Iterative MIMO Detection and Channel Estimation Using Joint Superimposed and Pilot-Aided Training

Abstract

This paper presents a novel iterative detection and channel estimation scheme that combines the effort of superimposed training (ST) and pilot-aided training (PAT) for multiple-input multiple-output (MIMO) flat fading channels. The proposed method, hereafter known as joint mean removal ST and PAT (MRST-PAT), implements an iterative detection and channel estimation that achieves the performance of data-dependent ST (DDST) algorithm, with the difference that the data arithmetic cyclic mean is estimated and removed from data at the receiver’s end. It is demonstrated that this iterative and cooperative detection and channel estimator algorithm surpasses the effects of data detection identifiability condition that DDST has shown when higher orders of modulation are used. Theoretical performance of the MRST-PAT scheme is provided and corroborated by numerical simulations. In addition, the performance comparison between the proposed method and different MIMO channel estimation techniques is analyzed. The joint effort between ST and PAT shows that MRST-PAT is a solid candidate in communications systems for multiamplitude constellations in Rayleigh fading channels, while achieving high-throughput data rates with manageable complexity and bit-error rate (BER) as a figure of merit.

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“…Thus, the main advantages of this SIP based channel estimation are: high spectral efficiency, low complexity, and no prior knowledge about channels and noise required. Description of the SIP based channel estimation technique can be found in [11,26].…”

OTFS Channel Estimation And Data Detection Designs With Superimposed Pilots

“…The data-dependent superimposed training (DDST) scheme superimposes, in addition to pilots, the arithmetic mean of transmit data on the transmitted information symbols [15]. The DDST scheme, as explained in [16], has data identifiability problem. Reference [16] resolved it by proposing a hybrid solution, known as joint mean removal SP and pilot-aided training (PAT) for detection and channel estimation in MIMO system over flat-fading quasi-static channels.…”

“…The DDST scheme, as explained in [16], has data identifiability problem. Reference [16] resolved it by proposing a hybrid solution, known as joint mean removal SP and pilot-aided training (PAT) for detection and channel estimation in MIMO system over flat-fading quasi-static channels. The design in [16], similar to [10]- [12], requires channel to be time-invariant for a large number of frames, to compute the time average of received signals.…”

“…Reference [16] resolved it by proposing a hybrid solution, known as joint mean removal SP and pilot-aided training (PAT) for detection and channel estimation in MIMO system over flat-fading quasi-static channels. The design in [16], similar to [10]- [12], requires channel to be time-invariant for a large number of frames, to compute the time average of received signals. The SP-aided transmission in OFDM cannot be trivially extended for the delay-Doppler channel estimation in OTFS systems as the i) channel changes rapidly in the time-frequency domain; and ii) channel gain in the delay-Doppler domain varies across frames [8].…”