Abstract
Hybrid precoding and combining is a key technique to provide an appropriate antenna gain in millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. In wideband mmWave channels, the analog precoder and combiner is designed in the time domain and remain unchanged over the whole bandwidth. In contrast, digital precoders and combiners are optimized on a per-subcarrier basis which makes the resultant problem very difficult. To solve this problem, we combine the well-known turbo-equalizer with the tabu-search (TS)-algorithm developed in artificial intelligence and propose TS-based joint hybrid precoding and combining scheme to intelligently search the near-optimum pair of hybrid precoder and combiner. Specifically, our scheme consists of two key steps. At first, a base station (BS) and a mobile station (MS) develop the turbo-like (TL)-joint search by using the idea of iterative information exchange between them. Then, to find out the near-optimum pair of hybrid precoder and combiner in each iteration of the TL-joint search, the TS-algorithm is employed. Simulation results are shown to verify the significant sum-rate performance of the proposed solution with low-complexity compared to some existing solutions.
Original language | English |
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Pages (from-to) | 196375 - 196385 |
Number of pages | 11 |
Journal | IEEE Access |
Volume | 8 |
Publication status | Published - 22 Oct 2020 |
Keywords
- Hybrid precoding
- millimeter-wave
- massive MIMO
- artificial intelligence