Scaling 6G Subscribers with Fewer BS Antennas using Multi-carrier NOMA in Fixed Wireless Access
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866929566757421056 |
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| author | Rajabalifardi, Kamyar Bhattacharya, Sagnik Afshang, Mehrnaz Mozaffari, Mohammad Cioffi, John M. |
| author_facet | Rajabalifardi, Kamyar Bhattacharya, Sagnik Afshang, Mehrnaz Mozaffari, Mohammad Cioffi, John M. |
| contents | This paper introduces a novel power allocation and subcarrier optimization algorithm tailored for fixed wireless access (FWA) networks operating under low-rank channel conditions, where the number of subscriber antennas far exceeds those at the base station (BS). As FWA networks grow to support more users, traditional approaches like orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) struggle to maintain high data rates and energy efficiency due to the limited degrees of freedom in low-rank scenarios. Our proposed solution addresses this by combining optimal power-subcarrier allocation with an adaptive time-sharing algorithm that dynamically adjusts decoding orders to optimize performance across multiple users. The algorithm leverages a generalized decision feedback equalizer (GDFE) approach to effectively manage inter-symbol interference and crosstalk, leading to superior data rates and energy savings. Simulation results demonstrate that our approach significantly outperforms existing OMA and NOMA baselines, particularly in low-rank conditions, with substantial gains in both data rate and energy efficiency. The findings highlight the potential of this method to meet the growing demand for scalable, high-performance FWA networks. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_21786 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Scaling 6G Subscribers with Fewer BS Antennas using Multi-carrier NOMA in Fixed Wireless Access Rajabalifardi, Kamyar Bhattacharya, Sagnik Afshang, Mehrnaz Mozaffari, Mohammad Cioffi, John M. Signal Processing Information Theory This paper introduces a novel power allocation and subcarrier optimization algorithm tailored for fixed wireless access (FWA) networks operating under low-rank channel conditions, where the number of subscriber antennas far exceeds those at the base station (BS). As FWA networks grow to support more users, traditional approaches like orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) struggle to maintain high data rates and energy efficiency due to the limited degrees of freedom in low-rank scenarios. Our proposed solution addresses this by combining optimal power-subcarrier allocation with an adaptive time-sharing algorithm that dynamically adjusts decoding orders to optimize performance across multiple users. The algorithm leverages a generalized decision feedback equalizer (GDFE) approach to effectively manage inter-symbol interference and crosstalk, leading to superior data rates and energy savings. Simulation results demonstrate that our approach significantly outperforms existing OMA and NOMA baselines, particularly in low-rank conditions, with substantial gains in both data rate and energy efficiency. The findings highlight the potential of this method to meet the growing demand for scalable, high-performance FWA networks. |
| title | Scaling 6G Subscribers with Fewer BS Antennas using Multi-carrier NOMA in Fixed Wireless Access |
| topic | Signal Processing Information Theory |
| url | https://arxiv.org/abs/2410.21786 |