Pricing-Based Interference Coordination for D2D Communications in Cellular Networks

Yin, Rui; Yu, Guanding; Zhang, Huazi; Zhang, Zhaoyang; Li, Geoffrey Ye

doi:10.1109/twc.2014.2368151

Cited by 129 publications

(84 citation statements)

References 23 publications

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“…Resource allocation in D2D communication is such an application. Here, we describe at first some classical approaches [7][8][9][10][11][12][13][14][15][16] followed by existing RL-based resource allocation algorithms [17,18].…”

Section: Related Workmentioning

confidence: 99%

“…Here, the channel assigned to the cellular users is reused by only one D2D pair and the cotier interference is not considered. In [16], Yin et al propose a distributed resource allocation method where minimum rates of cellular users and D2D pairs are maintained. A Game theoretic algorithm (GTA) is proposed for minimizing the interferences among D2D pairs.…”

Section: Related Workmentioning

confidence: 99%

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Throughput-Aware Cooperative Reinforcement Learning for Adaptive Resource Allocation in Device-to-Device Communication

et al. 2017

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Device-to-device (D2D) communication is an essential feature for the future cellular networks as it increases spectrum efficiency by reusing resources between cellular and D2D users. However, the performance of the overall system can degrade if there is no proper control over interferences produced by the D2D users. Efficient resource allocation among D2D User equipments (UE) in a cellular network is desirable since it helps to provide a suitable interference management system. In this paper, we propose a cooperative reinforcement learning algorithm for adaptive resource allocation, which contributes to improving system throughput. In order to avoid selfish devices, which try to increase the throughput independently, we consider cooperation between devices as promising approach to significantly improve the overall system throughput. We impose cooperation by sharing the value function/learned policies between devices and incorporating a neighboring factor. We incorporate the set of states with the appropriate number of system-defined variables, which increases the observation space and consequently improves the accuracy of the learning algorithm. Finally, we compare our work with existing distributed reinforcement learning and random allocation of resources. Simulation results show that the proposed resource allocation algorithm outperforms both existing methods while varying the number of D2D users and transmission power in terms of overall system throughput, as well as D2D throughput by proper Resource block (RB)-power level combination with fairness measure and improving the Quality of service (QoS) by efficient controlling of the interference level.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Throughput-Aware Cooperative Reinforcement Learning for Adaptive Resource Allocation in Device-to-Device Communication

et al. 2017

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“…Thus, the proposed algorithms in the above can be adopted: At the first, the optimization framework in the dedicated mode can be used to allocate the reserved resource for the D2D pairs, then the micro-adjustment like one D2D pair sharing the same resource of a RCU can be solved by the optimization framework in the reusing mode. Note that in case of multiple D2D pairs sharing the same resource [31], the proposed algorithm in the reusing mode can also be adopted as the problem is still the D. C. form, and finally the optimal user matching can be obtained by the Hungarian algorithm as in [27].…”

Section: E Mode Switching For Multiple D2d Pairs and Rcusmentioning

confidence: 99%

Mode Switching for Energy-Efficient Device-to-Device Communications in Cellular Networks

Feng

Yu²,

Xiong³

et al. 2015

IEEE Trans. Wireless Commun.

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118

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This paper investigates energy-efficient device-todevice (D2D) communications in cellular networks. We aim to maximize the overall energy-efficiency (EE) of D2D users and regular cellular users (RCUs) while considering the circuit power consumption and the quality-of-service (QoS) requirements for both types of users as well as power constraints. Three transmission modes, namely, dedicated mode, reusing mode, and cellular mode, are considered for D2D users to share spectrum with RCUs. Parametric Dinkelbach method and concave-convex procedure (CCCP) are adopted to transform the original optimization problems into more tractable forms through sequential convex approximations. Then, interior point method is exploited to obtain the optimal solution. Simulation results show that system EE can be improved significantly with the proposed mode switching algorithm compared with the single mode transmission. Besides, it is also shown that the reusing mode is more preferred in the EE based mode switching while it is the dedicated mode in the spectrum-efficiency (SE) based mode switching in most situations.

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“…Both the works of Yu et al and Jung et al [10,11] consider the joint mode selection and resource allocation problem that aims to improve the sum-rate and the power efficiency. While guaranteeing the quality of service (QoS) of both CUs and D2D pairs, a centralized spectrum allocation scheme has been designed to maximize the system throughput in [12]. In [13], a coalitional game approach is employed to solve the joint mode selection and D2D resource allocation.…”

Section: Introductionmentioning

confidence: 99%

A Resource Allocation Scheme for Multi-D2D Communications Underlying Cellular Networks with Multi-Subcarrier Reusing

Zhang

Al-qaness

et al. 2017

Applied Sciences

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Device-to-device (D2D) communication is proposed as a promising technique of future cellular networks which fulfills its potential in terms of high resource utilization. In this paper, in order to improve the achievable rate of D2D communication and the spectrum utilization, we consider the scenario that multiple D2D pairs can share uplink spectrum resources with multiple cellular users (CUs). We aim to maximize the overall system spectrum efficiency while satisfying the rate requirements of all CUs and guaranteeing that the system gain is positive. We formulate the joint optimization problem of subcarrier assignment and power allocation which falls naturally into a mixed integer non-linear programming form that is a difficult problem to solve. Hence, we propose a two-stage resource allocation scheme which comprises a subcarrier assignment by employing a heuristic greedy strategy, as well as a power allocation algorithm based on the Lagrangian dual method. Numerical results demonstrate the advantageous performance of our scheme in greatly increasing the system sum spectrum efficiency.

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Pricing-Based Interference Coordination for D2D Communications in Cellular Networks

Cited by 129 publications

References 23 publications

Throughput-Aware Cooperative Reinforcement Learning for Adaptive Resource Allocation in Device-to-Device Communication

Throughput-Aware Cooperative Reinforcement Learning for Adaptive Resource Allocation in Device-to-Device Communication

Mode Switching for Energy-Efficient Device-to-Device Communications in Cellular Networks

A Resource Allocation Scheme for Multi-D2D Communications Underlying Cellular Networks with Multi-Subcarrier Reusing

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