Energy-Efficient Resource Allocation for Ultra-Reliable and Low-Latency Communications

Ultra-reliable and low-latency communications (URLLC) is expected to be supported without compromising the resource usage efficiency. In this paper, we study how to maximize energy efficiency (EE) for URLLC under the stringent quality of service (QoS) requirement imposed on the end-to-end (E2E) delay and overall packet loss, where the E2E delay includes queueing delay and transmission delay, and the overall packet loss consists of queueing delay violation, transmission error with finite blocklength channel codes, and proactive packet dropping in deep fading. Transmit power, bandwidth and number of active antennas are jointly optimized to maximize the system EE under the QoS constraints. Since the achievable rate with finite blocklength channel codes is not jointly concave in radio resources, it is challenging to optimize resource allocation. By analyzing the properties of the optimization problem, the global optimal solution is obtained. Simulation and numerical results validate the analysis and show that the proposed policy can improve EE significantly compared with existing policy.

[1]  Tony Q. S. Quek,et al.  Delay Modeling for Heterogeneous Backhaul Technologies , 2015, 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall).

[2]  Klaus I. Pedersen,et al.  Signal Quality Outage Analysis for Ultra-Reliable Communications in Cellular Networks , 2015, 2015 IEEE Globecom Workshops (GC Wkshps).

[3]  Chenyang Yang,et al.  Cross-Layer Optimization for Ultra-Reliable and Low-Latency Radio Access Networks , 2017, IEEE Transactions on Wireless Communications.

[4]  Andreas Mitschele-Thiel,et al.  Latency Critical IoT Applications in 5G: Perspective on the Design of Radio Interface and Network Architecture , 2017, IEEE Communications Magazine.

[5]  Gerhard Fettweis,et al.  5G-Enabled Tactile Internet , 2016, IEEE Journal on Selected Areas in Communications.

[6]  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).

[7]  Adnan Aijaz,et al.  Towards 5G-enabled Tactile Internet: Radio resource allocation for haptic communications , 2016, 2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).

[8]  C H Chang,et al.  EFFECTIVE BANDWIDTH IN HIGHSPEED DIGITAL NETWORKS , 1995 .

[9]  Chenyang Yang,et al.  Energy efficient design for tactile internet , 2016, 2016 IEEE/CIC International Conference on Communications in China (ICCC).

[10]  Björn Debaillie,et al.  A Flexible and Future-Proof Power Model for Cellular Base Stations , 2015, 2015 IEEE 81st Vehicular Technology Conference (VTC Spring).

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

[12]  Geoffrey Ye Li,et al.  Recent advances in energy-efficient networks and their application in 5G systems , 2015, IEEE Wireless Communications.

[13]  Leila Musavian,et al.  Tradeoff Analysis and Joint Optimization of Link-Layer Energy Efficiency and Effective Capacity Toward Green Communications , 2016, IEEE Transactions on Wireless Communications.

[14]  Jussi Turkka,et al.  A Novel Radio Frame Structure for 5G Dense Outdoor Radio Access Networks , 2015, 2015 IEEE 81st Vehicular Technology Conference (VTC Spring).