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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2406.12596 |
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| _version_ | 1866916589637468160 |
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| author | Liu, Haoyan Jie, Caijian Yang, Min Li, Chengguang |
| author_facet | Liu, Haoyan Jie, Caijian Yang, Min Li, Chengguang |
| contents | Exploring channel dimensions has been the driving force behind breakthroughs in successive generations of mobile communication systems. In 5G, space division multiple access (SDMA) leveraging massive MIMO has been crucial in enhancing system capacity through spatial differentiation of users. However, SDMA can only finely distinguish users at adjacent angles in ultra-dense networks by extremely large-scale antenna arrays. For a long time, most research has focused on the angle domain of the space, overlooking the potential of the distance domain. Near-field location division multiple access (LDMA) was proposed based on the beam-focusing effect yielded by near-field spherical propagation model, partitioning channel resources by both angle and distance. To achieve a similar idea in the far-field region, this paper introduces a far-field LDMA scheme for wideband systems based on orthogonal frequency division multiplexing (OFDM). Benefiting from frequency diverse arrays (FDA), it becomes possible to manipulate beams in the distance domain. Combined with OFDM, the inherent cyclic prefix ensures a complete OFDM symbol can be received without losing distance information, while the matched filter of OFDM helps eliminate the time-variance of FDA steering vectors. Theoretical and simulation results show that LDMA can fully exploit the additional degrees of freedom in the distance domain to significantly improve spectral efficiency, especially in narrow sector multiple access (MA) scenarios. Moreover, LDMA can maintain independence between array elements even in single-path channels, making it stand out in MA schemes at millimeter-wave and higher frequency bands. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_12596 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Beyond Near-Field: Far-Field Location Division Multiple Access in Downlink MIMO Systems Liu, Haoyan Jie, Caijian Yang, Min Li, Chengguang Signal Processing Exploring channel dimensions has been the driving force behind breakthroughs in successive generations of mobile communication systems. In 5G, space division multiple access (SDMA) leveraging massive MIMO has been crucial in enhancing system capacity through spatial differentiation of users. However, SDMA can only finely distinguish users at adjacent angles in ultra-dense networks by extremely large-scale antenna arrays. For a long time, most research has focused on the angle domain of the space, overlooking the potential of the distance domain. Near-field location division multiple access (LDMA) was proposed based on the beam-focusing effect yielded by near-field spherical propagation model, partitioning channel resources by both angle and distance. To achieve a similar idea in the far-field region, this paper introduces a far-field LDMA scheme for wideband systems based on orthogonal frequency division multiplexing (OFDM). Benefiting from frequency diverse arrays (FDA), it becomes possible to manipulate beams in the distance domain. Combined with OFDM, the inherent cyclic prefix ensures a complete OFDM symbol can be received without losing distance information, while the matched filter of OFDM helps eliminate the time-variance of FDA steering vectors. Theoretical and simulation results show that LDMA can fully exploit the additional degrees of freedom in the distance domain to significantly improve spectral efficiency, especially in narrow sector multiple access (MA) scenarios. Moreover, LDMA can maintain independence between array elements even in single-path channels, making it stand out in MA schemes at millimeter-wave and higher frequency bands. |
| title | Beyond Near-Field: Far-Field Location Division Multiple Access in Downlink MIMO Systems |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2406.12596 |