Relay Selection and Scheduling for Millimeter Wave Backhaul in Urban Environments

Millimeter wave (mmWave) communication is a key enabling technology for 5G cellular systems. However, due to mmWave propagation characteristics, link length for very high rates is limited and will likely necessitate the use of relay nodes for longer-range ultra-high-speed backhaul communications. This paper investigates relay selection and scheduling to support high end-to-end throughput in mmWave relay-assisted backhaul networks in urban environments. A major challenge in urban environments is the presence of large obstacles (buildings) that block long line-of-sight paths, which arenecessary for very high capacity mmWave links. Using a 3D model for buildings targeted at urban environments, we provide optimal and efficient algorithms both for scheduling communications along a single mmWave relay-assisted path and for choosing the relay-assisted path with maximum throughput among all candidate paths connecting a given base station pair. In addition to proving optimality of these algorithms, we evaluate their performance through simulations based on a real urban topology. Simulation results show that our algorithms can produce short relay paths with end-to-end throughputs of around 10 Gbps and higher that are capable of providing virtual mmWave links for a wireless backhaul use case. Our algorithms improve throughput from 23% to 49% over a range of settings, as compared to average relay paths, and throughput can be more than doubled compared to some relay path choices with similar numbers of relays.

[1]  Ben Y. Zhao,et al.  Demystifying 60GHz outdoor picocells , 2014, MobiCom.

[2]  Rong Zheng,et al.  Toward Robust Relay Placement in 60 GHz mmWave Wireless Personal Area Networks with Directional Antenna , 2016, IEEE Transactions on Mobile Computing.

[3]  Randeep Bhatia,et al.  Joint Channel Assignment and Routing for Throughput Optimization in Multiradio Wireless Mesh Networks , 2005, IEEE Journal on Selected Areas in Communications.

[4]  E. Violette,et al.  Millimeter-wave propagation at street level in an urban environment , 1988 .

[5]  Li Su,et al.  Blockage Robust and Efficient Scheduling for Directional mmWave WPANs , 2015, IEEE Transactions on Vehicular Technology.

[6]  Catherine Rosenberg,et al.  Engineering Wireless Mesh Networks: Joint Scheduling, Routing, Power Control, and Rate Adaptation , 2010, IEEE/ACM Transactions on Networking.

[7]  Xuemin Shen,et al.  Efficient concurrent transmission scheduling for cooperative millimeter wave systems , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[8]  Bei Xie,et al.  Performance Study on Relay-Assisted Millimeter Wave Cellular Networks , 2016, 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring).

[9]  Mohsen Guizani,et al.  5G wireless backhaul networks: challenges and research advances , 2014, IEEE Network.

[10]  Bruce E. Hajek,et al.  Link scheduling in polynomial time , 1988, IEEE Trans. Inf. Theory.

[11]  Jeffrey G. Andrews,et al.  Tractable Model for Rate in Self-Backhauled Millimeter Wave Cellular Networks , 2014, IEEE Journal on Selected Areas in Communications.

[12]  Raghuraman Mudumbai,et al.  Interference Analysis for Highly Directional 60-GHz Mesh Networks: The Case for Rethinking Medium Access Control , 2011, IEEE/ACM Transactions on Networking.

[13]  Paolo Santi,et al.  Computationally efficient scheduling with the physical interference model for throughput improvement in wireless mesh networks , 2006, MobiCom '06.

[14]  Reinaldo A. Valenzuela,et al.  Gbps User Rates Using mmWave Relayed Backhaul With High-Gain Antennas , 2017, IEEE Journal on Selected Areas in Communications.

[15]  Mehdi Bennis,et al.  Beamwidth Optimization in Millimeter Wave Small Cell Networks with Relay Nodes: A Swarm Intelligence Approach , 2016, ArXiv.