Joint decoding for multiway multirelay networks with coded random access

The emergence of Internet-of-Thing (IoT) has driven tremendous growth of number of connected devices such that in the near future everything is connected to the networks forming super-dense networks. To cope with this challenge, this paper investigates networks with multiple relays serving massive number of devices (users), termed as multiway multirelay (MWMR) networks. Coded random access is adopted to simplify the transmission involving massive number of users. Iterative demapping (IDM) algorithm is proposed to be incorporated into successive interference cancellation (SIC) of random access decoding to significantly improve the network throughput. The relays employ modern decode-and-forward (mDF) protocol allowing the relays to keep forwarding (broadcasting) the decoded messages even though error is detected. To take the advantage of messages received from multiple relays, this paper then proposes a joint decoding technique exploiting source correlation of the messages to reduce the required transmit power and improve the network throughput. It is shown that the proposed techniques reduces bit-error-rate (BER) floor to the level below 10
^-5
. Moreover, with Λ
_a
(x), more than two times throughput improvement is achieved using the proposed techniques. We also confirm that K = 2 relays is the practical optimal number of relays to serve massively distributed users in MWMR networks.