Quantum Annealer for MIMO Detection Complexity

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

As the complexity of Multi-Input/Multi-Output (MIMO) processing increases with the number of antennas and users, existing detection techniques face challenges in achieving faster and more accurate data stream processing, leading to computational bottlenecks and increased error rates in wireless communication systems.

Innovation Solution

The implementation of a quantum annealer that embeds a Maximum Likelihood (ML) detection algorithm to decode spatially multiplexed data streams, utilizing quantum computing to enhance the probability and speed of detection in complex MIMO communications, specifically using a D-Wave 2000Q quantum annealer to achieve target bit error rates and frame error rates within limited computation time.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If the number of antennas and users in MIMO systems increases to boost data capacity, then wireless data transmission capability is improved, but processing complexity increases leading to computational bottlenecks

Engineering Contradiction:

Improvewireless data transmission capabilityVSAvoidprocessing complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces classical mechanical/digital computing systems with a quantum annealing system. The quantum annealer uses quantum mechanical effects (quantum tunneling, superposition) to solve the MIMO detection optimization problem, substituting the traditional sequential digital processing approach with parallel quantum processing that can handle the exponential complexity of large-scale MIMO systems.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent transforms the MIMO detection problem into a different parameter space by formulating it as a quadratic optimization problem suitable for quantum annealing. The channel estimation and data detection are reformulated in terms of energy minimization of a Hamiltonian system, changing the problem parameters from signal processing domains to quantum energy states.

Inventive Principle:

Principle #35Parameter changes

2Ease of operation

If classical detection techniques are used in large-scale MIMO systems, then implementation is straightforward, but detection speed decreases and error rates increase

Engineering Contradiction:

Improveimplementation simplicityVSAvoiddetection speed

Core Design Contradiction:

Ease of operationVSSpeed

Solution Approach 1:

The patent substitutes classical detection algorithms (such as zero-forcing or minimum mean square error detectors) with a quantum annealing-based maximum likelihood detector. This replacement provides both faster detection speed and improved accuracy by exploiting quantum parallelism to evaluate multiple detection hypotheses simultaneously.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Loss of time

If computational time is limited for MIMO detection, then real-time processing is achieved, but detection accuracy decreases with higher error rates

Engineering Contradiction:

Improvecomputation timeVSAvoiddetection accuracy

Core Design Contradiction:

Loss of timeVSReliability

Solution Approach 1:

The patent performs preliminary transformation of the MIMO detection problem into a quadratic optimization form that can be directly mapped to the quantum annealer's Hamiltonian. This pre-processing step, including channel matrix decomposition and objective function formulation, enables the quantum system to immediately begin optimization without iterative refinement, achieving both speed and accuracy.

Inventive Principle:

Principle #10Preliminary action

4Productivity

If quantum annealing is used for MIMO detection, then detection speed and accuracy are improved, but device complexity increases

Engineering Contradiction:

Improvedetection speedVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments the MIMO detection system into distinct functional modules: a classical pre-processing unit that formulates the optimization problem, a quantum annealing unit that solves the optimization, and a post-processing unit that interprets results. This segmentation allows each component to be optimized independently and facilitates integration with existing communication infrastructure.

Inventive Principle:

Principle #1Segmentation

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach significantly improves the detection of data streams by reducing computational complexity and achieving low bit error rates and frame error rates, even in large-scale MIMO systems with 48 users and antennas, while being adaptable to various modulation schemes.

Implementation Method 1

a quantum annealer operable to embed the ML algorithm onto qubits of the quantum annealer

Methodology Applied

Scientific EffectQuantum annealing:

Implementation Method 2

via quantum fluctuations (e.g., temporary changes in the amount of energy in a point in space)

Methodology Applied

Scientific EffectQuantum tunneling:

Data Source

PatentUS11863279B2Quantum optimization for multiple input and multiple output (MIMO) processing

Publication Date: 2024.01.02 UNIVERSITIES SPACE RES ASSOC

AI summary

Systems and methods herein provide for Multi-Input/Multi-Output (MIMO) processing. In one embodiment, a MIMO system comprises a receiver operable to receive a plurality of spatially multiplexed data streams. The system also comprises a processor operable to embed a maximum likelihood (ML) detection algorithm onto a quantum annealer, and to decode the spatially multiplexed data streams via the embedded ML to detect data bits of a plurality of users.