Abstract
Channel estimation algorithms and their implementations for mobile receivers are considered in this paper. The 3GPP long term evolution (LTE) based pilot structure is used as a benchmark in a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) receiver. The decision directed (DD) space-alternating generalized expectation-maximization (SAGE) algorithm is used to improve the performance from that of the pilot symbol based least-squares (LS) channel estimator. The performance is improved with high user velocities, where the pilot symbol density is not sufficient. Minimum mean square error (MMSE) filtering is also used in estimating the channel in between pilot symbols. The pilot overhead can be reduced to a third of the LTE pilot overhead with DD channel estimation, obtaining a ten percent increase in data throughput. Complexity reduction and latency issues are considered in the architecture design. The pilot based LS, MMSE and the SAGE channel estimators are implemented with a high level synthesis tool, synthesized with the UMC 0.18 \(\mu \)m CMOS technology and the performance-complexity trade-offs are studied. The MMSE estimator improves the performance from the simple LS estimator with LTE pilot structure and has low power consumption. The SAGE estimator has high power consumption but can be used with reduced pilot density to increase the data rate.
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