Applications envisioned to enable connected and autonomous vehicles entail the exchange of data through reliable and low-latency direct communications between vehicles. The current specifications for the cellular-vehicle-to-everything (C-V2X) technology can still barely match such requirements. To tackle this issue, we investigate here the joint application to the C-V2X sidelink with autonomous resource allocation of two techniques that are being considered for the evolution of cellular systems, i.e., in-band full-duplex (FD) and non-orthogonal multiple access (NOMA). In particular, we consider FD capabilities to detect ongoing collisions while transmitting and thus resolve persistent resource allocations, which are causing repeated errors at the neighboring receivers. Regarding NOMA, we consider the use of successive-interference cancellation (SIC) for the decoding of multiple signals when different vehicles are transmitting simultaneously using the same resources, thus converting packet losses into improved spectral efficiency. The investigation is based on the latest fifth generation (5G) New Radio (NR)-V2X specifications and focuses on broadcast transmissions, which are expected to cover the majority of the exchanged traffic in V2X contexts. As shown through simulations in large-scale scenarios, the two techniques, both relying on signal processing at the receiver to cancel the (self or successive) interference, provide complementary advantages under different conditions. FD is in fact very effective to improve the delivery performance at short distances when periodic data traffic is assumed, while SIC-based NOMA improves the reception probability at medium distances both under periodic and aperiodic data traffic conditions.


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    Titel :

    Joint use of Self and Successive Interference Cancellation in V2X Sidelink with Autonomous Resource Allocation




    Erscheinungsdatum :

    01.06.2023


    Format / Umfang :

    1282417 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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