Performance Evaluation of Variable Bandwidth Channel Allocation Scheme in Multiple Subcarrier Multiple Access

Multiple Subcarrier Multiple Access (MSMA) enables concurrent sensor data streamings from multiple wireless and batteryless sensors using the principle of subcarrier backscatter used extensively in passive RFID. Since the interference cancellation performance of MSMA depends on the Signal to Interference plus Noise Ratio of each subcarrier, the choice of channel allocation scheme is essential. Since the channel allocation is a combinatorial problem, obtaining the true optimal allocation requires a vast amount of examinations which is impracticable in a system where we have tens of sensor RF tags. It is particularly true when we have variable distance and variable bandwidth sensor RF tags. This paper proposes a channel allocation scheme in the variable distance and variable bandwidth MSMA system based on a newly introduced performance index, total contamination power, to prioritize indecision cases. The performance of the proposal is evaluated with existing methods in terms of average communication capacity and system fairness using MATLAB Monte Carlo simulation to reveal its advantage. The accuracy of the simulation is also verified with the result obtained from the brute force method

Wireless Communication using Unmanned Aerial Vehicles (UAVs): Optimal Transport Theory for Hover Time Optimization

In this paper, the effective use of flight-time constrained unmanned aerial vehicles (UAVs) as flying base stations that can provide wireless service to ground users is investigated. In particular, a novel framework for optimizing the performance of such UAV-based wireless systems in terms of the average number of bits (data service) transmitted to users as well as UAVs' hover duration (i.e. flight time) is proposed. In the considered model, UAVs hover over a given geographical area to serve ground users that are distributed within the area based on an arbitrary spatial distribution function. In this case, two practical scenarios are considered. In the first scenario, based on the maximum possible hover times of UAVs, the average data service delivered to the users under a fair resource allocation scheme is maximized by finding the optimal cell partitions associated to the UAVs. Using the mathematical framework of optimal transport theory, a gradient-based algorithm is proposed for optimally partitioning the geographical area based on the users' distribution, hover times, and locations of the UAVs. In the second scenario, given the load requirements of ground users, the minimum average hover time that the UAVs need for completely servicing their ground users is derived. To this end, first, an optimal bandwidth allocation scheme for serving the users is proposed. Then, given this optimal bandwidth allocation, the optimal cell partitions associated with the UAVs are derived by exploiting the optimal transport theory. Results show that our proposed cell partitioning approach leads to a significantly higher fairness among the users compared to the classical weighted Voronoi diagram. In addition, our results reveal an inherent tradeoff between the hover time of UAVs and bandwidth efficiency while serving the ground users

Improving Energy Efficiency for IoT Communications in 5G Networks

Increase in number of Internet of Things (IoT) devices is quickly changing how mobile networks are being used by shifting more usage to uplink transmissions rather than downlink transmissions. Currently, mobile network uplinks utilize Single Carrier Frequency Division Multiple Access (SC-FDMA) schemes due to the low Peak to Average Power Ratio (PAPR) when compared to Orthogonal Frequency Division Multiple Access (OFDMA). In an IoT perspective, power ratios are highly important in effective battery usage since devices are typically resource-constrained. Fifth Generation (5G) mobile networks are believed to be the future standard network that will handle the influx of IoT device uplinks while preserving the quality of service (QoS) that current Long Term Evolution Advanced (LTE-A) networks provide. In this paper, the Enhanced OEA algorithm was proposed and simulations showed a reduction in the device energy consumption and an increase in the power efficiency of uplink transmissions while preserving the QoS rate provided with SC-FDMA in 5G networks. Furthermore, the computational complexity was reduced through insertion of a sorting step prior to resource allocation

Wireless Communication using Unmanned Aerial Vehicles (UAVs): Optimal Transport Theory for Hover Time Optimization

In this paper, the effective use of flight-time constrained unmanned aerial vehicles (UAVs) as flying base stations that can provide wireless service to ground users is investigated. In particular, a novel framework for optimizing the performance of such UAV-based wireless systems in terms of the average number of bits (data service) transmitted to users as well as UAVs' hover duration (i.e. flight time) is proposed. In the considered model, UAVs hover over a given geographical area to serve ground users that are distributed within the area based on an arbitrary spatial distribution function. In this case, two practical scenarios are considered. In the first scenario, based on the maximum possible hover times of UAVs, the average data service delivered to the users under a fair resource allocation scheme is maximized by finding the optimal cell partitions associated to the UAVs. Using the mathematical framework of optimal transport theory, a gradient-based algorithm is proposed for optimally partitioning the geographical area based on the users' distribution, hover times, and locations of the UAVs. In the second scenario, given the load requirements of ground users, the minimum average hover time that the UAVs need for completely servicing their ground users is derived. To this end, first, an optimal bandwidth allocation scheme for serving the users is proposed. Then, given this optimal bandwidth allocation, the optimal cell partitions associated with the UAVs are derived by exploiting the optimal transport theory. Results show that our proposed cell partitioning approach leads to a significantly higher fairness among the users compared to the classical weighted Voronoi diagram. In addition, our results reveal an inherent tradeoff between the hover time of UAVs and bandwidth efficiency while serving the ground users