In this paper, the uplink semi-persistent scheduling policy problem of minimizing network latency is considered for a training-based large-scale antenna system employing two simple linear receivers, a maximum ratio combiner and a zero-forcing receiver, while satisfying each user's reliability and latency constraints under an energy constraint. The network latency is defined as the air-time requested either to serve all users with a minimum quality-of-service, including reliability constraints and minimum throughput levels, or to maximize the spectral efficiency. Optimal non-orthogonal pilots are used to decrease the network latency. An optimization algorithm for determining the latency-optimal uplink scheduling policy using binary-integer programming (BIP) with an exponential-time complexity is proposed. In addition, it is proven that a linear programming relaxation of the BIP can provide an optimal solution with a polynomial-time complexity. Numerical simulations demonstrate that the proposed scheduling policy can provide several times lower network latency in realistic environments than conventional policies. The proposed optimal semi-persistent scheduling policy provides critical guidelines for designing 5G and future cellular systems, particularly for their ultra-reliable low-latency communication services.
Bibliographical noteFunding Information:
This work was supported in part by the ICT Research and Development Program of MSIT/IITP, Multiple Access Technique with Ultra-Low Latency and High Efficiency for Tactile Internet Services in IoT Environments, under Grant 2015-0-00300, and in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology under Grant NRF-2015K2A3A1000189.
© 2013 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Materials Science(all)