Intelligent Interference Management in UAV-Based HetNets

Unmanned aerial vehicles (UAVs) can play a key role in meeting certain demands of cellular networks. UAVs can be used not only as user equipment (UE) in cellular networks but also as mobile base stations (BSs) wherein they can either augment conventional BSs by adapting their position to serve the changing traffic and connectivity demands or temporarily replace BSs that are damaged due to natural disasters. The flexibility of UAVs allows them to provide coverage to UEs in hot-spots, at cell-edges, in coverage holes, or regions with scarce cellular infrastructure. In this work, we study how UAV locations and other cellular parameters may be optimized in such scenarios to maximize the spectral efficiency (SE) of the network. We compare the performance of machine learning (ML) techniques with conventional optimization approaches. We found that, on an average, a double deep Q learning approach can achieve 93.46% of the optimal median SE and 95.83% of the optimal mean SE. A simple greedy approach, which tunes the parameters of each BS and UAV independently, performed very well in all the cases that we tested. These computationally efficient approaches can be utilized to enhance the network performance in existing cellular networks.

MiA-CODER: A Multi-Intelligent Agent-Enabled Reinforcement Learning for Accurate Coverage Hole Detection and Recovery in Unequal Cluster-Tree-Based QoSensing WSN

Coverage is an important factor for the effective transmission of data in the wireless sensor networks. Normally, the formation of coverage holes in the network deprives its performance and reduces the lifetime of the network. In this paper, a multi-intelligent agent enabled reinforcement learning-based coverage hole detection and recovery (MiA-CODER) is proposed in order to overcome the existing challenges related to coverage of the network. Initially, the formation of coverage holes is prevented by optimizing the energy consumption in the network. This is performed by constructing the unequal Sierpinski cluster-tree topology (USCT) and the cluster head is selected by implementing multi-objective black widow optimization (MoBWo) to facilitate the effective transmission of data. Further, the energy consumption of the nodes is minimized by performing dynamic sleep scheduling in which Tsallis entropy enabled Bayesian probability (TE2BP) is implemented to switch the nodes between active and sleep mode. Then, the coverage hole detection and repair are carried out in which the detection of coverage holes if any, both inside the cluster and between the clusters, is completed by using the virtual sector-based hole detection (ViSHD) protocol. Once the detection is over, the BS starts the hole repair process by using a multi-agent SARSA algorithm which selects the optimal mobile node and replaces it to cover the hole. By doing so, the coverage of the network is enhanced and better QoSensing is achieved. The proposed approach is simulated in NS 3.26 and evaluated in terms of coverage rate, number of dead nodes, average energy consumption and throughput.

UAV-Based Intelligent Transportation System for Emergency Reporting in Coverage Holes of Wireless Networks

During critical moments, disaster and accident victims may not be able to request help from the emergency response center. This may happen when the victim’s vehicle is located within a coverage hole in a wireless network. In this paper, we adopt an unmanned aerial vehicle (UAV) to work as an automatic emergency dispatcher for a user in a vehicle facing a critical condition. Given that the UAV is located within a coverage hole and a predetermined critical condition is detected, the UAV becomes airborne and dispatches distress messages to a communication network. We propose to use a path loss map for UAV trajectory design, and we formulate our problem mathematically as an Integer Linear Program (ILP). Our goals are to minimize the distress messages delivery time and the UAV’s mission completion time. Due to the difficulty of obtaining the optimal solution when the scale of the problem is large, we proposed an efficient algorithm that reduces the computational time significantly. We simulate our problem under different scenarios and settings, and study the performance of our proposed algorithm.

A Robust Fault-Tolerance Scheme with Coverage Preservation for Planar Topology based WSN

Maintaining prolonged service lifetime and adequate quality of sensing coverage are the key challenges in constructing Wireless Sensor Network (WSN) based applications. As such networks usually operate in inhospitable and hostile environment, failures are ineludible and providing resilience is a necessity. However, it is challenging to satisfy the conflicting problems of enhancing energy efficiency and fault tolerance simultaneously. Fault-tolerance is a significant requirement while designing WSN. It is crucial to detect the failures in advance and take necessary measures to maintain durable and efficient functioning of the network. Generally, in the existing face structured WSNs, node faults and failures can induce the formation of coverage holes, disrupt the face structure and consequently curtail the application performance. The coverage quality will affect the monitoring effectiveness of tracking applications, e.g., a moving target tracking. Moreover, node failures can cause the network to be partitioned, further reducing the accuracy in tracking. In this paper, we propose a robust fault-tolerance scheme with coverage preservation using a face structured WSN topology (FCAFT ). The key objective of the proposed FCAFT scheme is to sustain the performance of the network by timely healing the faults in the network, to enhance the durability and reliability of the WSN. The results of simulation and comparison with existing methods reveal that FCAFT is efficacious in sustaining the coverage and enhancing the service lifetime of WSN, which is a necessity for critical monitoring and tracking applications of WSNs.

An intelligent algorithm to reduce and eliminate coverage holes in the mobile network

The need for services in the world of telecommunications and the prosperity and rapid development of this sector around the world has led mobile phone companies to compete to provide the best services to customers. One of these devices used for communications is the mobile phone. The mobile phone is simply an electronic device that is mainly serving unwired telecommunications through a cellular network of particular base stations known as cell sites. There are many obstacles or problems in the telecommunication field, and the relevant institutions and companies should find solutions to these obstacles and problems. One of these obstacles in telecommunications is the coverage holes. Coverage holes occur when the location of the mobile phone is set in midway between the two base transceiver stations (BTSs). This causes an abnormal interruption in communication until the user crosses the coverage holes area. This paper presents an intelligent algorithm as a set of technical steps that can be used to improve the communication services of the mobile phone network and to solve the communication problems via the reduction of the coverage holes between two BTSs. It suggests a method that could alleviate this problem using a strategy that reduces the coverage holes by developing an intelligent algorithm system to receive signal strength indicators and use AT command “+CREG” to disconnect and reconnect to available BTS within an acceptable energy level. As a result, the connection turned from marginal into good connection.

Power Control and Clustering-Based Interference Management for UAV-Assisted Networks

Unmanned Aerial Vehicle (UAV) has been widely used in various applications of wireless network. A system of UAVs has the function of collecting data, offloading traffic for ground Base Stations (BSs) and illuminating coverage holes. However, inter-UAV interference is easily introduced because of the huge number of LoS paths in the air-to-ground channel. In this paper, we propose an interference management framework for UAV-assisted networks, consisting of two main modules: power control and UAV clustering. The power control is executed first to adjust the power levels of UAVs. We model the problem of power control for UAV networks as a non-cooperative game which is proved to be an exact potential game and the Nash equilibrium is reached. Next, to further improve system user rate, coordinated multi-point (CoMP) technique is implemented. The cooperative UAV sets are established to serve users and thus transforming the interfering links into useful links. Affinity propagation is applied to build clusters of UAVs based on the interference strength. Simulation results show that the proposed algorithm integrating power control with CoMP can effectively reduce the interference and improve system sum-rate, compared to Non-CoMP scenario. The law of cluster formation is also obtained where the average cluster size and the number of clusters are affected by inter-UAV distance.

Analysis of Coverage Hole Problem for Detection and Restoration in Wireless Sensor Networks

Wireless Sensor Network is an evolving technology which has gained massive attention in the past few years. Researchers are focusing on designing the wireless sensors more and more intelligent and efficient to make our life extremely comfortable and luxurious. Wireless Sensor Networks are used in bridge monitoring, smart agriculture, health care monitoring, landslide detection, biodiversity mapping, etc. Coverage holes are one of the key problems which occur in the Wireless Sensor Network accidentally and they cannot be neglected. The coverage holes appear in the sensing field due to poor instalment, node failure, battery depletion, etc. In this paper, detection and restoration method based on Hybrid Wireless Sensor Networks and Static Wireless Sensor Networks are discussed. Further, we have analysed the performances of these networks using Unequal Clustering and Connected Graphand Novel Energy Efficient Clustering Protocol techniques. The simulation results revealed that for Hybrid Wireless Sensor Networks, Unequal Clustering and Connected Graph protocol is best suitable and for Static Wireless Sensor Networks, Novel Energy Efficient Clustering Protocoltechnique will be preferred.