Enhanced SIC and Initial Guess ML Receivers for Collaborative MIMO of the LTE Uplink

Abstract

In this paper, Collaborative MIMO is introduced to the Uplink of the Long Term Evolution (LTE) system. This technique uses two or more single carrier frequency division multiple access based user equipments (UEs) equipped with single antenna. These UEs transmit their data collaboratively over the same Resource block (RB), and then the Evolved Node B (eNodeB) separates the users' data by means of multiuser frequency domain equalization. This will increase the whole throughput of the LTE Uplink, besides moving the complexity of implementing multiple antennas to the eNodeB. In order to decode the data ZF, MMSE and successive interference cancellation (SIC) are employed although they didn't exploit the full spatial diversity, whereas the standard ML is abandoned for its exponential complexity. In this paper, we propose a novel Initial Guess based ML (IGML) receiver whose complexity is in the same order of ML receiver of OFDM-MIMO systems, and a QR based simplified ML receiver. We also propose two ordering techniques for the SIC receiver when used in shadowing environment, as well as various simulation parameters are examined to find the best collaborating environments. The simulation results reveal that the IGML receiver is far by almost 4.5dB at target BER of 10-4 from the traditional MMSE receiver.