Joint Uplink Scheduling and Interference Mitigation in Multicell LTE Networks

Yaacoub, Elias; Dawy, Zaher

doi:10.1109/icc.2011.5962631

Cited by 21 publications

(9 citation statements)

References 12 publications

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“…Distributed power control techniques where each BS controls its transmit power, have been widely used [2][3][4][5] to manage ICI in wireless cellular networks. In the first category are non-cooperative power control techniques [2], where each BS determines its transmit power based on its own interference information.…”

Section: Introductionmentioning

confidence: 99%

“…In the first category are non-cooperative power control techniques [2], where each BS determines its transmit power based on its own interference information. In the second category are the cooperative power control methods, where adjacent BSs cooperate in deciding the transmit power used.…”

Section: Introductionmentioning

confidence: 99%

“…The distributed computation based on the BP method, reduces the complexity of BS cooperation carried out by a centralised approach N times, where N is the number of BSs involved in the cooperation process [8], [9]. In these research papers [2][3][4][5][6][7][8]. however, it has been assumed that BSs transmit to its respective UEs regardless of the level of the signal-tointerference-plus-noise-ratio (SINR) at the UE.…”

Section: Introductionmentioning

confidence: 99%

“…The contribution of the paper is that, unlike other distributed power control algorithms in [2,3], [7,8] we allow only the transmission of those BSs that can satisfy the minimum received SINR requirements of their respective UEs. This results in a better usage of power and channel as the BSs will not transmit unless they can satisfy a defined quality of service, required by UE.…”

Section: Introductionmentioning

confidence: 99%

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A distributed cooperative power allocation scheme for small cell networks

Apandi

Hardjawana

Vucetic

2015

2015 IEEE Wireless Communications and Networking Conference (WCNC)

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A small cell networks (SCN) concept has been widely accepted as the most efficient method to increase cellular network capacity. As the cell size and networks become smaller and denser, respectively, inter-cell interference (ICI) at a user terminal equipment (UE), coming from the adjacent base station (BS) transmissions, grows considerably and becomes more complex to manage. In this paper, we develop a distributed cooperative downlink power allocation algorithm for SCN that maximises the network sum capacity, subject to the minimum received SINR requirements at the UEs. We first formulate the power optimisation problem, with BSs transmit powers as the variables to be optimised. A factor graph representation for ICI and Belief Propagation (BP) method for the power allocation optimisation are then developed. This optimisation representation allows each BS to cooperate by exchanging messages about the estimates of the sum capacity that can satisfy minimum SINR requirements at UEs. Each BS uses this information to optimise its transmit power allocation. To reduce the overhead information that needs to be exchanged by the BSs, we allow only a subset of BSs in the network, chosen randomly, to exchange messages. The simulation results show that the network sum capacity obtained by the proposed algorithm, with only 70% randomly chosen active BSs, is close to the one obtained by using a global optimal exhaustive search method and it outperforms the best existing scheme.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A distributed cooperative power allocation scheme for small cell networks

Apandi

Hardjawana

Vucetic

2015

2015 IEEE Wireless Communications and Networking Conference (WCNC)

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“…The eNodeB in LTE provides basis for the admission control algorithm and is capable of operating separately on a per cell basis (Spaey et al, 2010). Congestion avoidance is the main aim of CAC scheme which limits the number of ongoing connections in the system or denies new connection request so that QoS can be maintained and delivered to different connections at the target level.The below two conditions need to be satisfied in the CAC algorithm in order to admit the user to the network (Antonopoulos and Verikoukis, 2010).…”

Section: Call Admission Control In Lte Networkmentioning

confidence: 99%

Utility Based Scheduling and Call Admission Control for Long Term Evolution Networks

Franklin¹

2012

Journal of Computer Science

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In this study, we propose to design a call admission control algorithm which schedules the channels for Real time and non-real time users. In Long Term Evolution (LTE) 3GPP Networks, several works were done on call admission control but these works rarely considers scheduling of resources to the real time and non-real time users.When the system meets traffic oriented performance degration, maximum resources are utilized for load balancing and to maintain the consistent quality. In order to avoid the channel degradation and improve the Quality of Service (QoS), the call requests are classified into New Call (NC) request and Handoff Call (HC) request and the type of services are classified as VoIP and video. Then based upon the Received Signal Strength (RSS) value, the channel is estimated as good channel or bad channel. Resource allocation is made for VoIP users based on traffic density. Then non-VoIP users and the non-real time users are allocated resource blocks using the channel condition based marginal utility function. When there are no sufficient resources to allocate, it allocates the resources of bad channel users there by degrading their service. We have designed the network topology with G (n) and B (n) for representing the available good and bad channels. We investigate the performance degradation when the real time, Non real Time, video and VOIP environments based on RSS threshold value.Comparison is made with the VOS in terms of the paramenters like throughput,bandwidth,delay,fairness and rate. Our proposed method provides good performance and quality.From our simulation results we show that this admission control algorithm provides channel quality and prioritizes the handover calls over new calls which allocates resources to all kinds of users.

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