Lenstra Lenstra Lovász (LLL) Assisted Likelihood Ascent Search (LAS) Algorithm for Signal Detection in Massive MIMO

• Published in: 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN) pp. 1 - 4
• Main Authors: Menon, U. Vivek, Challa, Naga Raju, Bagadi, Kalapraveen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2019
• Subjects: Antennas; Bit error rate; Classification algorithms; Complexity theory; Detectors; LAS Algorithm; LLL Algorithm; Massive MIMO; MMSE
• DOI: 10.1109/ViTECoN.2019.8899594

In this paper, we propose a new algorithm called Lenstra Lenstra Lovász (LLL) assisted Likelihood Ascent Search (LAS) algorithm for signal detection in Massive MIMO which attains a near to optimum performance. This algorithm is developed by collaborating two existing algorithms to satisfy the tradeoff between performance and complexity in Massive Multiple Input Multiple Output (MIMO) systems. The Linear Detection and Lattice Reduction (LR) are some of the prominent suboptimal algorithms whose performance is far from optimal. In the proposed LLL-LAS Algorithm, the LLL algorithm is an LR based detection which serves as the initial solution to the LAS algorithm. The Simulation results substantiate the decrement in the Bit Error Rate which makes it better than the other classical detection techniques