scholarly journals Max-Min Rate Fairness Optimization for In-Band Full-Duplex IoT Networks: User Grouping and Power Control

2020 ◽  
Author(s):  
Ngo Tan Vu Khanh
Keyword(s):  
Optimal Solution ◽  
Base Station ◽  
Wireless Channel ◽  
Full Duplex ◽  
Full Potential ◽  
Traffic Demand ◽  
User Grouping ◽  
Grouping Method ◽  
Network Interference ◽  
Inner Approximation

The skyrocketing growth in the number of Internet of Things (IoT) devices will certainly pose a huge traffic demand for fifth-generation (5G) wireless networks and beyond. In-band full-duplex (IBFD), which is theoretically expected to double the spectral efficiency of a half-duplex (HD) wireless channel and to connect more devices, has been considered as a promising technology to accelerate the development of IoT. To exploit the full potential of IBFD, the key challenge is how to handle network interference (including self-interference, co-channel interference and multiuser interference) more effectively. In this paper, we propose a simple yet efficient user grouping method, where a base station (BS) serves strong downlink users and weak uplink users and vice versa in different frequency bands, mitigating severe network interference. We aim to maximize a minimum rate among all users subject to bandwidth and power constraints, which is formulated as a highly nonconvex optimization problem. By leveraging inner approximation framework, we develop a very efficient iterative algorithm to solve this problem, which guarantees at least a local optimal solution. Numerical results are provided to show not only the benefit of using full-duplex raido at BS, but also the advantage of the proposed user grouping method.

scholarly journals Max-Min Fairness and Sum Throughput Maximization for In-Band Full-Duplex IoT Networks: User Grouping, Bandwidth and Power Allocation

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2182
Author(s):  
Ngo Tan Vu Khanh ◽  
Van Dinh Nguyen
Keyword(s):  
Iterative Algorithm ◽  
Optimization Problem ◽  
Base Station ◽  
Throughput Maximization ◽  
Full Duplex ◽  
Quadratic Program ◽  
User Grouping ◽  
Grouping Method ◽  
Network Interference ◽  
Inner Approximation

The skyrocketing growth in the number of Internet of Things (IoT) devices has posed a huge traffic demand for fifth-generation (5G) wireless networks and beyond. In-band full-duplex (IBFD), which is theoretically expected to double the spectral efficiency of a half-duplex wireless channel and connect more devices, has been considered as a promising technology in order to accelerate the development of IoT. In order to exploit the full potential of IBFD, the key challenge is how to handle network interference (including self-interference, co-channel interference, and multiuser interference) more effectively. In this paper, we propose a simple yet efficient user grouping method, where a base station (BS) serves strong downlink users and weak uplink users and vice versa in different frequency bands, mitigating severe network interference. First, we aim to maximize a minimum rate among all of the users subject to bandwidth and power constraints, which is formulated as a nonconvex optimization problem. By leveraging the inner approximation framework, we develop a very efficient iterative algorithm for solving this problem, which guarantees at least a local optimal solution. The proposed iterative algorithm solves a simple convex program at each iteration, which can be further cast to a conic quadratic program. We then formulate the optimization problem of sum throughput maximization, which can be solved by the proposed algorithm after some slight modifications. Extensive numerical results are provided to show not only the benefit of using full-duplex radio at BS, but also the advantage of the proposed user grouping method.

scholarly journals Robust Beamforming Design for Secure V2X Downlink System with Wireless Information and Power Transfer under a Nonlinear Energy Harvesting Model

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3294 ◽  
Author(s):  
Shidang Li ◽  
Chunguo Li ◽  
Weiqiang Tan ◽  
Baofeng Ji ◽  
Luxi Yang
Keyword(s):  
Energy Harvesting ◽  
Traffic Safety ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Base Station ◽  
Power Splitting ◽  
Power Transfer ◽  
Vehicular Communication ◽  
Downlink System ◽  
Nonlinear Energy

Vehicle to everything (V2X) has been deemed a promising technology due to its potential to achieve traffic safety and efficiency. This paper considers a V2X downlink system with a simultaneous wireless information and power transfer (SWIPT) system where the base station not only conveys data and energy to two types of wireless vehicular receivers, such as one hybrid power-splitting vehicular receiver, and multiple energy vehicular receivers, but also prevents information from being intercepted by the potential eavesdroppers (idle energy vehicular receivers). Both the base station and the energy vehicular receivers are equipped with multiple antennas, whereas the information vehicular receiver is equipped with a single antenna. In particular, the imperfect channel state information (CSI) and the practical nonlinear energy harvesting (EH) model are taken into account. The non-convex optimization problem is formulated to maximize the minimum harvested energy power among the energy vehicular receivers satisfying the lowest harvested energy power threshold at the information vehicular receiver and secure vehicular communication requirements. In light of the intractability of the optimization problem, the semidefinite relaxation (SDR) technique and variable substitutions are applied, and the optimal solution is proven to be tight. A number of results demonstrate that the proposed robust secure beamforming scheme has better performance than other schemes.

scholarly journals Erasure channel modelling–based secure bit allocation schemes for multipath routing in wireless sensor networks

2016 ◽  
Vol 12 (12) ◽  
pp. 155014771668360
Author(s):  
Zhenhua Yuan ◽  
Chen Chen ◽  
Ye Jin
Keyword(s):  
Energy Efficiency ◽  
Channel Model ◽  
Multipath Routing ◽  
Optimal Solution ◽  
Wireless Channel ◽  
Bit Allocation ◽  
Wireless Sensor ◽  
Routing Scheme ◽  
Erasure Channel ◽  
Binary Erasure Channel

In this article, we study secure multipath routing with energy efficiency for a wireless sensor network in the presence of eavesdroppers. We consider two objectives: (1) the multipath routing scheme for maximising the energy efficiency with security constraints and (2) the multipath routing scheme for maximising the secrecy capacity. The binary erasure channel model is adopted to describe the wireless channel states among neighbouring nodes. Based on the binary erasure channel model, the problem of multipath routing degrades to a problem of bit allocation for each path. We formulate the problems and find that the problems are both quasi-convex. For the first one, it is a linear fractional optimisation problem. The optimal solution is obtained by the Charnes–Cooper transformation. For the second one, we propose an iterative algorithm to obtain the [Formula: see text]-optimal solution. The performance analysis shows that the probability of the secure bit allocation increases along with the number of multipaths and decreases along with the number of hops per path and eavesdroppers. Simulation results are presented to illustrate the proposed algorithms.

scholarly journals An efficient cryptographic technique using modified Diffie–Hellman in wireless sensor networks

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092577 ◽  
Author(s):  
Shahwar Ali ◽  
A Humaria ◽  
M Sher Ramzan ◽  
Imran Khan ◽  
Syed M Saqlain ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Security ◽  
Response Times ◽  
Base Station ◽  
Wireless Channel ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Key Generation ◽  
Diffie Hellman

In wireless sensor networks, the sensors transfer data through radio signals to a remote base station. Sensor nodes are used to sense environmental conditions such as temperature, strain, humidity, sound, vibration, and position. Data security is a major issue in wireless sensor networks since data travel over the naturally exposed wireless channel where malicious attackers may get access to critical information. The sensors in wireless sensor networks are resource-constrained devices whereas the existing data security approaches have complex security mechanisms with high computational and response times affecting the network lifetime. Furthermore, existing systems, such as secure efficient encryption algorithm, use the Diffie–Hellman approach for key generation and exchange; however, Diffie–Hellman is highly vulnerable to the man-in-the-middle attack. This article introduces a data security approach with less computational and response times based on a modified version of Diffie–Hellman. The Diffie–Hellman has been modified to secure it against attacks by generating a hash of each value that is transmitted over the network. The proposed approach has been analyzed for security against various attacks. Furthermore, it has also been analyzed in terms of encryption/decryption time, computation time, and key generation time for different sizes of data. The comparative analysis with the existing approaches shows that the proposed approach performs better in most of the cases.

Scheduling and Access Control for Wireless Connections with Throughput Guarantees

2010 ◽  
pp. 353-376
Author(s):  
Peifang Zhang ◽  
Scott Jordan
Keyword(s):  
Resource Allocation ◽  
Access Control ◽  
Utility Function ◽  
Base Station ◽  
Wireless Channel ◽  
Service Differentiation ◽  
Data Services ◽  
Slow Fading ◽  
Code Division Multiple ◽  
Music Streaming

Emerging wideband code division multiple access (WCDMA) data services will likely require resource allocation to ensure that throughput targets are met. Scheduling and access control can both be key components in this task. In this chapter, we introduce a two-layer scheduler and connection access controller that attempts to balance efficiency with fairness. We first propose a scheduler that takes advantage of variations in the wireless channel—both channel fluctuations in time for each user, and channel variations among multiple users at a particular time. By mixing a max-min policy with a policy of serving users with relatively good channels, the scheduler can achieve individual average throughput targets in a manner that encourages system efficiency. We then propose a two-layer algorithm that offers targeted throughput for interactive nomadic data streams, such as video or music streaming. The design purpose is to provide users with service differentiation, which lays the groundwork for network optimization in terms of capacity or utility, and can be easily extended to revenue maximization. Upon the request of a data stream connection, a target throughput is negotiated between the user and the network/base station. The network attempts to achieve the throughput targets over the duration of each individual connection by maximizing a system objective based on users’ satisfaction that is represented by a utility function. We assume that a users’ utility function depends not only on the throughput target but also on final achieved throughput. The algorithm integrates connection access control and resource allocation per connection request with rate scheduling on a per frame basis adaptive to slow fading. Through numerical analysis, the proposed joint scheduler and connection access controller is shown to achieve the design goals.

Multi-Objective Optimization Algorithm Design and Implementation of Mobile Base Station Site Selection

2010 ◽  
Vol 29-32 ◽  
pp. 2496-2502
Author(s):  
Min Wang ◽  
Jun Tang
Keyword(s):  
Site Selection ◽  
Engineering Application ◽  
Optimal Solution ◽  
Base Station ◽  
Pareto Optimal Solution ◽  
Antibody Concentration ◽  
Pareto Optimal ◽  
Memory Cells ◽  
Multi Objective Optimization ◽  
Multi Objective

The number of base station location impact the network quality of service. A new method is proposed based on immune genetic algorithm for site selection. The mathematical model of multi-objective optimization problem for base station selection and the realization of the process were given. The use of antibody concentration selection ensures the diversity of the antibody and avoiding the premature convergence, and the use of memory cells to store Pareto optimal solution of each generation. A exclusion algorithm of neighboring memory cells on the updating and deleting to ensure that the Pareto optimal solution set of the distribution. The experiments results show that the algorithm can effectively find a number of possible base station and provide a solution for the practical engineering application.

Performance Improvement of MU-MIMO System by Optimizing the K-Factor for the K-Mean User Grouping Algorithm

2016 ◽  
Vol 5 (3) ◽  
pp. 89
Author(s):  
Ankush Kansal ◽  
Pawandeep Singh
Keyword(s):  
Mimo System ◽  
Access Point ◽  
Base Station ◽  
Optimum Number ◽  
Multiuser Mimo ◽  
User Grouping ◽  
Single Antenna ◽  
User Groups ◽  
Sum Rate ◽  
Grouping Algorithm

<p>In this paper, downlink multiuser-MIMO system with large number of transmitting antennas at the base station and R user terminals each having single antenna is considered. According to this design, an access point communicates with large number of users in the Rayleigh fading scenario. Due to large number of users, it becomes difficult to accommodate all of them in the system simultaneously. So, a user grouping technique known as K-mean clustering is used, such that a group of users with similar conditions at that particular time are served together. While making groups, the interference is surely reduced but the number of users being served at a time also reduces. So, it is necessary to make out the balance such that the performance of the system is maintained while accommodating maximum number of users. So, optimum number of user groups needs to be formed. The results show that when groups are increased from two till four sum rate increases but when five groups are made the sum rate decreases to a point but, is still higher than two groups.</p><p> </p>

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