Performance and Compensation of I/Q Imbalance in Differential STBC-OFDM

Abstract

Differential space time block coding (STBC) achieves full spatial diversity and avoids channel estimation overhead. Over highly frequency-selective channels, STBC is integrated with orthogonal frequency division multiplexing (OFDM) to achieve high performance. However, low-cost implementation of differential STBC-OFDM using direct-conversion transceivers is sensitive to In-phase/Quadrature-phase imbalance (IQI). In this paper, we quantify the performance impact of IQI at the receiver front-end on differential STBC-OFDM systems and propose a compensation algorithm to mitigate its effect. The proposed receiver IQI compensation works in an adaptive decision-directed manner without using known pilots or training sequences, which reduces the rate loss due to training overhead. Our numerical results show that our proposed compensation algorithm can effectively mitigate receive IQI in differential STBC-OFDM.

Performance Analysis and Compensation of Joint TX/RX I/Q Imbalance in Differential STBC-OFDM

“…Thus, all subcarriers over all OFDM symbols have the same compensation matrix. To estimate this matrix, we only need to estimate a scalar γ r = −β r /α * r and this is similar to [17] and [22] which discuss RX-IQI compensation. Consequently, by setting γ = γ r 0 , after some manipulation, the estimator in Eq.…”

“…We extend the work in [22] which only analyzes and compensates for the effect of the RX-IQI in the differential STBC-OFDM (DSTBC-OFDM) transmission. In this paper, we analyze the joint impact of TX-IQI and RX-IQI in DSTBC-OFDM systems.…”

An Efficient Transmitter Feature Extraction Scheme with IQ Imbalance and Nonlinearity in TDD OFDM Systems

“…The CSI and IQI were independently estimated based on the pilot by using linear estimation technology in a multiuser single-input-multiple-output (MU-SIMO) system; first, the linear minimum mean squared error (LMMSE) was used to estimate the CSI, and then LS was used to estimate the IQI, thus achieving the separation of the CSI and IQI parameters due to the assumption of IQI at the receiver only [9]. The transmitter (TX) and receiver (RX) IQI compensation problem in differential space-time block-coded orthogonal frequency division multiplexing (STBC-OFDM) systems was studied in [10] and developed further in [11]; the TX and RX IQIs were extracted by employing an algorithm based on a widely linear estimation. An iterative decision feedback (DFB) receiver was proposed to compensate for the IQI due to imperfections in the transceiver RF link for a single carrier with a frequencydomain equalization (SC-FDE) system [12].…”

“…In such works, a number of simulated and practical trials were conducted, thus verifying the efficiency and reliability of their proposed methods. Nevertheless, unlike traditional approaches [7][8][9][10][11][12][13][14][15][16][17][18], machine learning is powerless in environments without samples, due to its requirements for learning.…”

Performance Analysis of Single Carrier Coherent and Noncoherent Modulation under I/Q Imbalance

“…Moreover, the authors in [11] derived the SER of OFDM with M−QAM constellation, over frequency selective channels with RX IQI, whereas the authors in [12] quantified the effects of IQI on the outage probability of both single-carrier and multi-carrier systems over N*Nakagami-m fading conditions. Likewise, the error rate of free-space optical systems using subcarrier intensity modulated QPSK over Gamma-Gamma fading channels with receiver IQI was investigated in [13], while Chen et al recently analyzed the impact of IQI on differential space time block coding (STBC)-based OFDM systems by deriving an error floor and approximations for the corresponding BER [14], [15]. Finally, IQI has also been studied in half-duplex (HD) and full duplex (FD) amplify and forward (AF) and decode and forward (DF) coopeartive systems [16]- [19], as well as two-way relay systems and multi-antenna systems [20]- [22].…”