Abstract
This work addresses the physical layer channel code design for an uncoordinated, frame- and slot-asynchronous random access protocol. Starting from the observation that collisions between two users yield very specific interference patterns, we define a surrogate channel model and propose different protograph low-density parity-check code designs. The proposed codes are both tested in a setup where the physical layer is abstracted, as well as on a more realistic channel model, where finite-length physical layer simulations of the entire asynchronous random access scheme, including decoding, are carried out. We find that the abstracted physical layer model overestimates the performance when short blocks are considered. Additionally, the optimized codes show gains in supported channel traffic, a measure of the number of terminals that can be concurrently accommodated on the channel, of around 17% at a packet loss rate of 10 − 2 w.r.t. off-the-shelf codes.
Highlights
Driven by the emerging machine-to-machine (M2M) communications and the Internet of things services, the number of connected devices is expected to reach the impressive number of 50 billion by [1]
Our ad-hoc protograph ensemble was designed for the Gaussian interference model, we show here that its asymptotic performance is good in this case of non-Gaussian interferers
While the abstracted physical layer model is a common approach to get first-level insights into the system performance [27], physical layer simulations serve as a confirmation of the results
Summary
Driven by the emerging machine-to-machine (M2M) communications and the Internet of things services, the number of connected devices is expected to reach the impressive number of 50 billion by [1]. Works in the literature usually assume capacity achieving random code ensembles and apply a threshold-based model for decoding [25]: the average signal-to-noise plus interference ratio over a packet is compared to the Shannon limit, i.e., the worst channel parameter for which error-free transmission is possible, to decide whether decoding is possible or not. As an extension of [30], we do not restrict to finding LDPC code ensembles with favourable iterative decoding thresholds only, and design finite-length codes These codes are used to simulate the physical layer of the random access protocol, giving a more realistic estimate of the PLR. The performance trends and relative performance identified via the simpler simulations with the abstracted physical layer are confirmed
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