Improved Two-Dimensional Double Successive Projection Algorithm for Massive MIMO Detection

• Autorzy: Chakraborty Sourav , Sinha Nirmalendu Bika , Mitra Monojit

Identyfikatory

DOI

10.24425/ijet.2023.144343

• Języki publikacji: EN

Abstrakty

EN

In a massive multiple-input multiple-output (MIMO) system, a large number of receiving antennas at the base station can simultaneously serve multiple users. Linear detectors can achieve optimal performance but require large dimensional matrix inversion, which requires a large number of arithmetic operations. Several low complexity solutions are reported in the literature. In this work, we have presented an improved two-dimensional double successive projection (I2D-DSP) algorithm for massive MIMO detection. Simulation results show that the proposed detector performs better than the conventional 2D-DSP algorithm at a lower complexity. The performance under channel correlation also improves with the I2D-DSP scheme. We further developed a soft information generation algorithm to reduce the number of magnitude comparisons. The proposed soft symbol generation method uses real domain operation and can reduce almost 90% flops and magnitude comparisons.

Słowa kluczowe

EN

massive MIMO; MMSE; ZF; 2D-DSP; QAM; LLR; I2D-DSP

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2023
• Tom: Vol. 69, No. 1
• Strony: 139--146
• Opis fizyczny: Bibliogr. 27 poz., tab., wykr.

Twórcy

autor

Chakraborty Sourav

• Department of Electronics and Communication Engineering, Cooch Behar Government Engineering College, Coochbehar,India

autor

Sinha Nirmalendu Bika

• Principal, Maharaja Nandakumar Mahavidyalaya, Purba Medinipore, India

autor

Mitra Monojit

• Department of Electronics and Telecommunication, Engineering, IIEST Shibpur, Howrah, India

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).