Optimization of base station density and user transmission power in multi-tier heterogeneous cellular systems

2020 ◽  
Vol 161 ◽  
pp. 334-343
Author(s):  
Zhixin Liu ◽  
Heng Zhu ◽  
Yazhou Yuan ◽  
Yi Yang ◽  
Kit Yan Chan
Keyword(s):  
Base Station ◽  
Cellular Systems ◽  
Transmission Power ◽  
Station Density

A Review on 3GPP 5G Security Aspects

2019 ◽  
Author(s):  
Rajavelsamy R ◽  
Debabrata Das
Keyword(s):  
Network Architecture ◽  
Base Station ◽  
Cellular Systems ◽  
Core Network ◽  
User Privacy ◽  
Wireless Backhaul ◽  
Level Of Use ◽  
Unified Authentication ◽  
3Rd Generation Partnership Project ◽  
5G Security

5G promises to support new level of use cases that will deliver a better user experience. The 3rd Generation Partnership Project (3GPP) [1] defined 5G system introduced fundamental changes on top of its former cellular systems in several design areas, including security. Unlike in the legacy systems, the 5G architecture design considers Home control enhancements for roaming customer, tight collaboration with the 3rd Party Application servers, Unified Authentication framework to accommodate various category of devices and services, enhanced user privacy, and secured the new service based core network architecture. Further, 3GPP is investigating the enhancements to the 5G security aspects to support longer security key lengths, False Base station detection and wireless backhaul in the Phase-2 of 5G standardization [2]. This paper provides the key enhancements specified by the 3GPP for 5G system, particularly the differences to the 4G system and the rationale behind the decisions.

scholarly journals Joint Optimization on Trajectory, Cache Placement, and Transmission Power for Minimum Mission Time in UAV-Aided Wireless Networks

2021 ◽  
Vol 10 (7) ◽  
pp. 426
Author(s):  
Tingting Lan ◽  
Danyang Qin ◽  
Guanyu Sun
Keyword(s):  
Wireless Communication ◽  
Power Allocation ◽  
Optimization Problems ◽  
Base Station ◽  
Optimization Techniques ◽  
Joint Optimization ◽  
Transmission Power ◽  
Wireless Backhaul ◽  
Mission Time ◽  
Cache Placement

In recent years, due to the strong mobility, easy deployment, and low cost of unmanned aerial vehicles (UAV), great interest has arisen in utilizing UAVs to assist in wireless communication, especially for on-demand deployment in emergency situations and temporary events. However, UAVs can only provide users with data transmission services through wireless backhaul links established with a ground base station, and the limited capacity of the wireless backhaul link would limit the transmission speed of UAVs. Therefore, this paper designed a UAV-assisted wireless communication system that used cache technology and realized the transmission of multi-user data by using the mobility of UAVs and wireless cache technology. Considering the limited storage space and energy of UAVs, the joint optimization problem of the UAV’s trajectory, cache placement, and transmission power was established to minimize the mission time of the UAV. Since this problem was a non-convex problem, it was decomposed into three sub-problems: trajectory optimization, cache placement optimization, and power allocation optimization. An iterative algorithm based on the successive convex approximation and alternate optimization techniques was proposed to solve these three optimization problems. Finally, in the power allocation optimization, the proposed algorithm was improved by changing the optimization objective function. Numerical results showed that the algorithm had good performance and could effectively reduce the task completion time of the UAV.

Dual Transmission Power and Ant Colony Optimization based Lifespan Maximization Protocol for Sensor Networks

2015 ◽  
Vol 11 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Rohini Sharma ◽  
D. K. Lobiyal
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Technique ◽  
Residual Energy ◽  
Base Station ◽  
Ant Colony ◽  
Sensor Nodes ◽  
Transmission Power ◽  
Route Length ◽  
Leach Protocol ◽  
Dual Transmission

A main characteristic of wireless sensor network (WSN) is its limited battery power. Non-uniform energy depletion in WSN, leads to formation of energy holes in certain areas of network. For a uniform consumption of energy among sensor nodes, some points should be considered like the residual energy of the nodes, energy consumed in the communication and route length. In this work, the authors has achieved the uniform consumption of energy by using dissimilar transmission power levels for communication between cluster heads and the sink node, and for intra- cluster communication. Further, they have used ant colony optimization technique for routing between the base station and sensors which are not the member of any cluster. They have proposed dual transmission power levels and ant colony optimization based (DTP-ACO) protocol to improve the lifespan of the network. Results demonstrate that DTP-ACO protocol outperforms LEACH protocol in provisions of the life span, residual energy, packets sent to the base station and throughput of the network.

scholarly journals Power Control and Channel Allocation Algorithm for Energy Harvesting D2D Communications

Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 93 ◽  
Author(s):  
Na Su ◽  
Qi Zhu
Keyword(s):  
Energy Harvesting ◽  
Power Control ◽  
Channel Allocation ◽  
Base Station ◽  
Transmission Power ◽  
D2d Communications ◽  
Harvesting Time ◽  
Allocation Algorithm ◽  
Total Capacity ◽  
Power And Energy

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.

scholarly journals Energy-Efficient Power Allocation and Relay Selection Schemes for Relay-Assisted D2D Communications in 5G Wireless Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2865 ◽  
Author(s):  
Md Rahman ◽  
YoungDoo Lee ◽  
Insoo Koo
Keyword(s):  
Wireless Networks ◽  
Power Allocation ◽  
Relay Selection ◽  
Base Station ◽  
Data Rate ◽  
Transmission Power ◽  
D2d Communications ◽  
Long Distance ◽  
Inference System ◽  
Efficient Power

Device-to-device (D2D) communications allows user equipment (UE) that are in close proximity to communicate with each other directly without using a base station. Relay-assisted D2D (RA-D2D) communications in 5G networks can be applied to support long-distance users and to improve energy efficiency (EE) of the networks. In this paper, we first establish a multi-relay system model where the D2D UEs can communicate with each other by reusing only one cellular uplink resource. Then, we apply an adaptive neuro-fuzzy inference system (ANFIS) architecture to select the best D2D relay to forward D2D source information to the expected D2D destination. Efficient power allocation (PA) in the D2D source and the D2D relay are critical problems for operating such networks, since the data rate of the cellular uplink and the maximum transmission power of the system need to be satisfied. As is known, 5G wireless networks also aim for low energy consumption to better implement the Internet of Things (IoT). Consequently, in this paper, we also formulate a problem to find the optimal solutions for PA of the D2D source and the D2D relay in terms of maximizing the EE of RA-D2D communications to support applications in the emerging IoT. To solve the PA problems of RA-D2D communications, a particle swarm optimization algorithm is employed to maximize the EE of the RA-D2D communications while satisfying the transmission power constraints of the D2D users, minimum data rate of cellular uplink, and minimum signal-to-interference-plus-noise-ratio requirements of the D2D users. Simulation results reveal that the proposed relay selection and PA methods significantly improve EE more than existing schemes.

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.

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