Partially Loaded Superimposed Training Scheme for Large MIMO Uplink Systems

This paper proposes a new superimposed training (ST) scheme for uplink multi-user multi-cell system, where each base station, equipped with a large number of antennas (M), communicates to single antenna users. In uplink training phase, large number of users within limited coherence time introduces the pilot contamination, which causes two types of interferences in data estimation. The first type, which is referred as self interference, arises due to the dependence between channel estimate and estimation error of the same user, while the second type, known as cross interference, occurs because of the correlation between ST vectors of different users. In this paper, an ST scheme with variable data length is proposed for Rician fading channels. For simplicity of analysis, a single cell model is considered first to derive mean squared error and signal to interference plus noise ratio. The analysis is further extended to multi-cell system. Various limiting cases are investigated, and the design parameters viz., power allocation factor and length of data vector, are optimized. Simulation results verify that the proposed ST scheme reduces self interference, and yields sum rate improvement over conventional ST scheme.