A Cognitive Implementation For High Throughput, Low Power Hybrid Adaptive and Intelligent Mimo Detectors on Reconfigurable Architectures For 5g LTE/IoT Environment
Anil Kumar Tipparti
Anil Kumar Tipparti, Professor, Department of Electronics and Communication Engineering, CMR Institute of Technology, Kandlakoya, Medchal Road, Hyderabad (Telangana), India.
Manuscript received on 25 March 2019 | Revised Manuscript received on 06 April 2019 | Manuscript Published on 18 April 2019 | PP: 774-777 | Volume-7 Issue-6S March 2019 | Retrieval Number: F03510376S19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Internet of things (IoT) is the world of technology, and it has been predicted that usage of connected devices will be around 200 billion users. As IoT in wearable health care is the major area facilitates the usage of numerous transmitters on board, which leads to the employing of MIMO system (with high performance decoders) for an effective communication. Unfortunately, employing of MIMO system suitable for IoT remains on the darker side of the research. Also, achieving the quality of performance (QoP) with low power, low energy and less computational complexity using re-configurable architectures is the real challenge. To meet this scenario, a novel MIMO detector called Hybrid Adaptive and Intelligent (HAI) detector has been proposed. It is a Hybrid detector (i.e. consists of different combinations of conventional MIMO detectors, such as ZF with Fuzzy K-Best & MMSE with Fuzzy K-best).One of this combination of detectors will be chosen using Cognitive Selective Permutation theory, which is Adaptive to the SM input parameters (S/N), to achieve high QoP parameters. In the proposed algorithm, Intelligence (Fuzzy based) has been incorporated to Dynamically upgrade the value of K (in Fuzzy K-Best Decoding process), to achieve very much reduced complexity as well as power. After testing this detector in the re-configurable Programmable architecture, it gives best performance parameters compared to other detectors (i.e. High BER performance, Low Complexity, High Throughput, Low power and Energy efficient).
Keywords: HAI MIMO Detector, CSP, QoP, LTE/3GPP, SM, IoT, MIMO Communication Systems.
Scope of the Article: Artificial Intelligent Methods, Models, Techniques