International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 03 Issue: 03 | Mar-2016 www.irjet.net p-ISSN: 2395-0072 © 2016, IRJET | Impact Factor value: 4.45 | ISO 9001:2008 Certified Journal | Page 1496 LATTICE REDUCTION AIDED DETECTION TECHNIQUES FOR MIMO SYSTEMS Susmita Prasad 1 , Samarendra Nath Sur 2 Dept. of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Majhitar, Sikkim, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - A Multiple input multiple output (MIMO) technology is seen to provide the best solution to high data rate and reliable wireless communication. For the purpose of detection, Maximum Likelihood receivers are most optimal but highly complex especially with higher order constellation. There are a number of other detectors, linear and non-linear, which are less complex but suboptimal. In this paper we utilize a novel class receivers based on Lattice Reduction for MIMO Systems which achieve near maximum-likelihood detector performance with lower complexity. [1] Lenstra-Lenstra-Lovasz Algorithm [2] is used for lattice reduction purpose. Performance comparisons are made between LRA receivers and other conventional receivers in both independent and correlated channels by simulations. It will be shown that LRA based receivers outperform the conventional ones, especially in correlated channels. Key Words: MIMO Systems, Zero-Forcing Detection, Minimum Mean Square Error Detection, Wireless Communication, Lattice-Reduction, Maximum- Likelihood Detection, Bit Error Rate 1. INTRODUCTION There is a huge demand for high data rate wireless communication services which has caused notable research interests in the multiple input and multiple output (MIMO) technologies. In MIMO, a number of independent data streams are simultaneously send over a communication channel by the use of multiple antennas at the transmitter and receiver sides in a rich scattering environment. Each receiving antenna acquires a superimposition of all of these transmitted streams. The process of separating out each independent data streams is called the MIMO detection. [3] A brute-force Maximum-Likelihood (ML) detection provides optimal solution to the MIMO symbol detection [4], but its implementation is highly complex especially with either a larger size constellation or large number of antennas. Therefore, the real challenge lies in designing the hardware for the MIMO symbol detectors such that bit-error-rate (BER) performance comparable to the ML detector is achieved while having low hardware complexity and high throughput. Many low-complexity methods like Zero-Forcing (ZF) and Minimum Mean Square Error (MMSE) detection exhibits considerably lower complexity which map well to hardware but have greatly reduced BER performance compared to the ML detector. [5] It is clearly desirable to explore detection algorithms that achieve ML or near-ML performance. Lattice reduction (LR)-aided detectors incorporate lattice reduction algorithms into the algorithms of ZF or MMSE detectors.[6] For L-R aided MIMO detection, the Lenstra-Lenstra-Lovasz algorithm has been used exclusively till date. The LLL reduction is used to improve the performance of the MIMO detection schemes. The algorithm optimizes the generating matrix of the lattice, to obtain a nicer description of the lattice. [7] As of now many research papers have shown the utilization of LLL algorithm for the purpose of lattice reduction. Few of these papers include ǮLattice Reduction Aided Detection for MIMO-OFDM-CDM Communication Systemsǯ by J. Adeane, M.R.D. Rodrigues and I.J.Wessel and ǮLattice-Reduction-Aided Receivers for MIMO-OFDM in Spatial Multiplexing Systemǯ by )naki Berenguer, Jaime Adeaner, Ian J. Wassell and Xiaodong Wang. Performance comparisons between LRA receiver and other linear receivers will be provided. It will be shown that even with higher order constellation and when the