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

Abstract

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.

Precoded massive MU-MIMO uplink transmission under transceiver I/Q imbalance

“…This is a well-known phenomenon, discussed e.g. in [9], [11], [13]- [15]. In general, when the image subcarrier c ′ is allocated to another UE v, this results in cross-talk between UEs at mirror subcarriers.…”

“…However, when considering I/Q imbalance in the TX electronics of an individual UE, the transmitted antenna signal vector of UE u at subcarrier c becomes [9], [13] s Txi,u,c = K Tx1,u,c s u,c + K Tx2,u,c s *…”

“…Starting from I/Q imbalance modeling in uplink orthogonal frequency division multiple access (OFDMA) based massive MU-MIMO systems, we show that I/Q imbalance in the RF front-ends causes signal distortion where each subcarrier signal is interfered by the signals at the image subcarrier, implying hence inter-user interference. Stemming from this phenomenon and based on the earlier I/Q imbalance studies in [6]- [9], we exploit the so-called augmented spatial post-processing at RX, now taking into account the effects of precoding in uplink transmitters (TXs). We derive the minimum mean-square error (MMSE)-optimal augmented spatial post-processing solution, and by simulating the system performance as a funtion of multiple system parameters, we show that the proposed solution outperforms the traditional per-subcarrier processing clearly and thus provides significant performance improvements without costly changes in the associated RF front-ends.…”

Optimal Power Allocation for OFDMA Systems under I/Q Imbalance

“…Various approaches have been proposed so far to eliminate, compensate, and mitigate the effects of IQI using baseband signal processing techniques at the receiver (RX) (see [11]- [15], and references therein). For example, in [11], the authors presented an IQI mitigation method for orthogonal frequency division multiple access (OFDMA) systems, in which each subcarrier is processed jointly with its counterpart at the image subcarrier.…”

“…For example, in [11], the authors presented an IQI mitigation method for orthogonal frequency division multiple access (OFDMA) systems, in which each subcarrier is processed jointly with its counterpart at the image subcarrier. All previously mentioned works deal with IQI at the RX by employing digital signal processing.…”