Review for Capacity and Coverage Improvement in Aerially Controlled Heterogeneous Network

As a result of vast growth in wireless networks, there is an abrupt hike in user demands, constantly demanding surplus data as well as services. This abrupt demand creates a lot of burden on backbone-based macro-cellular networks because of inability and incapability in handling these high traffic demands. The possible solutions to handle these inefficiencies are to control the ground level data plane network from aerially such as Tethered balloon, loon technology, unmanned aerial vehicle (UAV) concept, etc. This one is a survey paper in which a network is proposed to enhance the capacity and to extend the coverage of heterogeneous network assisted by UAVs (i.e., handling of traffic demand inefficiency of traditional infrastructure-based macro-cellular networks is done through UAVs as intermediate aerial nodes in heterogeneous network). The paper investigates the problem related to high user demands-based UAVs-assisted heterogeneous network. A MIMO-OFDM approach is set to serve the higher data rates to the ground users. Multiple UAVs have been used to provide long distance connectivity and enhance the load balancing and traffic offload. This review paper hopes for the betterment in spectral efficiency, transmission range, and transmission delays.

[1]  Walid Saad,et al.  Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs , 2015, IEEE Transactions on Wireless Communications.

[2]  Ye Li OFDM for wireless communications: techniques for capacity improvement , 1998, ICCT'98. 1998 International Conference on Communication Technology. Proceedings (IEEE Cat. No.98EX243).

[3]  Rajesh Kumar,et al.  G-FANET: an ambient network formation between ground and flying ad hoc networks , 2017, Telecommun. Syst..

[4]  C. O. Ohaneme,et al.  Path loss Characterization of Wireless Propagation for South – South Region of Nigeria , 2011 .

[5]  Shashi B. Rana,et al.  Performance Evaluation of different Path Loss Models for Broadcasting applications , 2014 .

[6]  Sachin Kumar Gupta,et al.  Performance evaluation of broadband service delivery via tethered balloon technology , 2016, 2016 11th International Conference on Industrial and Information Systems (ICIIS).

[7]  Mohd. Samar Ansari,et al.  Tethered Balloon Technology in Design Solutions for Rescue and Relief Team Emergency Communication Services , 2018, Disaster Medicine and Public Health Preparedness.

[8]  Shahab Farazi,et al.  Optimal Power Allocation for MIMO Fully Cooperative Relay Broadcast Channels , 2014, IEEE Communications Letters.

[9]  Yongbin Wei,et al.  A survey on 3GPP heterogeneous networks , 2011, IEEE Wireless Communications.

[10]  Ismail Güvenç,et al.  UAV assisted heterogeneous networks for public safety communications , 2015, 2015 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).

[11]  Erik G. Larsson,et al.  Massive MIMO as enabler for communications with drone swarms , 2016, 2016 International Conference on Unmanned Aircraft Systems (ICUAS).

[12]  Jiming Chen,et al.  Q-Charge: A Quadcopter-Based Wireless Charging Platform for Large-Scale Sensing Applications , 2017, IEEE Network.

[13]  Siyi Wang,et al.  Performance analysis of micro unmanned airborne communication relays for cellular networks , 2014, 2014 9th International Symposium on Communication Systems, Networks & Digital Sign (CSNDSP).

[14]  Chia-Peng Lee,et al.  Modeling Delay Timer Algorithm for Handover Reduction in Heterogeneous Radio Access Networks , 2017, IEEE Transactions on Wireless Communications.

[15]  Khaled Ben Letaief,et al.  Throughput and Energy Efficiency Analysis of Small Cell Networks with Multi-Antenna Base Stations , 2013, IEEE Transactions on Wireless Communications.

[16]  Mehdi Bennis,et al.  UAV-Assisted Heterogeneous Networks for Capacity Enhancement , 2016, IEEE Communications Letters.

[17]  N. S. Rajput,et al.  Disaster Coverage Predication for the Emerging Tethered Balloon Technology: Capability for Preparedness, Detection, Mitigation, and Response , 2017, Disaster Medicine and Public Health Preparedness.

[18]  Roberto Sabatini,et al.  UAVs Assisted Delay Optimization in Heterogeneous Wireless Networks , 2016, IEEE Communications Letters.

[19]  Enrico Natalizio,et al.  UAV-assisted disaster management: Applications and open issues , 2016, 2016 International Conference on Computing, Networking and Communications (ICNC).

[20]  S. H. Alsamhi,et al.  An Intelligent Hand-off Algorithm to Enhance Quality of Service in High Altitude Platforms Using Neural Network , 2015, Wirel. Pers. Commun..

[21]  Kathiravan Srinivasan,et al.  Intelligent deployment of UAVs in 5G heterogeneous communication environment for improved coverage , 2017, J. Netw. Comput. Appl..

[22]  Rui Zhang,et al.  Wireless communications with unmanned aerial vehicles: opportunities and challenges , 2016, IEEE Communications Magazine.

[23]  Zuriati Zukarnain,et al.  Vertical handoff algorithm for different wireless technologies , 2017, PeerJ Prepr..

[24]  Sastri L. Kota,et al.  Hetnets - a new paradigm for increasing cellular capacity and coverage [Guest Editorial] , 2011 .

[25]  Lin Cai,et al.  UAV-Assisted Dynamic Coverage in a Heterogeneous Cellular System , 2017, IEEE Network.

[26]  Walid Saad,et al.  Efficient Deployment of Multiple Unmanned Aerial Vehicles for Optimal Wireless Coverage , 2016, IEEE Communications Letters.

[27]  Rajesh Kumar,et al.  A Cooperative Network Framework for Multi-UAV Guided Ground Ad Hoc Networks , 2014, Journal of Intelligent & Robotic Systems.

[28]  Qin Zhang,et al.  Capacity analysis of aerial small cells , 2017, 2017 IEEE International Conference on Communications (ICC).