Measure Concentration on the OFDM-based Random Access Channel

TL;DR

This paper introduces a novel OFDM-based random access scheme that subdivides the frequency domain to achieve near-capacity performance, supported by new concentration inequalities and a sparsity capture effect, leading to significant capacity gains.

Contribution

It proposes a new approach using sub-channel division in OFDM to enhance capacity, supported by theoretical concentration inequalities and a sparsity capture effect.

Findings

Achieves approximately 30-fold capacity increase in simulations.

Demonstrates the effectiveness of sub-channel subdivision for scalable random access.

Provides new concentration inequalities relevant to the approach.

Abstract

It is well known that CS can boost massive random access protocols. Usually, the protocols operate in some overloaded regime where the sparsity can be exploited. In this paper, we consider a different approach by taking an orthogonal FFT base, subdivide its image into appropriate sub-channels and let each subchannel take only a fraction of the load. To show that this approach can actually achieve the full capacity we provide i) new concentration inequalities, and ii) devise a sparsity capture effect, i.e where the sub-division can be driven such that the activity in each each sub-channel is sparse by design. We show by simulations that the system is scalable resulting in a coarsely 30-fold capacity increase.