Quantum versus simulated annealing in wireless interference network optimization.

Huo Chen,Chi Wang,Edmond Jonckheere

doi:10.1038/srep25797

Abstract

Quantum annealing (QA) serves as a specialized optimizer that is able to solve many NP-hard problems and that is believed to have a theoretical advantage over simulated annealing (SA) via quantum tunneling. With the introduction of the D-Wave programmable quantum annealer, a considerable amount of effort has been devoted to detect and quantify quantum speedup. While the debate over speedup remains inconclusive as of now, instead of attempting to show general quantum advantage, here, we focus on a novel real-world application of D-Wave in wireless networking—more specifically, the scheduling of the activation of the air-links for maximum throughput subject to interference avoidance near network nodes. In addition, D-Wave implementation is made error insensitive by a novel Hamiltonian extra penalty weight adjustment that enlarges the gap and substantially reduces the occurrence of interference violations resulting from inevitable spin bias and coupling errors. The major result of this paper is that quantum annealing benefits more than simulated annealing from this gap expansion process, both in terms of ST99 speedup and network queue occupancy. It is the hope that this could become a real-word application niche where potential benefits of quantum annealing could be objectively assessed.

Highlights

Quantum annealing is based on the premise that the minimum energy configuration of the Ising spin glass model encodes the solution to specific NP-hard problems, including all Karp’s 21 NP-complete problems[16]
This is commonly used in Bluetooth and FH-CDMA19,20, while the 2-hop interference model is sometimes used in studies of IEEE 802.11 networks[21], in which no two links within 2-hop distance can be simultaneously activated
It is known that SA can boost the overall performance of classical heuristic algorithms in solving Weighted Maximum Independence Set (WMIS) problems[33]

Summary

Introduction

Quantum annealing is based on the premise that the minimum energy configuration of the Ising spin glass model encodes the solution to specific NP-hard problems, including all Karp’s 21 NP-complete problems[16]. Such problems are written in the form of Quadratic Unconstrained Binary Optimization (QUBO) problems, N f (x1, ..., xn) = − ∑ cmxm + ∑ Jmnxmxn, m=1. The most commonly used model is the 1-hop interference model (node exclusive model), in which every node can transmit or receive along only one activated link abutting that node in the same time slot This is commonly used in Bluetooth and FH-CDMA19,20, while the 2-hop interference model is sometimes used in studies of IEEE 802.11 networks[21], in which no two links within 2-hop distance can be simultaneously activated. Protocol designers can set K to arbitrary value, as long as end-to-end delay, signal interference and computation cost reach a Pareto-optimal point

Methods

Results

Conclusion