource blocks (RBs) have to be carefully considered in UDNs. To tackle these challenges, we formulate a joint user-centric overlapped clustering and resource allocation problem with the goal of maximizing the system's spectral efficiency (SE). To efficiently solve this problem, it is decoupled into two subproblems, which can be solved independently with the aid of our graph-theoretical framework. We first develop a novel distributed three-stage user-centric clustering solution, which is aware of the APs' traffic-loads. Then, based on the overlapped clusters constructed, we propose a novel two-stage graph-based user-centric resource allocation scheme for mitigating the resultant inter-cluster interference, despite the limited availability of orthogonal RBs. Our numerical results confirm the benefits of the proposed framework and show that it outperforms the benchmark solutions in terms of both its per area aggregated user rate (PAAR) and user rate.

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Section: Introduction a Motivation And Scopesmentioning

confidence: 99%

Graph-Based Joint User-Centric Overlapped Clustering and Resource Allocation in Ultradense Networks

Lin

Zhang

et al. 2018

IEEE Trans. Veh. Technol.

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“…Previous research work has investigated nearoptimal algorithms for scheduling channels or subcarriers under the conditions of fairness and power control [5,6,7,8]. The general optimal solution without those conditions for scheduling resource blocks in a multi-cell network is not well-studied.…”

Section: Introductionmentioning

confidence: 99%

Near-Optimal Resource Allocation in Cooperative Cellular Networks Using Genetic Algorithms

Luo

Armour

McGeehan

2015

Multiple Access Communications

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Abstract. This paper shows how a genetic algorithm can be used as a method of obtaining the near-optimal solution of the resource block scheduling problem in a cooperative cellular network. An exhaustive search is initially implemented to guarantee that the optimal result, in terms of maximizing the bandwidth efficiency of the overall network, is found, and then the genetic algorithm with the properly selected termination conditions is used in the same network. The simulation results show that the genetic algorithm can approximately achieve the optimum bandwidth efficiency whilst requiring only 24% of the computation effort of the exhaustive search in the investigated network.

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“…In systems with BS cooperation, additional mechanisms, such as resource allocation techniques [37], may be required to deal with the interference contributions that cannot be fully mitigated using spatial processing. In this paper, a multi-base spreading code allocation scheme is specifically proposed for systems with BS cooperation, where spreading codes are assigned to users in such a way that minimum average cross-correlation between active users can be achieved.…”

Section: Introductionmentioning

confidence: 99%

Multi-user interference mitigation under limited feedback requirements for WCDMA systems with base station cooperation

2015

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One of the techniques that has been recently identified for dealing with multi-user interference in future communications systems is base station cooperation or joint processing. However, perfect multi-user interference cancellation with this technique demands severe synchronization requirements, perfect and global channel state information, and an increased backhaul and signaling overhead. In this paper, we consider a more realistic layout with the aim of mitigating the multi-user interference, where only local channel state information is available at the base stations. Due to synchronization inaccuracies and errors in the channel estimation, the system becomes partially asynchronous. In the downlink of WCDMA based systems, this asynchronism stands for the loss of the orthogonality of the spreading codes allocated to users and thus, for an increase in the multi-user interference level of the system. In this contribution, we propose a framework for mitigating the multi-user interference which builds in three main steps: definition of a cooperation area based on the channel characteristics, statistical modeling of the average multi-user interference power experienced by each user and a specific spreading code allocation scheme for users served with joint processing. This code allocation assigns spreading codes to users in such a way that minimum average cross-correlation between active users can be achieved. Interestingly, these steps can be

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Multicell OFDMA Downlink Resource Allocation Using a Graphic Framework

Cited by 155 publications

References 21 publications

Graph-Based Joint User-Centric Overlapped Clustering and Resource Allocation in Ultradense Networks

Graph-Based Joint User-Centric Overlapped Clustering and Resource Allocation in Ultradense Networks

Near-Optimal Resource Allocation in Cooperative Cellular Networks Using Genetic Algorithms

Multi-user interference mitigation under limited feedback requirements for WCDMA systems with base station cooperation

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