Cooperative Broadcast-Multicast in NOMA-based Networks: Design, Relay Selection, and Performance Analysis
Autor: | Saba Bazyar, Nima Reisi |
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Rok vydání: | 2020 |
Předmět: |
Multicast
Computer science business.industry ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS 020206 networking & telecommunications Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology medicine.disease Interference (wave propagation) law.invention Noma Base station Signal-to-noise ratio Relay law Channel state information Computer Science::Networking and Internet Architecture 0202 electrical engineering electronic engineering information engineering Cellular network medicine business Computer Science::Information Theory Computer network |
Zdroj: | 2020 28th Iranian Conference on Electrical Engineering (ICEE). |
DOI: | 10.1109/icee50131.2020.9260882 |
Popis: | In this paper, a new framework for utilizing Non-Orthogonal-Multiple-Access (NOMA) technology in cellular networks is proposed. In this framework, the aim is to transmit a broadcast message, which is intended for all users, and a multicast message, which is important for a small group of users, simultaneously, using NOMA signaling. To reliably transmit these messages to the users far from the base station (BS), a relay-assisted cooperation is proposed. In each transmit interval, a relay is selected to re-transmit the superimposed broadcast-multicast signal to users, thanks to NOMA technology. Assuming the instantaneous Channel State Information (CSI) can be obtained without error, a two-stage relay selection (RS) algorithm is proposed and the closed-form expression for outage probabilities of broadcast and multicast messages are calculated for this strategy. Simulation results, confirming the analytical results, show that as expected, the RS based on full CSI achieves a lower outage probability for both broadcast and multicast messages compared with the random RS strategy. Moreover, increasing the number of relays, the outage probability of the proposed RS algorithm becomes smaller. |
Databáze: | OpenAIRE |
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