MIMO OFDM receivers for systems with IQ imbalances

Orthogonal frequency division multiplexing (OFDM) is a widely recognized modulation scheme for high data rate communications. However, the implementation of OFDM-based systems suffers from in-phase and quadrature-phase (IQ) imbalances in the front-end analog processing. Such imbalances are caused by the analog processing of the received radio frequency (RF) signal, and they cannot be efficiently or entirely eliminated in the analog domain. The resulting IQ distortion limits the achievable operating SNR at the receiver and, consequently, the achievable data rates. The issue of IQ imbalances is even more severe at higher SNR and higher carrier frequencies. In this paper, the effect of IQ imbalances on multi-input multioutput (MIMO) OFDM systems is studied, and a framework for combating such distortions through digital signal processing is developed. An input-output relation governing MINIO OFDM systems is derived. The framework is used to design receiver algorithms with compensation for IQ imbalances. It is shown that the complexity of the system at the receiver grows from dimension (n(R) x n(T)) for ideal IQ branches to (2n(R) X 2n(T)) in the presence of IQ imbalances. However, by exploiting the structure of space-time block codes along with the distortion models, one can obtain efficient receivers that are robust to IQ imbalances. Simulation results show significant improvement in the achievable BER of the proposed MINIO receivers for space-time block-coded OFDM systems in the presence of IQ imbalances

On the baseband compensation of IQ imbalances in OFDM systems

OFDM is a widely recognized and standardized modulation scheme for future high bit rate communications. Implementation of OFDM-based systems suffers from inphase-quadrature phase (IQ) imbalances in the front-end analog processing. The IQ imbalances can severely limit the operating SNR and, consequently, the supported constellation sizes. In this paper, the effect of IQ imbalances on OFDM receivers is analyzed and system level algorithms to compensate for these distortions are proposed. The algorithms include different post and pre-FFT estimation and correction techniques

Joint compensation of transmitter and receiver impairments in OFDM systems

The implementation of OFDM-based systems suffers from impairments such as in-phase and quadrature-phase (IQ) imbalances in the front-end analog processing. Such imbalances are caused by the analog processing of the radio frequency (RF) signal and can be present at both the transmitter and receiver. The resulting IQ distortion limits the achievable operating SNR at the receiver and the achievable data rates. In this paper, the effect of both the transmitter and receiver IQ imbalances in an OFDM system is studied and algorithms are developed to compensate for such distortions in the digital domain. The algorithms include post-FFT least-squares and adaptive equalization, as well as a pre-distortion scheme at the transmitter and a pre-FFT correction at the receive

Least mean-phase adaptive filters with application to communications systems

The mean-squared-error criterion is widely used in the literature. However, there are applications where the squared-error is not the primary parameter affecting the performance of a system. In many communication systems, for instance, the information bits are carried over the phase of the transmitted signal. In this letter, we introduce a cost function that is based on both the error magnitude and the phase error. The criterion is useful for applications where the performance depends primarily on the phase of the estimated (recovered) signal. An adaptive filter is then developed using the proposed criterion with essentially the same complexity as the standard least mean squared (LMS) algorithm. The filter outperforms LMS specially in situations with fast channel variations. Bit error rate (BER) simulations for two communication systems using the proposed algorithm support the claims

An optimum OFDM receiver exploiting cyclic prefix for improved data estimation

Orthogonal frequency division multiplexing (OFDM) is a promising technique for multi-antenna broadband systems, since it significantly reduces receiver complexity by providing orthogonal subchannels. A drawback of OFDM systems is the performance/rate reduction due to the cyclic prefix overhead. We propose receiver structures that exploit the cyclic prefix to increase the performance of the link. The proposed structures use the standard OFDM transmitter, and the modifications are only made at the receiver. Optimum receivers in both the least-mean-squares and least-squares senses are presented, and they do not result in any extra processing complexity compared to the standard OFDM receiver. The proposed architecture is further extended to a MIMO OFDM structure. Simulation results validate the improved performance of the proposed receiver

A Dynamic Antenna Scheduling Strategy for Multi-User MIMO Communications

The paper develops a dynamic antenna scheduling strategy for downlink MIMO communications, where the transmitted signal for each user is beamformed towards a selected subset of receive antennas at this user. The proposed method removes the condition on the number of transmit-receive antennas in comparison to traditional zero-forcing and time-scheduling strategies. By characterizing the probability distribution of the so-called signal-to-leakage-plus-noise (SLNR) ratio, we show that there is an optimal set of receive antennas that maximizes the system performance for each channel realization. This fact is used to propose an antenna scheduling scheme that leads to improvements in terms of SINR outage probabilities

An uplink DS-CDMA receiver using a robust post-correlation Kalman structure

Kalman filtering has been proposed in the literature for wireless channel estimation, however, it is not sufficiently robust to uncertainties in the channel auto-correlation model as well as to multiple access interference (MAI). This paper presents a receiver structure for direct-sequence code-division multiple-access (DS-CDMA) systems by using robust Kalman estimation and post-correlation (i.e., symbol rate) processing for channel estimation. The proposed structure is also generalized to incorporate multiple-antenna combining and interference cancellation techniques. The resulting receiver outperforms earlier structures in the presence of channel modeling uncertainties, MAI, and low-received signal-to-noise ratio. The enhancement in performance is achieved at the same order of complexity as a standard Kalman-based receiver

Joint Compensation of IQ Imbalance and Phase Noise in OFDM Systems

The joint effects of IQ imbalance and phase noise on OFDM systems are analyzed, and a compensation scheme is proposed to improve the system performance. The scheme consists of a joint channel estimation algorithm and a joint data symbol estimation algorithm. In the proposed channel estimation algorithm, the channel coefficients are jointly estimated with the IQ imbalance parameters and the phase noise components. Its performance is demonstrated to be close to the associated Cramer-Rao lower bound. In the proposed data symbol estimation algorithm, the joint compensation is decomposed into IQ imbalance compensation and phase noise compensation. It is shown both by theory and computer simulations that the proposed scheme can effectively improve the signal-to-noise ratio at the receiver. As a result, the sensitivity of OFDM receivers to the physical impairments can be significantly lowered, simplifying the RF and analog circuitry design in terms of implementation cost, power consumption, and silicon fabrication yield