Reliable Hybrid Systematic Network Coding for Multicast Services in 5G Networks

Abstract

Providing reliable and efficient multicast services is one of the most important issues of the emerging 5G network. As the number of users grows rapidly, non-feedback multicast schemes are more suitable for bandwidth efficiency. However, conventional non-feedback multicast solutions, like the well-known Random Linear Network Coding (RLNC) and Systematic Network Coding (SNC), are suffering from complicated packet decoding and redundant packet reception at the unsaturated users. In this paper, we propose a reliable Hybrid Systematic Network Coding (HSNC) scheme to fully solve these problems. HSNC utilizes both deterministic and randomly generated coding vectors over the same finite field. By subtracting coding vectors with zero elements from a Reed- Solomon coding matrix, the goal to maximize the number of linear independent rows of a coding matrix can be easily realized. Close-form expressions of bit overhead ratio, decoding probability and computational cost are derived out. Numerical results show that HSNC, with or without a sliding window, outperforms RLNC and SNC in terms of the decoding probability. Moreover, HSNC has lower bit overhead and computational cost.