Abstract-In adaptive time division duplex (TDD) broadcast multi-antenna orthogonal frequency division multiplexing (OFDM) systems, non-reciprocal transceiver chains at the base station (BS) cause multi-user interference. This is due to the inappropriate spatial filter design at the BS based on the reverse link estimate. Hence, BS transceiver calibration is required. Provided that an estimate of the forward link channel is available at the BS, e.g., in a calibration phase, the transceiver parameters can be estimated by solving a total least squares (TLS) problem. In addition, if mutual coupling between the antennas exists the number of unknown front-end parameters to be estimated increases. Consequently, large matrices need to be decomposed via singular value decomposition (SVD) to attain a calibrated system. To deal with these large matrices a conjugate gradient (CG) method for solving the TLS problem iteratively is proposed in this paper. Simulation results show that the calibration based on the CG method achieves almost the same performance compared to the TLS solution but with significantly reduced complexity.
One major drawback of Orthogonal Frequency Division Multiplexing (OFDM) is the large peak-to-average power-ratio (PAPR), which significantly degrades the power efficiency. In order to prevent nonlinear distortions the PAPR needs to be minimized to guarantee a linear dynamic range of the high power amplifier. Therefore, various reduction algorithms have been proposed. However, they do not include link adaptation requirements. Previous results show that bit and power loading algorithms in adaptive OFDM systems fail to meet the target error rate requirements if large time-domain peaks occur. Hence, in this paper a joint utilization of extended constellation alphabets of active subcarriers and tone reservation for peak power reduction in adaptive OFDM systems is derived. The resulting linear programming (LP) problem can be efficiently solved and the solution is lossless in terms of throughput. Furthermore, a suboptimal algorithm, which achieves great PAPR reduction with lower complexity, is proposed while link adaptation is employed.
Abstract-Currently evolving communication standards, especially those using multi-antenna (MIMO) multicarrier modulation techniques, are based on the exploitation of channel state information (CSI) at the transmitter. The utilization of adaptive transmission schemes comes with a more sensitive behavior with respect to front-end imperfections. Direct-conversion architectures in turn allow for low-cost transceiver solutions but introduce higher imbalances of the in-phase (I) and quadrature (Q) branches. For adaptive systems with high data rates severe performance losses are observed with respect to bit error rates (BER). In this paper the influence of transmitter side I/Q imbalances is investigated with respect to a MIMO hardware demonstrator, which applies adaptive Orthogonal Frequency Division Multiplexing (OFDM) strategies. An enhanced algorithm for blind online pre-compensation is presented. Comparable single-tone low-IF measurement results indicate an improved image signal suppression and higher convergence robustness while the system shows decreased downlink BER after compensation.
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