Jingbo Gao

Review: Independent component analysis for multiple-input multiple-output wireless communication systems

Independent component analysis (ICA), an efficient higher order statistics (HOS) based blind source separation technique, has been successfully applied in various fields. In this paper, we provide an overview of the applications of ICA in multiple-input multiple-output (MIMO) wireless communication systems, and introduce some of the important issues surrounding them. First, we present an ICA based blind equalization scheme for MIMO orthogonal frequency division multiplexing (OFDM) systems, with linear precoding for ambiguity elimination. Second, we discuss three peak-to-average power ratio (PAPR) reduction schemes, which do not introduce any spectral overhead. Third, we investigate the application of ICA to blind compensation for inphase/quadrature (I/Q) imbalance in MIMO OFDM systems. Finally, we present an ICA based semi-blind layer space-frequency equalization (LSFE) structure for single-carrier (SC) MIMO systems. Simulation results show that the ICA based equalization approach provides a much better performance than the subspace method, with significant PAPR reduction. The ICA based I/Q compensation approach outperforms not only the previous compensation methods, but also the case with perfect channel state information (CSI) and no I/Q imbalance, due to additional frequency diversity obtained. The ICA based semi-blind LSFE receiver outperforms its OFDM counterpart significantly with a training overhead of only 0.05%.

Non-redundant precoding and PAPR reduction in MIMO OFDM systems with ICA based blind equalization

We propose a non-redundant linear precoding scheme and three peak-to-average power ratio (PAPR) reduction schemes for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with independent component analysis (ICA) based blind equalization. The proposed precoding at the transmitter allows complete elimination of the ambiguity in the ICA equalized signals under certain conditions. The optimal design of precoding is investigated, and performance analysis on the ambiguity error probability is provided. The proposed PAPR reduction schemes are incorporated with precoding, and therefore do not introduce any spectral overhead compared to conventional PAPR reduction schemes. Simulation results show that the proposed blind structure provides a bit error rate (BER) performance which is much better than that of the subspace method, and close to the case with perfect channel state information (CSI) at the receiver. Furthermore, the proposed structure can reduce the PAPR of the transmit signals considerably.

Independent component analysis based semi-blind I/Q imbalance compensation for MIMO OFDM systems

We propose a novel semi-blind compensation scheme for both frequency-dependent and frequencyindependent I/Q imbalance based on independent component analysis (ICA) in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, where ICA is applied to compensate for I/Q imbalance and equalize the received signal jointly, without any spectral overhead. A reference signal is embedded in the transmitted signal with little power consumption and no spectral overhead introduced, to enable ambiguity elimination for the ICA output signal at the receiver. Moreover, channel interpolation is incorporated with layered space frequency equalization (LSFE) to enhance the system performance. Simulation results show that the proposed implicit compensation scheme can not only provide a better bit error rate (BER) performance and a higher bandwidth efficiency than the previous training based I/Q imbalance compensation method, but also outperform the ideal case with perfect channel state information (CSI) and no I/Q imbalance, due to additional frequency diversity.

Optimal asymmetric resource allocation with limited feedback for OFDM based relay systems

We propose an optimal asymmetric resource allocation scheme with limited feedback for wireless relay systems based on orthogonal frequency division multiplexing (OFDM) modulation. Unlike the previous work, we assume that the bits transmitted over the same subchannel from the source to the relay may be distributed over different subchannels when being forwarded from the relay to the destination. This not only increases the degree of freedom for transmission, but also reduces the transmission overhead significantly because the amount of feedback information required is independent of the number of subchannels. Furthermore, the transmission durations at the source and the relay are designed to be asymmetric, which also enhances the degree of freedom for transmission. Simulation results show that the proposed optimal asymmetric resource allocation scheme achieves a higher system capacity, and has less sensitivity to channel estimation errors than the previous work. It also demonstrates a fast convergence speed.

Genetic Algorithm Based Equalization for Direct Sequence Ultra-Wideband Communications Systems

We propose a genetic algorithm (GA) based equalization approach for direct sequence Ultra-wideband (DS-UWB) wireless communications, where GA is combined with a RAKE receiver to combat the inter-symbol interference (ISI) due to the frequency selective nature of UWB channels for high data rate transmission. Simulation results show that the proposed GA based structure significantly outperforms the RAKE receiver. It also provides a close bit error rate (BER) performance to the optimal maximum likelihood detection (MLD) approach, while requiring a much lower computational complexity.

Blind I/Q Imbalance Compensation Using Independent Component Analysis in MIMO OFDM Systems

I/Q imbalance, which is one of the radio frequency (RF) circuit impairments in direct conversion transmitter and receiver, introduces severe performance degradation in wireless communication systems. In this paper, we propose a novel blind compensation algorithm for both frequency-dependent and frequency-independent I/Q imbalance based on independent component analysis (ICA) in multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, where ICA, an efficient higher order statistics (HOS) based blind source separation technique, is applied to compensate for I/Q imbalance and equalize the received signals simultaneously. Moreover, precoding is employed to resolve the ambiguity in the ICA output signals. Simulation results show that the proposed approach can not only compensate for I/Q imbalance effectively, but also achieve frequency diversity gains and outperform the case with perfect channel state information (CSI) and no I/Q imbalance.

Kalman smoothing-based adaptive frequencydomain channel estimation for uplink multiple-input multiple-output orthogonal frequency division multiple access systems

This study investigates Kalman smoothing (KS)-based frequency-domain channel estimation for uplink multiple-input multiple-output (MIMO) orthogonal frequency division multiple access (OFDMA) systems with time-varying channels. The proposed KS channel estimation scheme significantly outperforms the recursive least squares (RLS) channel estimation in the high signal-to-noise ratio (SNR) range, because of more effective exploitation of the signal information. In addition, channel interpolation is employed to improve the channel estimation accuracy by exploiting the correlation between adjacent subcarriers. The proposed KS channel estimator can also achieve a bit error rate (BER) performance which is close to the case with perfect channel state information (CSI) with a training overhead of only 5%.

Kalman Filtering Based Compensation for I/Q Imbalance and CFO in Time-Varying MIMO OFDM Systems

I/Q imbalance and carrier frequency offset (CFO) are two typical radio frequency (RF) circuit analog impairments in wireless communication systems, and degrade the system performance severely. In this paper, we propose a novel Kalman filtering based compensation scheme for I/Q imbalance and CFO in time-varying MIMO OFDM systems. To circumvent CFO and track time variations of wireless communication channels, the CFO is absorbed into the state vector of the equivalent channel model. Moreover, the inter-carrier interference (ICI) caused by phase shift of the cyclic prefix (CP) in the equivalent system is removed by decision feedback filtering, which allows low complexity compensation on each subcarrier independently. Simulation results show that the proposed approach can compensate for I/Q imbalance and CFO effectively and is robust again time variations.

Genetic Algorithm Based Frequency Domain Equalization for DS-UWB Systems without Guard Interval

In this work, a genetic algorithm (GA) based frequency domain equalization (FDE) scheme referred to as FDE-GA, which does not require any guard interval (GI),is proposed for direct sequence-ultra wideband (DS-UWB) wireless communication systems and is shown to significantly outperform the RAKE receiver. The proposed FDE-GA receiver also has a dramatic complexity reduction over the previous RAKE-GA receiver, while achieving a comparable bit error rate (BER) performance. The FDE-GA structure achieves a much higher bandwidth efficiency than conventional FDE methods, because the inter-block-interference (IBI), as a result of the absence of the GI, is removed effectively within each block before the GA.

Linear Least Squares CFO Estimation and Kalman Filtering Based I/Q Imbalance Compensation in MIMO SC-FDE Systems

This paper investigates carrier frequency offset (CFO) estimation and inphase/quadrature (I/Q) imbalance compensation in time-varying frequency-selective channels. We first propose a linear least squares (LLS) CFO estimation approach which has a lower complexity and a higher accuracy than the previous nonlinear CFO estimation methods. We then propose a Kalman filtering based I/Q imbalance compensation approach in the presence of CFO, which demonstrates a good ability to track the channel time variations with a fast convergence speed, by nulling the cyclic prefix (CP) and including the CFO in the state vector of the equivalent channel model. The proposed Kalman filtering based I/Q imbalance compensation approach with associated equalization tracks the time variation with a fast convergence speed. Simulation results show that the proposed compensation approach for CFO and I/Q imbalance provides a bit error rate (BER) performance close to the ideal case with perfect channel state information (CSI), no CFO and no I/Q imbalance.