This paper presents a novel hybrid decoder dubbed SCRAM (Slotted Coded Random Access Multiplexing), for Coded Slotted ALOHA (CSA). The proposed decoder is provisioned to meet the challenging requirements of the future Machine to Machine (M2M) Internet of Things (IoT) in the 5G standard. These challenges are mainly portrayed in a reliable robust communication with ultra-low latency. At the User Equipment (UE) terminal, a Low Density Parity Check (LDPC) encoder is deployed, and the encoded codewords are transmitted on the uplink channel using Slotted ALOHA (SA). While LDPC codes are chosen because of their near Shannon capacity performance, SA serves as a Random Access (RA) mechanism that guarantees the low-latency requirements. However, the incorporation of uncoordinated SA introduces collisions between the transmitted packets. The proposed decoder aims at resolving these collisions by means of a joint LDPC-SA hybrid decoder. Unlike the sequential decoders presented in the literature, the proposed joint decoder concurrently decodes both the SA and LDPC blocks in a similar fashion to the Belief Propagation (BP) algorithm applied for LDPC codes. The results presented herein show that the proposed SCRAM decoder significantly outperforms the state-of-the-art decoding schemes of CSA by more than 5.5 dB.


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    Title :

    SCRAM: A Novel Approach for Reliable Ultra-Low Latency M2M Applications


    Contributors:


    Publication date :

    2018-08-01


    Size :

    217672 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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