Ultra-Reliable Communication in 5G mmWave Networks: A Risk-Sensitive Approach

In this letter, we investigate the problem of providing gigabit wireless access with reliable communication in 5G millimeter-wave (mmWave) massive multiple-input multiple-output networks. In contrast to the classical network design based on average metrics, we propose a distributed risk-sensitive reinforcement learning-based framework to jointly optimize the beamwidth and transmit power, while taking into account the sensitivity of mmWave links due to blockage. Numerical results show that our proposed algorithm achieves more than 9 Gbps of user throughput with a guaranteed probability of 90%, whereas the baselines guarantee less than 7.5 Gbps. More importantly, there exists a rate-reliability-network density tradeoff, in which as the user density increases from 16 to 96 per km2, the fraction of users that achieves 4 Gbps is reduced by 11.61% and 39.11% in the proposed and the baseline models, respectively.

[1]  Theodore S. Rappaport,et al.  Millimeter Wave Mobile Communications for 5G Cellular: It Will Work! , 2013, IEEE Access.

[2]  H. Vincent Poor,et al.  Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale , 2018, Proceedings of the IEEE.

[3]  Jia Liu,et al.  Hybrid-Beamforming-Based Millimeter-Wave Cellular Network Optimization , 2019, IEEE Journal on Selected Areas in Communications.

[4]  Vincent K. N. Lau,et al.  Hierarchical Interference Mitigation for Massive MIMO Cellular Networks , 2013, IEEE Transactions on Signal Processing.

[5]  Matti Latva-aho,et al.  Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks , 2016, ArXiv.

[6]  Ralph Neuneier,et al.  Risk-Sensitive Reinforcement Learning , 1998, Machine Learning.

[7]  Derrick Wing Kwan Ng,et al.  Secure Massive MIMO Transmission With an Active Eavesdropper , 2015, IEEE Transactions on Information Theory.

[8]  Klaus Obermayer,et al.  Risk-Sensitive Reinforcement Learning , 2013, Neural Computation.

[9]  Elizabeth S. Bentley,et al.  Hybrid-beamforming-based millimeter-wave cellular network optimization , 2017, 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[10]  Matti Latva-aho,et al.  Path selection and rate allocation in self-backhauled mmWave networks , 2018, 2018 IEEE Wireless Communications and Networking Conference (WCNC).

[11]  Mehdi Bennis,et al.  Design and Deployment of Small Cell Networks , 2015 .

[12]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[13]  Robert W. Heath,et al.  Millimeter wave cellular channel models for system evaluation , 2014, 2014 International Conference on Computing, Networking and Communications (ICNC).

[14]  Ming Xiao,et al.  Low-Latency Millimeter-Wave Communications: Traffic Dispersion or Network Densification? , 2017, IEEE Transactions on Communications.

[15]  Erik G. Ström,et al.  Ultra-Reliable Low-Latency Communication (URLLC): Principles and Building Blocks , 2017, ArXiv.

[16]  Samson Lasaulce,et al.  Game Theory and Learning for Wireless Networks: Fundamentals and Applications , 2011 .

[17]  Zhu Han,et al.  Self-Organization in Small Cell Networks: A Reinforcement Learning Approach , 2013, IEEE Transactions on Wireless Communications.

[18]  Danilo De Donno,et al.  Tracking mm-Wave channel dynamics: Fast beam training strategies under mobility , 2016, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[19]  Matti Latva-aho,et al.  Joint Load Balancing and Interference Mitigation in 5G Heterogeneous Networks , 2016, IEEE Transactions on Wireless Communications.

[20]  Erik G. Ström,et al.  Wireless Access for Ultra-Reliable Low-Latency Communication: Principles and Building Blocks , 2018, IEEE Network.

[21]  Jeffrey G. Andrews,et al.  What Will 5G Be? , 2014, IEEE Journal on Selected Areas in Communications.

[22]  Euhanna Ghadimi,et al.  A reinforcement learning approach to power control and rate adaptation in cellular networks , 2016, 2017 IEEE International Conference on Communications (ICC).

[23]  Matti Latva-aho,et al.  Ultra-Reliable and Low Latency Communication in mmWave-Enabled Massive MIMO Networks , 2017, IEEE Communications Letters.