Exploiting Diversity for Ultra-Reliable and Low-Latency Wireless Control

This paper introduces a wireless communication protocol for industrial control systems that uses channel quality awareness to dynamically create network-device cooperation and assist the nodes in momentary poor channel conditions. To that point, channel state information is used to identify nodes with strong and weak channel conditions. We show that strong nodes in the network are best to be served in a single-hop transmission with transmission rate adapted to their instantaneous channel conditions. Meanwhile, the remainder of time-frequency resources is used to serve the nodes with weak channel condition using a two-hop transmission with cooperative communication among all the nodes to meet the target reliability in their communication with the controller. We formulate the achievable multi-user and multi-antenna diversity gain in the low-latency regime, and propose a new scheme for exploiting those on-demand, in favor of reliability and efficiency. The proposed transmission scheme is therefore dubbed adaptive network-device cooperation (ANDCoop), since it is able to adaptively allocate cooperation resources while enjoying the multi-user diversity gain of the network. We formulate the optimization problem of associating nodes to each group and dividing resources between the two groups. Numerical solutions show significant improvement in spectral efficiency and system reliability compared to the existing schemes in the literature. System design incorporating the proposed transmission strategy can thus reduce infrastructure cost for future private wireless networks.

[1]  Paul J. M. Havinga,et al.  Wireless Industrial Monitoring and Control Networks: The Journey So Far and the Road Ahead , 2012, J. Sens. Actuator Networks.

[2]  Gianluca Cena,et al.  Hybrid wired/wireless networks for real-time communications , 2008, IEEE Industrial Electronics Magazine.

[3]  Harish Viswanathan,et al.  Variable-rate ultra-reliable and low-latency communication for industrial automation , 2018, 2018 52nd Annual Conference on Information Sciences and Systems (CISS).

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

[5]  Jeffrey G. Andrews,et al.  Outage of Periodic Downlink Wireless Networks With Hard Deadlines , 2018, IEEE Transactions on Communications.

[6]  Nurul H. Mahmood,et al.  5G Centralized Multi-Cell Scheduling for URLLC: Algorithms and System-Level Performance , 2018, IEEE Access.

[7]  Anant Sahai,et al.  Cooperative communication for high-reliability low-latency wireless control , 2015, 2015 IEEE International Conference on Communications (ICC).

[8]  Takayuki Nishio,et al.  Extreme URLLC: Vision, Challenges, and Key Enablers , 2020, ArXiv.

[9]  Harish Viswanathan,et al.  Analysis of Feedback Error in Automatic Repeat reQuest , 2017, ArXiv.

[10]  H. Vincent Poor,et al.  Channel Coding Rate in the Finite Blocklength Regime , 2010, IEEE Transactions on Information Theory.

[11]  Lei Zhao,et al.  Diversity and Multiplexing Tradeoff in General Fading Channels , 2007, 2006 40th Annual Conference on Information Sciences and Systems.

[12]  Giuseppe Durisi,et al.  Quasi-Static Multiple-Antenna Fading Channels at Finite Blocklength , 2013, IEEE Transactions on Information Theory.

[13]  Ling Yu,et al.  QoS and service continuity in 3GPP D2D for IoT and wearables , 2017, 2017 IEEE Conference on Standards for Communications and Networking (CSCN).

[14]  Andrea J. Goldsmith,et al.  Capacity and power allocation for fading MIMO channels with channel estimation error , 2006, IEEE Trans. Inf. Theory.

[15]  R. Mittelhammer.  Mathematical Statistics for Economics and Business , 1996 .

[16]  David Tse,et al.  Mobility increases the capacity of ad hoc wireless networks , 2002, TNET.

[17]  Nurul H. Mahmood,et al.  Beyond 5G Wireless IRT for Industry 4.0: Design Principles and Spectrum Aspects , 2018, 2018 IEEE Globecom Workshops (GC Wkshps).

[18]  Theodore S. Rappaport,et al.  Statistical channel impulse response models for factory and open plan building radio communicate system design , 1991, IEEE Trans. Commun..

[19]  Paolo Baracca,et al.  URLLC for Factory Automation: an Extensive Throughput-Reliability Analysis of D-MIMO , 2020, WSA.

[20]  Wei Yu,et al.  Ultrareliable Wireless Communication with Message Splitting , 2019, 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[21]  Gerhard P. Hancke,et al.  Industrial Wireless Sensor Networks: Challenges, Design Principles, and Technical Approaches , 2009, IEEE Transactions on Industrial Electronics.

[22]  J. Nicholas Laneman.  Limiting analysis of outage probabilities for diversity schemes in fading channels , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[23]  Seung-Yeon Kim,et al.  Multi-Hop Relay Based Coverage Extension in the IEEE802.16j Based Mobile WiMAX Systems , 2008, 2008 Fourth International Conference on Networked Computing and Advanced Information Management.

[24]  Catherine A. Remley,et al.  Industrial Wireless Systems: Radio Propagation Measurements , 2017 .

[25]  S. Redana,et al.  Business Impact of Relay Deployment for Coverage Extension in 3GPP LTE-Advanced , 2009, 2009 IEEE International Conference on Communications Workshops.

[26]  Harish Viswanathan,et al.  Communications in the 6G Era , 2020, IEEE Access.

[27]  Anant Sahai,et al.  Wireless Channel Dynamics and Robustness for Ultra-Reliable Low-Latency Communications , 2019, IEEE Journal on Selected Areas in Communications.

[28]  Wei Yu,et al.  Interference Mitigation for Ultrareliable Low-Latency Wireless Communication , 2019, IEEE Journal on Selected Areas in Communications.

[29]  Upamanyu Madhow,et al.  Blockage and directivity in 60 GHz wireless personal area networks: from cross-layer model to multihop MAC design , 2009, IEEE Journal on Selected Areas in Communications.

[30]  Jian Deng,et al.  Multi-Hop Relay-Aided Underlay D2D Communications for Improving Cellular Coverage Quality , 2018, IEEE Access.

[31]  Babak Hassibi,et al.  How much training is needed in multiple-antenna wireless links? , 2003, IEEE Trans. Inf. Theory.

[32]  Harish Viswanathan,et al.  Adaptive Network-Device Cooperative Diversity for Ultra-Reliable and Low-Latency Wireless Control , 2019, 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring).

[33]  Ke Wang Helmersson,et al.  Deployment Strategies for Ultra-Reliable and Low-Latency Communication in Factory Automation , 2015, 2015 IEEE Globecom Workshops (GC Wkshps).

[34]  Thomas L. Marzetta,et al.  Multiple-antenna channel hardening and its implications for rate feedback and scheduling , 2004, IEEE Transactions on Information Theory.

[35]  Anant Sahai,et al.  Design of a low-latency, high-reliability wireless communication system for control applications , 2014, 2014 IEEE International Conference on Communications (ICC).

[36]  Lizhong Zheng,et al.  Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels , 2003, IEEE Trans. Inf. Theory.

[37]  Klaus Wehrle,et al.  Finite Blocklength Performance of Cooperative Multi-Terminal Wireless Industrial Networks , 2018, IEEE Transactions on Vehicular Technology.

[38]  Y.-P. Eric Wang,et al.  Analysis of ultra-reliable and low-latency 5G communication for a factory automation use case , 2015, 2015 IEEE International Conference on Communication Workshop (ICCW).

[39]  Stephen V. Hanly,et al.  Base Station Cooperation on the Downlink: Large System Analysis , 2010, IEEE Transactions on Information Theory.

[40]  Harish Viswanathan,et al.  Ultra Reliable Low Latency Communications In MmWave For Factory Floor Automation , 2020, Journal of the Indian Institute of Science.

[41]  Raymond Knopp,et al.  Information capacity and power control in single-cell multiuser communications , 1995, Proceedings IEEE International Conference on Communications ICC '95.