Title
An underlay communication channel for 5G cognitive mesh networks: Packet design, implementation, analysis, and experimental results
Abstract
This paper proposes and presents the design and implementation of an underlay communication channel (UCC) for 5G cognitive mesh networks. The UCC builds its waveform based on filter bank multicarrier spread spectrum (FB-MC-SS) signaling. The use of this novel spread spectrum signaling allows the device-to-device (D2D) user equipments (UEs) to communicate at a level well below noise temperature and hence, minimize taxation on macro-cell/small-cell base stations and their UEs in 5G wireless systems. Moreover, the use of filter banks allows us to avoid those portions of the spectrum that are in use by macro-cell and small-cell users. Hence, both D2D-to-cellular and cellular-to-D2D interference will be very close to none. We propose a specific packet for UCC and develop algorithms for packet detection, timing acquisition and tracking, as well as channel estimation and equalization. We also present the detail of an implementation of the proposed transceiver on a software radio platform and compare our experimental results with those from a theoretical analysis of our packet detection algorithm.
Year
DOI
Venue
2016
10.1109/ICCW.2016.7503836
2016 IEEE International Conference on Communications Workshops (ICC)
Keywords
Field
DocType
transceiver,packet detection algorithm,software radio platform,channel equalization,channel estimation,timing acquisition,D2D-to-cellular interference,cellular-to-D2D interference,5G wireless systems,taxation minimization,macro-cell base station,small-cell base stations,noise temperature,D2D UEs,device-to-device user equipments,FB-MC-SS signaling,filter bank multicarrier spread spectrum signaling,UCC,packet design,5G cognitive mesh networks,underlay communication channel
Mesh networking,Base station,Computer science,Software-defined radio,Network packet,Computer network,Communication channel,Real-time computing,Underlay,Spread spectrum,Cognitive network
Conference
ISSN
ISBN
Citations 
2164-7038
978-1-5090-0449-2
2
PageRank 
References 
Authors
0.38
19
10