Joint channel selection and optimal power allocation for multi‐cell D2D communications underlaying cellular networks

Esmat, Haitham H.; Elmesalawy, Mahmoud M.; Ibrahim, Ibrahim I.

doi:10.1049/iet-com.2016.0955

Cited by 10 publications

(9 citation statements)

References 21 publications

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“…Two metrics are used to estimate the performance of the suggested algorithm. The first one is the access rate that is defined as the ratio of the number of SUEs that achieved the target QoS to the total number of SUEs that this metric is used in several previous research works to evaluate the performance of such algorithms –. Then, the total achieved throughput of SCs is used as the second metric.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The first one is the access rate that is defined as the ratio of the number of SUEs that achieved the target QoS to the total number of SUEs that this metric is used in several previous research works to evaluate the performance of such algorithms. [36][37][38] Then, the total achieved throughput of SCs is used as the second metric. In simulation, the MUEs and SUEs are randomly distributed in the whole coverage areas of MBS and RRHs, respectively; system bandwidth = 10 MHz, K = M = 50, channel bandwidth = 180 kHz, the minimum data rate requirements for SUEs R min are set to be a random value in the range of [0, 10] bps/Hz, 2 = 0.05 for all channels, maximum transmit power for SUE P SUE max = 20 dBm, and N 0 = −174 dBm/Hz.…”

Section: Simulation Resultsmentioning

confidence: 99%

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Joint radio resource and power allocation using Nash bargaining game for H‐CRAN with nonideal fronthaul links

Esmat

Elmesalawy

Abdelhakam

2018

Trans Emerging Tel Tech

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Heterogeneous cloud radio access network (H‐CRAN) is introduced as a novel network architecture that takes the full rewards of both heterogeneous cellular network (HCNs) and cloud radio access network (CRAN). In H‐CRAN architecture, the remote radio heads of small cells (SCs) are overlaid within the coverage of macro cell and linked to the baseband unit pool through nonideal fronthaul connections. To improve the spectral efficiency of this network, the SCs are developed to reuse the same resources used by the macro cell. However, this will introduce inter‐tier interference between macro cell and SCs and intra‐tier interference among SCs that need to be efficiently managed. In this paper, the joint problem of radio resource and power allocation in H‐CRAN is formulated using cooperative Nash bargaining game. This optimization problem is designed to maximize the total throughput of SCs, while considering the fairness between user equipments (UEs) in each SC, interference protection requirements for macro UEs, outage probability requirements, and the capacity limitation of nonideal fronthaul connections. Then, by using Lagrangian dual decomposition, the near‐optimal bargaining allocation strategy for radio resources and power of each SC UE is determined. Simulation results illustrate that the performance of the suggested algorithm outperforms the other comparable algorithm in terms of the SCs' achieved throughput and fairness. Moreover, the effect of nonideal fronthaul capacity constraint and the interference protection limit of macro UEs on the performance of the suggested scheme are examined.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Joint radio resource and power allocation using Nash bargaining game for H‐CRAN with nonideal fronthaul links

Esmat

Elmesalawy

Abdelhakam

2018

Trans Emerging Tel Tech

Self Cite

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“…Therefore, interference management must be applied to effectively handle the interference, and to guarantee a certain degree of quality of service (QoS). In the literature, various power control and resource allocation schemes have been proposed to guarantee QoS requirements in terms of signal-to-interference-plus-noise ratio (SINR) or minimum required data rate [8][9][10][11][12][13][14][15][16][17]. In [8], a power control scheme was studied to maximize the sum of the achievable data rates of a CU-DU pair.…”

Section: Introductionmentioning

confidence: 99%

“…In [10], a resource allocation scheme was studied while assuming that the transmit power of UEs is fixed. Joint power control and resource allocation schemes were proposed in [11][12][13][14][15][16][17]. A single DU is assigned to only one channel, and vice versa in [11,12], whereas multiple DUs are allowed to be assigned to the same channel in [13,14].…”

Section: Introductionmentioning

confidence: 99%

“…A single DU is assigned to only one channel, and vice versa in [11,12], whereas multiple DUs are allowed to be assigned to the same channel in [13,14]. In addition, a DU is allowed to be assigned to multiple channels in [15][16][17]. In addition to power control and resource allocation, mode selection for DUs and relay selections were considered in [18][19][20] and [21,22], respectively.…”

Section: Introductionmentioning

confidence: 99%

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Resource Allocation with a Rate Guarantee Constraint in Device-to-Device Underlaid Cellular Networks

Kwon

Kim

2020

Electronics

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Device-to-device (D2D) communication is a crucial technique for various proximity services. In addition to high-rate transmission and high spectral efficiency, a minimum data rate is increasingly required in various applications, such as gaming and real-time audio/video transmission. In this paper, we consider D2D underlaid cellular networks and aim to minimize the total channel bandwidth while every user equipment (UE) needs to achieve a pre-determined target data rate. The optimization problem is jointly involved with matching a cellular UE (CU) to a D2D UE (DU), and with channel assignment and power control. The optimization problem is decoupled into two suboptimization problems to solve power control and channel assignment problems separately. For arbitrary matching of CU, DU, and channel, the minimum channel bandwidth of the shared channel is derived based on signal-to-interference-plus-noise ratio (SINR)-based power control. The channel assignment is a three-dimensional (3-D) integer programming problem (IPP) with a triple (CU, DU, channel). We apply Lagrangian relaxation, and then decompose the 3-D IPP into two two-dimensional (2-D) linear programming problems (LPPs). From intensive numerical results, the proposed resource allocation scheme outperforms the random selection and greedy schemes in terms of average channel bandwidth. We investigate the impact of various parameters, such as maximum D2D distance and the number of channels.

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Uplink resource allocation and power control for D2D communications underlaying multi-cell mobile networks

Esmat

Elmesalawy

Ibrahim

2018

AEU - International Journal of Electronics and Communications

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Joint channel selection and optimal power allocation for multi‐cell D2D communications underlaying cellular networks

Cited by 10 publications

References 21 publications

Joint radio resource and power allocation using Nash bargaining game for H‐CRAN with nonideal fronthaul links

Joint radio resource and power allocation using Nash bargaining game for H‐CRAN with nonideal fronthaul links

Resource Allocation with a Rate Guarantee Constraint in Device-to-Device Underlaid Cellular Networks

Uplink resource allocation and power control for D2D communications underlaying multi-cell mobile networks

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