An Equilibrium Analysis of a Secondary Mobile Data-Share Market

Internet service providers are offering shared data plans where multiple users may buy and sell their overage data in a secondary market managed by the ISP. We propose a game-theoretic approach to a software-defined network for modeling this wireless data exchange market: a fully connected, non-cooperative network. We identify and define the rules for the underlying progressive second price (PSP) auction for the respective network and market structure. We allow for a single degree of statistical freedom—the reserve price—and show that the secondary data exchange market allows for greater flexibility in the acquisition decision making of mechanism design. We have designed a framework to optimize the strategy space using the elasticity of supply and demand. Wireless users are modeled as a distribution of buyers and sellers with normal incentives. Our derivation of a buyer-response strategy for wireless users based on second price market dynamics leads us to prove the existence of a balanced pricing scheme. We examine shifts in the market price function and prove that our network upholds the desired properties for optimization with respect to software-defined networks and prove the existence of a Nash equilibrium in the overlying non-cooperative game.

Investigation of Bi-Directional LSTM deep learning-based ubiquitous MIMO uplink NOMA detection for military application considering Robust channel conditions

Ubiquitous multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks (UMNs) have emerged as an important technology for enabling security and other applications that need continuous monitoring. Their implementation, however, could be obstructed by the limited bandwidth available due to many wireless users. In this paper, bidirectional long short-term memory (LSTM)-based MIMO-NOMA detector is analyzed considering imperfect successive interference cancelation (SIC). Simulation results demonstrate that the traditional SIC MIMO-NOMA scheme achieves 15 dB, and the deep learning (DL) MIMO-NOMA scheme achieves 11 dB for [Formula: see text] number of iterations. There is a gap of 4 dB which means that the DL-based MIMO-NOMA performs better than the traditional SIC MIMO-NOMA techniques. It has been observed that when the channel error factor increases from 0 to 1, the performance of DL decreases significantly. For the channel error factor value less than 0.07, the DL detector performance much better than the SIC detector even though the perfect channel state information (CSI) is considered. The DL detector’s performance decreases significantly where variations between the actual and expected channel states occurred, although the DL-based detectors’ performance was able to sustain its predominance within a specified tolerance range.

A Centralized Win-Win Cooperative Framework for Wi-Fi and 5G Radio Access Networks

Cooperation to access wireless networks is a key approach towards optimizing the use of finite radio spectrum resources in overcrowded unlicensed bands and to help satisfy the expectations of wireless users in terms of high data rates and low latency. Although solutions that advocate this approach have been widely proposed in the literature, they still do not consider a number of aspects that can improve the performance of the users’ connections, such as the inclusion of (1) cooperation among network operators and (2) users’ quality requirements based on their applications. To fill this gap, in this paper we propose a centralized framework that is aimed at providing a “win-win” cooperation among Wi-Fi and cellular networks, which takes into account 5G technologies and users’ requirements in terms of Quality of Service (QoS). Moreover, the framework is supported by smart Radio Access Technology (RAT) selection mechanisms that orchestrate the connection of the clients to the networks. In particular, we discuss details on the design of the proposed framework, the motivation behind its implementation, the main novelties, its feasibility, and the main components. In order to demonstrate the benefits of our solution, we illustrate efficiency results achieved through the simulation of a smart RAT selection algorithm in a realistic scenario, which mimics the proposed “win-win” cooperation between Wi-Fi and cellular 5G networks, and we also discuss potential benefits for wireless and mobile network operators.

EMI-aware central processing point deployment in wireless networks for e-healthcare services.

In this thesis, we introduce an approach to jointly minimizing energy consumption of wireless transmitters and the harmful interference on sensitive medical devices, and optimizing the central controller placement for collecting data from transmitters. More specifically, a multi-objective non-convex mixed-integer non-linear programming (MINLP) problem is defined and formulated to optimize transmit power of wireless users and CPP deployment along with guaranteeing minimized EMI to comply with the immunity level of medical devices. To solve this problem, an important step is to convexify it. Then we propose the use of a standard branch-and-bound algorithm. Also the program is coded in MATLAB with the help of OPTItoolbox to find the optimal solution. To conduct a numerical result analysis, we considered different cases within a single floor of a hospital and a few scenarios for a two-story hospital building. The values of different variables are changed throughout the simulation and the results are compared. These variables include immunity level of sensitive medical devices, maximum transmission power of wireless users, floor attenuation factor, etc. Our results show the improvement in throughput and guaranteed immunity for medical devices, when the proposed formulation is deployed along with a branch-and-bound algorithm.

EMI-aware central processing point deployment in wireless networks for e-healthcare services.

In this thesis, we introduce an approach to jointly minimizing energy consumption of wireless transmitters and the harmful interference on sensitive medical devices, and optimizing the central controller placement for collecting data from transmitters. More specifically, a multi-objective non-convex mixed-integer non-linear programming (MINLP) problem is defined and formulated to optimize transmit power of wireless users and CPP deployment along with guaranteeing minimized EMI to comply with the immunity level of medical devices. To solve this problem, an important step is to convexify it. Then we propose the use of a standard branch-and-bound algorithm. Also the program is coded in MATLAB with the help of OPTItoolbox to find the optimal solution. To conduct a numerical result analysis, we considered different cases within a single floor of a hospital and a few scenarios for a two-story hospital building. The values of different variables are changed throughout the simulation and the results are compared. These variables include immunity level of sensitive medical devices, maximum transmission power of wireless users, floor attenuation factor, etc. Our results show the improvement in throughput and guaranteed immunity for medical devices, when the proposed formulation is deployed along with a branch-and-bound algorithm.

Genetic Optimization for Dynamic Spectrum Sharing in Cognitive Radio Networks in Interweave Mode

Dynamic spectrum sharing among the wireless users is growing demand to increase the spectrum usage. In this paper,, based upon a pricing strategy to overcome the drawbacks of the traditional mechanisms. The proposed mechanism enhances the spectral efficiency of the cognitive users and also motivates the primary users to lease the bands to the cognitive users, with increased primary user revenue. Fairness among cognitive users is also ensured in this mechanism.. Simulation results show that our mechanism increases the spectral efficiency of cognitive users and the revenue of primary users.

A Bidirectional Hybrid WDM-PON with High Data Rate Transmission for Wired and Wireless Users in Long-Reach with Enriched Noise Tolerance Capacity against Rayleigh Backscattering

Transportation of 10 Gbps, 10 Gbps/40 GHz, 10 Gbps/200 MHz data for downlink (DL) and 6 Gbps data for uplink (UL) transmission with Rayleigh backscattering (RB) noise mitigation for wired and wireless users even in radio-frequency sensitive areas have been proposed and investigated. A 2×2 wavelength-division-multiplexing mux/demux is employed to separate DL and UL to avoid RB noise. Power penalty of < 1 dB at Bit error rate value of 10−9 and clear eye-diagrams express the reliability and fruitfulness of the proposed network.

A Bidirectional Hybrid WDM-PON with High Data Rate Transmission for Wired and Wireless Users in Long-Reach with Enriched Noise Tolerance Capacity against Rayleigh Backscattering

Transportation of 10 Gbps, 10 Gbps/40 GHz, 10 Gbps/200 MHz data for downlink (DL) and 6 Gbps data for uplink (UL) transmission with Rayleigh backscattering (RB) noise mitigation for wired and wireless users even in radio-frequency sensitive areas have been proposed and investigated. A 2×2 wavelength-division-multiplexing mux/demux is employed to separate DL and UL to avoid RB noise. Power penalty of < 1 dB at Bit error rate value of 10−9 and clear eye-diagrams express the reliability and fruitfulness of the proposed network.

Management of Internet Bandwidth Implementing CoovaChilli and Free Radius

With rapid growth in popularity and use of Internet in academic institutions, the institutions are struggling to keep up with the demand. They need capability to effectively control, monitor and optimize the available bandwidth to ensure good service at optimum cost. This paper has described implementation of Coovachilli and free radius for management of internet bandwidth in academic institutions. During this research, freeware tools such as Freeradius and CoovaChilli have been used to manage Internet bandwidth on a per-user basis based on user credentials. The mechanisms have been used to control bandwidth of Wireless users. Same can be used for wired connections also. When a user tries to connect, the user is redirected to a captive portal under CoovaChilli. There the user provides login and password. Based on the credentials thus provided, CoovaChilli checks identity with the Freeradius. If authorized, the client is allowed access with the bandwidth as mentioned in the profile of the user in WISPr attributes define in Radreply table of Freeradius. When the user is not authorized, CoovaChilli sends an error message. This paper demonstrates that bandwidth can be effectively monitored, managed and optimized by using cost-effective open-source tools in the existing network scenario of the institution.

New Courteous Algorithm for Uplink Scheduling in LTE-Advanced and 5G Networks

The fast evolution of the number of wireless users and the emergence of new multimedia services have motivated third-generation partnership project (3GPP) to develop new radio access technologies. Thus, the carrier aggregation (CA) was introduced from version 10 long-term evolution (LTE), known as long-term evolution-advanced (LTE-A), to meet the increasing demands in terms of throughput and bandwidth and to ensure the Quality of Service (QoS) for different classes of bearers in LTE networks. However, such solution stills inefficient until implementing good resources management scheme. Several scheduling mechanisms have been proposed in the literature, to guarantee the QoS of different classes of bearers in LTE-A and 5G networks. Nevertheless, most of them promote high-priority bearers. In this study, a new approach of uplink scheduling resources has been developed. It aims to ensure service fairness of different traffic classes that allocates bearers over LTE-A and 5G networks. Also, it raises the number of admitted users in the network by increasing the number of admitted bearers through a dynamic management of service priorities. In fact, the low-priority traffic classes, using low-priority bearers, are favoured during a specific time interval, based on the average waiting time for each class. Simulation results show that the QoS parameters were much improved for the low-priority classes without significantly affecting the QoS of high priority ones.