Quantum Speedup for Index Modulation
Quantum Speedup for Index Modulation
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DOI：
10.1109/access.2021.3103207
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发表时间：
2021-05
期刊：
影响因子：
3.9
通讯作者：
Naoki Ishikawa
中科院分区：
文献类型：
--
作者：
Naoki Ishikawa
本文提出了一种用于下一代物联网无线网络的量子辅助索引调制。NP-难指标选择问题首先由一个二次无约束二进制优化（QUBO）问题的可行解的约束。为了最大限度地减少量子电路所需的量子位数，然后通过部分利用经典计算机的基于字典的方法来简化该公式。对于这两种公式，所需的量子比特的数量和非零元素的QUBO矩阵进行了代数分析，并发现与实际测量结果非常吻合。研究表明，Grover自适应搜索可以为索引选择问题提供量子加速比。这一有希望的结果意味着指数调制的开关结构适用于量子计算，未来的容错量子计算机可能有助于获得高性能的指数激活模式。
This paper presents a quantum-assisted index modulation for next-generation IoT wireless networks. The NP-hard index selection problem is first formulated by a quadratic unconstrained binary optimization (QUBO) problem consisting of constraints of feasible solutions. To minimize the number of qubits required for a quantum circuit, this formulation is then simplified by a dictionary-based approach that partially exploits a classical computer. For both formulations, the numbers of required qubits and non-zero elements in QUBO matrices are analyzed algebraically, and found to be in close agreement with the actual measurement. It is observed that the Grover adaptive search can provide the quantum speedup for the index selection problem. This promising result implies that the on-off structure of index modulation is suitable for quantum computation, and future fault-tolerant quantum computers may be useful for obtaining high-performance index activation patterns.