scholarly journals Resource Allocation for Intelligent Reflecting Surface Enabled Heterogeneous Networks

2020 ◽  
Author(s):  
Yongjun Xu ◽  
Zhijin Qin ◽  
Yu Zhao ◽  
Guoquan Li ◽  
Guan Gui ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Phase Shift ◽  
Power Allocation ◽  
Heterogeneous Networks ◽  
Communication Systems ◽  
Base Station ◽  
Small Cell ◽  
Joint Power ◽  
User Scenario ◽  
Reflecting Surface

Intelligent reflecting surface (IRS)-enabled communication systems provide higher system capacity and spectral efficiency by reflecting the incident signals from transmitters in a low-cost passive reflecting way. However, it poses new challenges in resource allocation due to surrounding interference and phase shift, especially when IRS is employed in heterogeneous networks (HetNets). In this paper, a joint power allocation and phase shift optimization problem is studied for the downlink IRS-enabled HetNet, in which the IRS is deployed to enhance the communications between small cell users (SCUs) and associated base station (BS). The signal-to-interference-plus-noise ratio (SINR) received at the SCU is maximized by jointly optimizing the transmit power of the small-cell BS and the phase shift of the IRS, subject to the constraints on the minimum SINR requirement of the macro-cell user (MCU) and the phase shift. Although the formulated problem is non-convex, we develop an optimal power allocation and the IRS's passive array coefficient solution for the single-user scenario. For the multi-user scenario, we propose an iterative algorithm to maximize the total rates of SCUs for obtaining a suboptimal solution by an alternating iteration manner, where the sum of multiple-ratio fractional programming problem is converted into a convex semidefinite program (SDP) problem. Simulation results show that the proposed algorithm significantly improves the achieved transmission rates of SCUs compared to the case without the IRS.

scholarly journals Resource Allocation for Intelligent Reflecting Surface Enabled Heterogeneous Networks

2020 ◽  
Author(s):  
Yongjun Xu ◽  
Zhijin Qin ◽  
Yu Zhao ◽  
Guoquan Li ◽  
Guan Gui ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Phase Shift ◽  
Power Allocation ◽  
Heterogeneous Networks ◽  
Communication Systems ◽  
Base Station ◽  
Small Cell ◽  
Joint Power ◽  
User Scenario ◽  
Reflecting Surface

Intelligent reflecting surface (IRS)-enabled communication systems provide higher system capacity and spectral efficiency by reflecting the incident signals from transmitters in a low-cost passive reflecting way. However, it poses new challenges in resource allocation due to surrounding interference and phase shift, especially when IRS is employed in heterogeneous networks (HetNets). In this paper, a joint power allocation and phase shift optimization problem is studied for the downlink IRS-enabled HetNet, in which the IRS is deployed to enhance the communications between small cell users (SCUs) and associated base station (BS). The signal-to-interference-plus-noise ratio (SINR) received at the SCU is maximized by jointly optimizing the transmit power of the small-cell BS and the phase shift of the IRS, subject to the constraints on the minimum SINR requirement of the macro-cell user (MCU) and the phase shift. Although the formulated problem is non-convex, we develop an optimal power allocation and the IRS's passive array coefficient solution for the single-user scenario. For the multi-user scenario, we propose an iterative algorithm to maximize the total rates of SCUs for obtaining a suboptimal solution by an alternating iteration manner, where the sum of multiple-ratio fractional programming problem is converted into a convex semidefinite program (SDP) problem. Simulation results show that the proposed algorithm significantly improves the achieved transmission rates of SCUs compared to the case without the IRS.

scholarly journals Optimizing the Spectrum and Power Allocation for D2D-Enabled Communication Systems Using DC Programming

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Guomei Gan ◽  
Yanhu Huang ◽  
Qiang Wang
Keyword(s):  
Resource Allocation ◽  
Power Allocation ◽  
Communication Systems ◽  
Dc Programming ◽  
Base Station ◽  
Allocation Problem ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Resource Allocation Problem ◽  
Subcarrier Assignment

Device to device (D2D) communication has recently attracted a lot of attentions since it can significantly improve the system throughput and reduce the energy consumption. Indeed, the devices can communicate with each other in a D2D system, and the base station (BS) can share the spectrum with D2D users, which can efficiently improve the spectrum and energy efficiency. Nevertheless, spectrum sharing also raises the difficulty of resource allocation owing to the serious cochannel interference. To reduce the interference, the transmit power of the D2D pairs and BS to cellular users should be further optimized. In this paper, we consider the resource allocation problem of D2D networks involving the power allocation and subcarrier assignment. The resource allocation problem is formulated as a mixed integer programming problem which is difficult to solve. To reduce the computational complexity, the original problem is decomposed as two subproblems in terms of the subcarrier assignment and power allocation. For the subcarrier assignment problem, the particle swarm optimization (PSO) is adopted to solve it since the subcarrier assignment is an integer optimization problem, and it is difficult to be tackled using the traditional optimization approach. When the subcarrier assignment is fixed, there are only the power allocation variables in the original resource allocation problem. The difference of convex functions (DC) programming is adopted to solve the power allocation problem. Simulation results demonstrate the effectiveness of the proposed resource allocation scheme of D2D networks.

scholarly journals Joint power allocation and subcarrier assignment for device to device in 5G time division duplex networks

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881109 ◽  
Author(s):  
Pan Zhao ◽  
Lei Feng ◽  
Peng Yu ◽  
Wenjing Li ◽  
Xuesong Qiu
Keyword(s):  
Quality Of Service ◽  
Power Allocation ◽  
Base Station ◽  
Joint Power ◽  
Time Division Duplex ◽  
Device To Device ◽  
Minlp Problem ◽  
Device To Device Communication ◽  
Time Division

The explosive demands for mobile broadband service bring a major challenge to 5G wireless networks. Device-to-device communication, adopting side links for user-direct communication, is regarded as a main technical source for offloading large volume of mobile traffic from cellular base station. This article investigates the joint power and subcarrier allocation scheme for device-to-device communication in 5G time division duplex systems. In time division duplex system, instead of utilizing an exclusive portion of the precious cellular spectrum, device-to-device pairs reuse the subcarriers occupied by cellular users, thus producing harmful interference to cellular users in both uplink and downlink communication, and strongly limiting the spectrum efficiency of the system. To this end, we focus on the maximization of device-to-device throughput while guaranteeing both uplink and downlink channel quality of service of cellular users as well as device-to-device pairs. The problem is formulated as a mixed integer non-linear programming (MINLP) problem. To make it tractable, we separate the original MINLP problem into two sub problems: power allocation and sub-carrier reusing. The former is to develop optimal power allocation for each device-to-device pair and each cellular user, with the constraints of maximum power and quality of service. It is solved by geometric programming technique in convex optimization method. The latter is derived as a one-to-many matching problem for scheduling multiple subcarriers occupied by cellulars to device-to-device pairs. It is solved by Hungarian method. Simulation results show that the proposed scheme significantly improves system capacity of the device-to-device underlay network, with quality of service of both device-to-device users and cellular users guaranteed.

scholarly journals Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

2020 ◽  
Author(s):  
Yongjun Xu ◽  
Haijian Sun ◽  
Jie Yang ◽  
Guan Gui ◽  
Song Guo
Keyword(s):  
Resource Allocation ◽  
Closed Form ◽  
Power Allocation ◽  
Energy Region ◽  
High Energy ◽  
Cognitive Networks ◽  
Feasible Region ◽  
Power Splitting ◽  
Joint Power ◽  
The Impact

Simultaneous wireless information and power transfer (SWIPT)-enabled cognitive networks (CRNs) is recognized as one of the most promising techniques to improve spectrum efficiency and prolong operation lifetime in 5G and beyond. However, existing methods focus on the centralized algorithm and the power allocation under perfect channel state information (CSI). The analytical solution and the impact of power splitting (PS) on the optimal power allocation strategy are not addressed. In addition, the influence of the PS factor on the feasible region of transit power is rarely analyzed. In this paper, we propose a joint power allocation and PS algorithm under perfect CSI and imperfect CSI, respectively, for multiuser SWIPT-enabled CRNs scenarios. The power minimization of resource allocation problem is formulated as a multivariate nonconvex optimization which is hard to obtain the closed-form solution. Hence, we propose a suboptimal algorithm to alternatively optimize the power allocation and PS coefficient under the cases of the low-harvested energy region and the high-harvested energy region, respectively. Moreover, a closed-form distributed power allocation and PS expressions are derived by the Lagrangian approach. Simulation results confirm the proposed method with good robustness and high energy efficiency.

Uplink spectrum resource allocation in heterogeneous networks (small cell/macrocell)

2014 ◽  
Vol 70 (7-8) ◽  
pp. 311-319 ◽  
Author(s):  
Mncedisi Bembe ◽  
Jeongchan Kim ◽  
Martin Mhlanga ◽  
Jae Jeung Rho ◽  
Youngnam Han
Keyword(s):  
Resource Allocation ◽  
Heterogeneous Networks ◽  
Small Cell

scholarly journals Energy consumption index minimized resource allocation in hybrid energy multiuser OFDM system with distributed antennas

2018 ◽  
Vol 17 ◽  
pp. 03015
Author(s):  
Huanhuan MAO ◽  
Pengcheng Zhu ◽  
Jiamin Li
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Energy Harvesting ◽  
Power Allocation ◽  
Base Station ◽  
Mixed Integer ◽  
Subcarrier Allocation ◽  
Ofdm System ◽  
Consumption Index ◽  
Distributed Antennas

Energy harvesting is one of the promising option for realization of green communication and has been a growing concern recently. In this paper, we address the downlink resource allocation in OFDM system with distributed antennas with hybrid power supply base station, where energy harvesting and non-renewable power sources are used complementarily. A joint subcarrier and power allocation problem is formulated for minimizing the net Energy Consumption Index (ECI) with system Quality of Service (QoS) and bit error rates constraint. The problem is a 0-1 mixed integer nonlinear programming problem due to the binary subcarrier allocation variable. To solve the problem, we design an algorithm based on Lagrange relaxation method and fraction programming which optimizes the power allocation and subcarrier allocation iteratively in two nests. Simulation results show that the proposed algorithm converges in a small number of iterations and can improve net ECI of system greatly.

scholarly journals Joint Power Allocation at the Base Station and the Relay for Untrusted Relay Cooperation OFDMA Network

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Weiheng Jiang ◽  
Wenjiang Feng
Keyword(s):  
Access Control ◽  
Power Allocation ◽  
Secure Communication ◽  
Base Station ◽  
Optimization Approach ◽  
Transmission Power ◽  
Secrecy Rate ◽  
Joint Power ◽  
Mobile Stations ◽  
Allocation Algorithms

The secure communication that multiple OFDMA-based cell-edge mobile stations (MS) can only transmit confidential messages to base station (BS) through an untrusted intermediate relay (UR) is discussed. Specifically, with the destination-based jamming (DBJ) scheme and fixed MS transmission power assumption, our focus is on the joint BS and US power allocation to maximize system sum secrecy rate. We first analyze the challenges in solving this problem. The result indicates that our nonconvex joint power allocation is equivalent to a joint MS access control and power allocation. Then, by problem relaxation and the alternating optimization approach, two suboptimal joint MS access control and power allocation algorithms are proposed. These algorithms alternatively solve the subproblem of joint BS and UR power allocation and the subproblem of MS selection until system sum secrecy rate is nonincreasing. In addition, the convergence and computational complexity of the proposed algorithms are analyzed. Finally, simulations results are presented to demonstrate the performance of our proposed algorithms.

Resource Allocation in Orthogonal Frequency Division Multiple Access-Long Term Evaluation: Neural Network

2019 ◽  
Vol 16 (12) ◽  
pp. 5026-5031
Author(s):  
Kethavath Narender ◽  
C. Puttamadappa
Keyword(s):  
Neural Network ◽  
Resource Allocation ◽  
Communication Systems ◽  
Multiple Access ◽  
Large Scale ◽  
Cuckoo Search ◽  
Base Station ◽  
Frequency Division ◽  
Term Evaluation

Symmetrical Frequency Division Multiple Access (OFDMA) is utilized in the higher rate Wireless Communication Systems (WCSs). In the correspondence framework, a fem to cell is a little cell in building Base Station (BS), which devours less power, short range, and works in a minimal effort. The fem to cell has little separation among sender and recipient that give higher flag quality. In spite of the favorable position in fem to cell systems, there win critical difficulties in Interference Management. Specifically, impedance between the macro cell and fem to cell turns into the fundamental issue in OFDMA-Long Term Evaluation (OFDMA-LTE) framework. In this paper, the Neural Network and Hybrid Bee Colony and Cuckoo Search based Resource Allocation (NN-HBCCS-RA) in OFDMA-LTE framework is presented. The ideal power esteems are refreshed to dispense every one of the clients in the fem to cell and large scale cell. The NN-HBCCS strategy accomplished low Signal to Interference Noise Ratio (SINR), otherworldly proficiency and high throughput contrasted with customary techniques.

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