scholarly journals Performance Comparison of Practical Resource Allocation Schemes for Device-to-Device Communications

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Gábor Fodor

Device-to-device (D2D) communications in cellular spectrum have the potential of increasing the spectral and energy efficiency by taking advantage of the proximity and reuse gains. Although several resource allocation (RA) and power control (PC) schemes have been proposed in the literature, a comparison of the performance of such algorithms as a function of the available channel state information has not been reported. In this paper, we examine which large scale channel gain knowledge is needed by practically viable RA and PC schemes for network assisted D2D communications. To this end, we propose a novel near-optimal and low-complexity RA scheme that can be advantageously used in tandem with the optimal binary power control scheme and compare its performance with three heuristics-based RA schemes that are combined either with the well-known 3GPP Long-Term Evolution open-loop path loss compensating PC or with an iterative utility optimal PC scheme. When channel gain knowledge about the useful as well as interfering (cross) channels is available at the cellular base station, the near-optimal RA scheme, termed Matching, combined with the binary PC scheme is superior. Ultimately, we find that the proposed low-complexity RA + PC tandem that uses some cross-channel gain knowledge provides superior performance.

Author(s):  
Xin Wang ◽  
Zhihong Qian ◽  
Xue Wang ◽  
Lan Huang

The rate-requirement of device-to-device (D2D) users is associated with the context information of velocity and data size of users to some extent. In this study, an efficient context-aware resource allocation scheme based on rate requirement (RARR) is proposed. This scheme consists of two allocation phases. In the rate-ensuring resource allocation phase, D2D pairs are allocated a certain amount of spectrum resource according to their rate requirement. In the allocation, the interference restricted area is limited to exclude cellular users that bring a negative capacity gain to the communication system. In the residual resource reallocation phase, surplus resources are assigned to D2D pairs according to the system fairness. Simulation results indicate that the proposed RARR scheme efficiently leads to superior performance in terms of system throughput and fairness and exhibits low complexity relative to traditional resource allocation.


2020 ◽  
Vol 5 (2) ◽  
pp. 45-59
Author(s):  
I.A. Olaoluwa ◽  
M.A. Adedoyin ◽  
A.I.O. Yussuff

Recent development in pairs of devices communications in the cellular system has necessitated the emergence of various resource allocation strategies for power control with the hope of achieving higher data rate, enhanced system capacity and overall spectral efficiency. Strategies for efficient service delivery in device-to-device (D2D) cellular system have often posed daunting challenges requiring uncompromising techniques. In this work, various techniques for resource allocation strategies for power control in D2D cellular system are investigated. This work is dedicated at the best technique of achieving maximum transmission power of users of cellular and the device pair users with reference to the efficient service delivery coupled with established signal-to-interference-plus-noise ratio (SINR) at the base station and the D2D users across the channel of the uplink because of the ability of the individual transmitter of devices have been able to realign with the power of transmitter relative to the calculated SINR and interference parameters. An expression of SINR, D2D pairs and the distance between device pairs with respect to base station for the optimized network for the various techniques are analyzed. The performance of the resource-based power control technique (RPCT) and the adaptive power control technique (APCT), with respect to the SINR and the device pairs, has shown effectiveness in its ability to address over forty-three pairs of D2D in order to have an improved level of SINR as obtained in this work, it is convenient to say that an increase in the number of cellular users, enables a corresponding increase in the total capacity of D2D users. When an increase is experienced in the number of users of cellular, it automatically adds a value of increase to the reusable channels thereby enabling additional quantity of D2D users in the clusters, such that co-channel interference within the D2D users in the neighboring cluster reduces, thereby enabling an increased capacity of the user of D2D.


Author(s):  
Toha Ardi Nugraha ◽  
Muhammad Putra Pamungkas ◽  
Anna Nur Nazilah Chamim

There are many scenarios that have been proposed for fifth generation (5G) networks. Some of them, if implemented, will bring fundamental changes at the architectural and node level. One example of such proposed technologies is device-to-device (D2D) communications which will change the nature of conventional cellular network design. D2D permits direct communication between two or more user devices without intervention of the base station (i.e. eNB). D2D can ensure network performance improvement over the traditional cellular network, because it can offload the mobile data traffic from the other devices. However, applying D2D features in a cellular network will bring about more complex interference problems, since D2D communication uses the same band as its underlying cellular communication network. The aim of this research is to investigate interference-related problems caused by D2D communications, affecting the underlying cellular networks, during downlink and uplink transmissions. The paper examines the use of power control methods to mitigate interference. A comparison is offered between fixed power level (FC) with or without power control, and adaptive power controls using two methods (AC1 and AC2), on a base station or on each of the D2D devices, based on the measured signal to interference plus noise ratio (SINR). The simulation results show that both power control methods contribute to improvement of network performance. AC1 and AC2 can improve SINR by about 1 dB and 0.5 dB compared to FC in a downlink transmission, and by 0.5 dB in an uplink transmission.


2020 ◽  
Vol 10 (5) ◽  
pp. 1557
Author(s):  
Weijia Feng ◽  
Xiaohui Li

Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.


Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 93 ◽  
Author(s):  
Na Su ◽  
Qi Zhu

This paper assumes that multiple device-to-device (D2D) users can reuse the same uplink channel and base station (BS) supplies power to D2D transmitters by means of wireless energy transmission; the optimization problem aims at maximizing the total capacity of D2D users, and proposes a power control and channel allocation algorithm for the energy harvesting D2D communications underlaying the cellular network. This algorithm firstly uses a heuristic dynamic clustering method to cluster D2D users and those in the same cluster can share the same channel. Then, D2D users in the same cluster are modeled as a non-cooperative game, the expressions of D2D users’ transmission power and energy harvesting time are derived by using the Karush–Kuhn–Tucker (KKT) condition, and the optimal transmission power and energy harvesting time are allocated to D2D users by the joint iteration optimization method. Finally, we use the Kuhn–Munkres (KM) algorithm to achieve the optimal matching between D2D clusters and cellular channel to maximize the total capacity of D2D users. Simulation results show that the proposed algorithm can effectively improve the system performance.


2019 ◽  
Vol 9 (18) ◽  
pp. 3816 ◽  
Author(s):  
Saraereh ◽  
Mohammed ◽  
Khan ◽  
Rabie ◽  
Affess

In order to solve the problem of interference and spectrum optimization caused by D2D (device-to-device) communication multiplexing uplink channel of heterogeneous cellular networks, the allocation algorithm based on the many-to-one Gale-Shapley (M21GS) algorithm proposed in this paper can effectively solve the resource allocation problem of D2D users multiplexed cellular user channels in heterogeneous cellular network environments. In order to improve the utilization of the wireless spectrum, the algorithm allows multiple D2D users to share the channel resources of one cellular user and maintains the communication service quality of the cellular users and D2D users by setting the signal to interference and noise ratio (SINR) threshold. A D2D user and channel preference list are established based on the implemented system’s capacity to maximize the system total capacity objective function. Finally, we use the Kuhn–Munkres (KM) algorithm to achieve the optimal matching between D2D clusters and cellular channel to maximize the total capacity of D2D users. The MATLAB simulation is used to compare and analyze the total system capacity of the proposed algorithm, the resource allocation algorithm based on the delay acceptance algorithm, the random resource allocation algorithm and the optimal exhaustive search algorithm, and the maximum allowable access for D2D users. The simulation results show that the proposed algorithm has fast convergence and low complexity, and the total capacity is close to the optimal algorithm.


Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1397
Author(s):  
Yishi Xue ◽  
Bo Xu ◽  
Wenchao Xia ◽  
Jun Zhang ◽  
Hongbo Zhu

Driven by its agile maneuverability and deployment, the unmanned aerial vehicle (UAV) becomes a potential enabler of the terrestrial networks. In this paper, we consider downlink communications in a UAV-assisted wireless communication network, where a multi-antenna UAV assists the ground base station (GBS) to forward signals to multiple user equipments (UEs). The UAV is associated with the GBS through in-band wireless backhaul, which shares the spectrum resource with the access links between UEs and the UAV. The optimization problem is formulated to maximize the downlink ergodic sum-rate by jointly optimizing UAV placement, spectrum resource allocation and transmit power matrix of the UAV. The deterministic equivalents of UE’s achievable rate and backhaul capacity are first derived by utilizing large-dimensional random matrix theory, in which, only the slowly varying large-scale channel state information is required. An approximation problem of the joint optimization problem is then introduced based on the deterministic equivalents. Finally, an algorithm is proposed to obtain the optimal solution of the approximate problem. Simulation results are provided to validate the accuracy of the deterministic equivalents, and the effectiveness of the proposed method.


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