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Spectral efficient designs of MIMO‐based CR‐NOMA for Internet of Things Networks
Summary Due to rapid increase in the wireless‐connected Internet‐of‐things (IoT) devices, the communication among devices is a critical task as it relies on the radio‐frequency spectrum, which is a limited resource. Therefore, additional spectral efficient communication designs are required for futu...
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Published in: | International journal of communication systems 2021-08, Vol.34 (12), p.n/a |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Summary
Due to rapid increase in the wireless‐connected Internet‐of‐things (IoT) devices, the communication among devices is a critical task as it relies on the radio‐frequency spectrum, which is a limited resource. Therefore, additional spectral efficient communication designs are required for future IoT networks. By keeping this in mind, we have exploited individually spectral efficient technologies such as the cognitive radio (CR), non‐orthogonal multiple access (NOMA), and multiple‐input multiple‐output (MIMO) simultaneously that is MIMO‐based CR‐NOMA (MIMO‐CR‐NOMA) and have proposed as well as analyzed a potential framework for its downlink scenario. The closed‐form expressions for the throughput at each user due to the number of transmitting and receiving antennas are derived numerically. Further, we have derived mathematical expressions for the sum throughput of different frameworks such as CR‐NOMA, CR‐MIMO, and MIMO‐CR‐NOMA systems. Moreover, the proposed frameworks are simulated, and the relationship between two NOMA users each with multiple antennas is illustrated with simulation results.
Spectral efficient MIMO‐based CR‐NOMA framework for Internet‐of‐things (IoT) devices. Closed‐form expressions for throughput at users due to number of transmitting/receiving antennas. Mathematical expressions for sum throughput for CR‐NOMA, CR‐MIMO, and MIMO‐CR‐NOMA systems. |
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ISSN: | 1074-5351 1099-1131 |
DOI: | 10.1002/dac.4888 |