Resource Allocation in Low Density Spreading Uplink NOMA via Asymptotic Analysis

Abstract

Low density spreading non-orthogonal multipleaccess (LDS-NOMA) is considered where K single-antenna user equipments (UEs) communicate with a base station (BS) over F fading sub-carriers. Each UE k spreads its data symbol over d k < F sub-carriers. Given d k , ∀k as design parameters, we characterize the resource allocation solutions that closely maximize the ergodic mutual information (EMI) in a scenario where the BS assigns resources solely based on the UEs' pathlosses. Conducting analysis in asymptotic limit where F , K, and d k , ∀k converge to +∞ at the same rate, we present EMI in terms of a deterministic equivalent plus a residual term. The deterministic equivalent is given in terms of pathloss values and LDS-codes, and the small residual term scales as O( 1d 2 ) where d = min{d k , ∀k}. We formulate an optimization problem to get the setC * of all spreading codes, irrespective of sparsity constraints, which maximize the deterministic equivalent of EMI. The spreading codes inC * with desired sparsity are obtained via a simple and efficient algorithmic solution. In the finite regime, the residual term is shown to be a small incremental gain for the sparse solutions inC * , which is dictated mainly by d k , ∀k values. Accordingly, we show that the solutions inC * with desired sparsity yield close to optimum values of EMI in the finite regime. Numerical simulation validates the attainable spectral efficiency enhancement as compared to regular, and random spreading.

Capacity Approaching Low Density Spreading in Uplink NOMA via Asymptotic Analysis

“…Parts of this paper have been published in the conference publication [30]. Specifically, the large system analysis and the optimization approach are sketched therein, while the precise proofs along with the derivation details are presented in the current work.…”