Interference Suppression with Antenna Arrays in OFDM Systems under Transceiver I/Q Imbalance

Hakkarainen, Aki; Werner, Janis; Dandekar, Kapil R.; Valkama, Mikko

doi:10.4108/icst.crowncom.2014.255187

Cited by 1 publication

(3 citation statements)

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“…The results in Fig. 6 also extend the work related to the SU-SIMO scenario in [30] and show somewhat similar behavior in both cases.…”

Section: B Sinr and Ser Simulation Results And Analysissupporting

confidence: 83%

“…A well-known statistical method for solving stationary estimation problems is the so-called Wiener filter which yields the optimal linear solution in the MMSE sense [43]. We have shown in [30] that the Wiener filter approach, when generalized to augmented or widely-linear processing, can be successfully used for the channel and hardware characteristic estimation problem under I/Q imbalance in SU-SIMO systems. Here this simple and intuitive approach is extended to cover the weight selection problem in the considered MU-MIMO OFDMA systems whereas other weight optimization methods could be used as well.…”

Section: Linear and Augmented Linear Mmse Combinersmentioning

confidence: 99%

“…Some of the studies also make somewhat limited assumptions of equal I/Q imbalance coefficients between different subcarriers and/or transceiver branches. Our earlier study in [30] focused on the external interference suppression with antenna array processing in OFDM systems but the study was limited only to the single-user single-input multiple-output (SU-SIMO) scenario. The rather limited SU-SISO and SU-MIMO schemes are considerable simpler than the full MU-MIMO transmission from the viewpoints of the signal models and associated signal processing algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Analysis and Augmented Spatial Processing for Uplink OFDMA MU-MIMO Receiver With Transceiver I/Q Imbalance and External Interference

Hakkarainen

Werner

Dandekar

et al. 2016

IEEE Trans. Wireless Commun.

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Abstract-This paper addresses receiver (RX) signal processing in multiuser multiple-input multiple-output (MU-MIMO) systems. We focus on uplink orthogonal frequency-division multiple access (OFDMA)-based MU-MIMO communications under inphase/quadrature (I/Q) imbalance in the associated radio frequency electronics. It is shown in the existing literature that transceiver I/Q imbalances cause cross-talk of mirror-subcarriers in OFDM systems. As opposed to typically reported single-user studies, we extend the studies to OFDMA-based MU-MIMO communications, with simultaneous user multiplexing in both frequency and spatial domains, and incorporate also external interference from multiple sources at RX input, for modeling challenging conditions in increasingly popular heterogeneous networks. In the signal processing developments, we exploit the augmented subcarrier processing, which processes each subcarrier jointly with its counterpart at the image subcarrier, and jointly across all RX antennas. Furthermore, we derive an optimal augmented linear RX in terms of minimizing the meansquared error. The novel approach integrates the I/Q imbalance mitigation, external interference suppression and data stream separation of multiple UEs into a single processing stage, thus avoiding separate transceiver calibration. Extensive analysis and numerical results show the signal-to-interference-plus-noise ratio (SINR) and symbol-error rate (SER) behavior of an arbitrary data stream after RX spatial processing as a function of different system and impairment parameters. Based on the results, the performance of the conventional per-subcarrier processing is heavily limited under transceiver I/Q imbalances, and is particularly sensitive to external interferers, whereas the proposed augmented subcarrier processing provides a high-performance signal processing solution being able to detect the signals of different users as well as suppress the external interference This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.This efficiently. Finally, we also extend the studies to massive MIMO framework, with very large antenna systems. It is shown that, despite the huge number of RX antennas, the conventional linear processing methods still suffer heavily from I/Q imbalances while the augmented approach does not have such limitations.

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“…The results in Fig. 6 also extend the work related to the SU-SIMO scenario in [30] and show somewhat similar behavior in both cases.…”

Section: B Sinr and Ser Simulation Results And Analysissupporting

confidence: 83%

Section: Linear and Augmented Linear Mmse Combinersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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