Statistical QoS-Driven Energy-Efficiency Optimization for URLLC Over 5G Mobile Wireless Networks in the Finite Blocklength Regime
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2019 IEEE. To support delay-bounded multimedia services over 5G mobile wireless networks, the statistical quality-of-service (QoS) technique has been designed to jointly guarantee the statistically delay-bounded video transmissions over different time-varying wireless channels, simultaneously. On the other hand, with stringent delay-bounded and error-rate-bounded QoS requirements for 5G applications, the traditional Shannon capacity is no longer appropriate to characterize the maximum achievable data transmission rate given the block error probability. Towards this end, the finite blocklength coding (FBC) technique has been developed to support the new type of Ultra-Reliable and Low Latency Communications (URLLC). However, since the existing approximations of the transmission rate are neither convex nor concave in terms of the transmit power in the finite blocklength regime, it is challenging to formulate and solve the resource allocation optimization problems for URLLC over various different wireless fading channels while guaranteeing the statistical delay-bounded QoS requirements. To overcome the aforementioned problems, we propose the energy efficient FBC based cross-layer design while guaranteeing the statistical delay-bounded QoS requirements for URLLC. In particular, we establish and analyze FBC based wireless network models. By taking into account the statistical delay-bounded QoS constraints, we formulate and solve the -effective energy efficiency optimization problem using FBC. Also conducted is a set of simulations which validate and evaluate our proposed FBC scheme under the statistical delay-bounded QoS constraints for URLLC.
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2019 53rd Annual Conference on Information Sciences and Systems (CISS)
