Coded Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing Research Articles

Coded OFDM Waveforms for MIMO Radars

Emerging digital radar concepts such as orthogonal frequency-division multiplexing (OFDM) allow flexible signal generation. This opens up new opportunities in waveform design in a multiple-input multiple-output (MIMO) system such as introducing coding for signal multiplexing. In this article, coded MIMO OFDM waveforms are proposed and investigated that allow continuous and simultaneous wideband transmission for all transmitters of a multiple transmit and receive antenna array for spatial radar environment perception. Challenges for coded MIMO OFDM radar operation are derived, and three coded MIMO strategies are introduced and analyzed. Their potential is validated and compared to the standard subcarrier interleaving OFDM approach using simulations and measurements of an experimental 4 × <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ 4$</tex-math></inline-formula> MIMO OFDM radar at 77GHz.

Performance optimization of iterative receiver for wireless communications based on realistic channel conditions

Adopting orthogonal frequency division multiplexing (OFDM) to low-density parity check (LDPC) coded multiple-input multiple-output (MIMO) is attractive scheme for wireless communication systems. An iterative receiver design for LDPC coded MIMO-OFDM system is proposed as the foundation for enhancing the wireless link performance can deliver the coverage, speed, throughput and reliability. However, in previous works, evaluations are basically assumed for a certain channel scenario and it is inefficient in incorporating different channel scenarios. The aim of this paper is to improve the system range for equivalent error rate, while not significantly increasing system complexity compared to conventional iterative receiver solution under realistic channel environment. We show that our proposed iteration adaptation at receiver can considerably adopt the system to realistic change environment, and reach very high reliability. Simulations of our optimization reveal superior error rate performance and lower computational cost vs. conventional LDPC coded MIMO OFDM system. Our simulation results also capture the effects of realistic vs. typical channel fading types (i.e., Rician vs. Rayleigh, respectively) and fading parameter models (average vs. random azimuth spread and K factor) on system performance and complexity.

Semiblind Iterative Receiver for Coded MIMO-OFDM Systems

In this paper, a semiblind iterative receiver is proposed for coded multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. A novel iterative extended soft-recursive least square (IES-RLS) estimator for joint channel and frequency offset estimation is introduced. Extrinsic bit information obtained from the channel decoder and expected symbol decisions obtained from the demodulator are simultaneously exploited by the IES-RLS. The proposed receiver combines the MIMO data demodulator, the proposed channel estimator, and the channel decoder in an iterative manner to yield an improved bit error rate (BER) performance. To arrive at a feasible algorithm, the first-order linearization of the received vector signal with respect to the frequency offset is used in the IES-RLS channel estimator. The BER performance, a constellation-constrained mutual information analysis, and an EXIT chart analysis are used to verify the effectiveness of the proposed receiver. Simulation results show the superiority of the proposed semiblind receiver, compared with conventional semiblind receivers.

Adaptation in Convolutionally Coded MIMO-OFDM Wireless Systems Through Supervised Learning and SNR Ordering

Multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) wireless systems use link adaptation to exploit the dynamic nature of wireless environments. Link adaptation maximizes throughput while maintaining target reliability by adaptively selecting the modulation order and coding rate. Link adaptation is extremely challenging, however, due to the difficulty in predicting error rates in OFDM with binary convolutional codes, bit interleaving, MIMO processing, and real channel impairments. This paper proposes a new machine-learning framework that exploits past observations of the error rate and the associated channel-state information to predict the best modulation order and coding rate for new realizations of the channel state without modeling the input-output relationship of the wireless transceiver. Our approach is enabled through our new error-rate expression that is only parameterized by postprocessing signal-to-noise ratios (SNRs), ordered over subcarriers and spatial streams. Using ordered SNRs, we propose a low-dimensional feature set that enables machine learning to increase the accuracy of link adaptation. An IEEE 802.11n simulation study validates the application of this machine-learning framework in real channels and demonstrates the improved performance of SNR ordering as it compares with competing link-quality metrics.

Analytical Performance Evaluation of Space Time Coded MIMO OFDM Systems Impaired by Fading and Timing Jitter

An analytical approach is presented to determine the impact of time selective fading, timing jitter and additive white Gaussian noise (AWGN) on the bit error rate (BER) performance of an orthogonal frequency- division multiplexing (OFDM) system with differential quaternary phase-shift keying (DQPSK), differential phase- shift keying (DPSK) and quaternary phase-shift keying (QPSK) modulation. The expression for the conditional BER conditioned on a given timing error and fading, is derived and the average BER is evaluated. The BER performance results are evaluated for different values of fading and jitter. The performance of the OFDM system in Rayleigh and Rician fading channels is also compared. Analytical approach is also developed to evaluate the BER performance of a quasi-orthogonal- space-time block coded OFDM system having multiple transmitting and single receiving antennas. The analysis is extended for a multiple- input multiple-output (MIMO)-OFDM system using the selection method for combining multiple receiving antennas, which offers significant improvement in the system performance. The effects of increase in number of OFDM subcarriers and increase in Doppler frequency are also investigated.

Turbo Processing for Joint Channel Estimation, Synchronization, and Decoding in Coded MIMO-OFDM Systems

This paper proposes a turbo joint channel estimation, synchronization, and decoding scheme for coded multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The effects of carrier frequency offset (CFO), sampling frequency offset (SFO), and channel impulse responses (CIRs) on the received samples are analyzed and explored to develop the turbo decoding process and vector recursive least squares (RLSs) algorithm for joint CIR, CFO, and SFO tracking. For burst transmission, with initial estimates derived from the preamble, the proposed scheme can operate without the need of pilot tones during the data segment. Simulation results show that the proposed turbo joint channel estimation, synchronization, and decoding scheme offers fast convergence and low mean squared error (MSE) performance over quasistatic Rayleigh multipath fading channels. The proposed scheme can be used in a coded MIMO-OFDM transceiver in the presence of multipath fading, carrier frequency offset, and sampling frequency offset to provide a bit error rate (BER) performance comparable to that in an ideal case of perfect synchronization and channel estimation over a wide range of SFO values.