A New 5G Cellular Broadcasting Approach: Hybrid LDM-NOMA and FeMBMS-OMA Analysis Based on Stochastic Geometry

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Shariatzadeh H., Maghrebi S. G., KARAKAYA B., Shahzadi A.

IEEE Access, vol.11, pp.119824-119839, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 11
  • Publication Date: 2023
  • Doi Number: 10.1109/access.2023.3291922
  • Journal Name: IEEE Access
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Page Numbers: pp.119824-119839
  • Keywords: 5G broadcast, BER, FeMBMS, LDM, outage/coverage probability, stochastic geometry (SG), sum rate
  • Istanbul University Affiliated: No


In this paper, an alternative hybrid infrastructure to complete the media cellular TV puzzle called 5G broadcast is introduced and developed. The performance of a non-orthogonal and orthogonal physical hybrid layer for cellular broadcasting is investigated. A downlink layered division multiplexing with non-orthogonal multiple access (LDM-NOMA) together with a further evolved multimedia broadcast multicast service with orthogonal multiple access (FeMBMS-OMA) is superimposed. In our scenario, we have defined them as two broadcast service providers (BSPs), whereby the former recruits the latter as a cooperative layer. Service selection is done by using a binary factor access technology. We assume that there is perfect knowledge with channel state information for Rayleigh fading multipath channel. Bit error rate (BER) and outage/coverage capacity are selected as our inquiries stochastic geometry benchmarks. The spectrum constellations of the scheme are worked according to the resource block (RB) element/symbols and different modulations. The proposed framework can work without a subscriber identity module (SIM card) uplink and internet protocol (IP). Mathematical analysis, based on the exact closed-form expressions, is consistent with the theory of the proposed LDM-NOMA and FeMBMS-OMA. The simulation results are based on the Monte Carlo iterative methodology, and demonstrate the superiority of the hybrid framework compared to each of the technologies separately.