Optimal power allocation for QoS-constrained downlink networks with finite blocklength codes

In this paper, we consider a downlink multiuser network operating with finite blocklength codes under statistical quality of service (QoS) constraints. An optimal power allocation algorithm is studied to maximize the normalized sum throughput under QoS constraints. We first determine the finite blocklength (FBL) throughput formulations and subsequently state optimization problems. We show the convexity of the power allocation problem under certain conditions and propose an optimal algorithm to solve the problem. Via numerical analysis, we demonstrate the performance improvements with the optimal power allocation. In addition, we provide interesting insights on the system behavior by characterizing the impact of the error probability, the QoS-exponent and blocklength on the performance.

[1]  Cheng-Shang Chang,et al.  Stability, queue length, and delay of deterministic and stochastic queueing networks , 1994, IEEE Trans. Autom. Control..

[2]  Chao Shen,et al.  Energy-Efficient Packet Scheduling With Finite Blocklength Codes: Convexity Analysis and Efficient Algorithms , 2016, IEEE Transactions on Wireless Communications.

[3]  Lajos Hanzo,et al.  Energy Efficient OFDMA Networks Maintaining Statistical QoS Guarantees for Delay-Sensitive Traffic , 2016, IEEE Access.

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

[5]  H. Vincent Poor,et al.  Dispersion of the Gilbert-Elliott Channel , 2011, IEEE Trans. Inf. Theory.

[6]  H. Vincent Poor,et al.  Dispersion of Gaussian channels , 2009, 2009 IEEE International Symposium on Information Theory.

[7]  Limin Xiao,et al.  Statistical QoS-Driven Resource Allocation and Source Adaptation for D2D Communications Underlaying OFDMA-Based Cellular Networks , 2017, IEEE Access.

[8]  Vincent Yan Fu Tan,et al.  The third-order term in the normal approximation for the AWGN channel , 2014, 2014 IEEE International Symposium on Information Theory.

[9]  Qinghe Du,et al.  QoS-Aware Base-Station Selections for Distributed MIMO Links in Broadband Wireless Networks , 2011, IEEE Journal on Selected Areas in Communications.

[10]  Dapeng Wu,et al.  Effective capacity: a wireless link model for support of quality of service , 2003, IEEE Trans. Wirel. Commun..

[11]  James Gross,et al.  Blocklength-Limited Performance of Relaying Under Quasi-Static Rayleigh Channels , 2016, IEEE Transactions on Wireless Communications.

[12]  H. Vincent Poor,et al.  Dispersion of the Gilbert-Elliott Channel , 2009, IEEE Transactions on Information Theory.

[13]  Jinho Choi.  Effective Capacity of NOMA and a Suboptimal Power Control Policy With Delay QoS , 2017, IEEE Transactions on Communications.

[14]  Mustafa Cenk Gursoy,et al.  Throughput analysis of buffer-constrained wireless systems in the finite blocklength regime , 2010, 2011 IEEE International Conference on Communications (ICC).

[15]  Mustafa Cenk Gursoy,et al.  Throughput of cognitive radio systems with finite blocklength codes , 2012, 2012 46th Annual Conference on Information Sciences and Systems (CISS).

[16]  Chenyang Yang,et al.  Radio Resource Management for Ultra-Reliable and Low-Latency Communications , 2017, IEEE Communications Magazine.

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

[18]  Chao Zhang,et al.  Statistical Delay Control and QoS-Driven Power Allocation over Two-Hop Wireless Relay Links , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.