Capacity Optimality of OAMP in Coded Large Unitarily Invariant Systems

TL;DR

This paper demonstrates that the orthogonal approximate message passing (OAMP) algorithm achieves the capacity of large unitarily invariant systems with optimized coding, significantly improving performance over existing algorithms.

Contribution

It proves the capacity optimality of OAMP in coded large unitarily invariant systems and introduces a capacity-achieving coding principle with optimized LDPC codes.

Findings

OAMP reaches the constrained capacity predicted by the replica method.

Optimized LDPC codes significantly improve OAMP performance.

QPSK modulation achieves near-capacity BER performance under various conditions.

Abstract

This paper investigates a large unitarily invariant system (LUIS) involving a unitarily invariant sensing matrix, an arbitrary fixed signal distribution, and forward error control (FEC) coding. Several area properties are established based on the state evolution of orthogonal approximate message passing (OAMP) in an un-coded LUIS. Under the assumptions that the state evolution for joint OAMP and FEC decoding is correct and the replica method is reliable, we analyze the achievable rate of OAMP. We prove that OAMP reaches the constrained capacity predicted by the replica method of the LUIS with an arbitrary signal distribution based on matched FEC coding. Meanwhile, we elaborate a constrained capacity-achieving coding principle for LUIS, based on which irregular low-density parity-check (LDPC) codes are optimized for binary signaling in the simulation results. We show that OAMP with the optimized codes has significant performance improvement over the un-optimized ones and the well-known Turbo linear MMSE algorithm. For quadrature phase-shift keying (QPSK) modulation, constrained capacity-approaching bit error rate (BER) performances are observed under various channel conditions.