Full-duplex operation requires effective self-interference (SI) cancellation that in turn needs reliable SI channel estimation. In this paper, we develop two estimation algorithms suitable for a 2-stage SI cancellation structure. By exploiting the sparsity of the SI channel, we first derive a compressed sensing-based SI channel estimation algorithm to be used in the first SI cancellation stage at radio-frequency (RF) to reduce the SI. We then develop a subspace-based algorithm to jointly estimate the residual SI channel, the intended channel and the transmitter nonlinearities for the second SI cancellation stage at baseband. Including the intended received signal in the estimation process is the main advantage of the proposed algorithm as compared to previous works that assume it as additive noise. Simulation results show that the proposed algorithms outperform the least-square (LS) algorithm and offer higher signal-to-residual-interference-and-noise ratio (SINR) over a large received signal-to-noise ratio (SNR) range.

Self-interference cancellation for full-duplex MIMO transceivers

We propose a novel iterative receiver for coded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Starting from the derivation of the optimal minimum mean squared error (MMSE) estimate of the transmitted data, we show that for BPSK and QPSK modulated signals, the soft estimate is a hyperbolic tangent function of the extrinsic information from the soft-input soft-output (SISO) decoder and the decision statistic from the detector. Compared with the conventional iterative receiver which computes the data estimate using only the decoder output, the proposed structure has significant performance gain, for example, it is 2.0 dB better for groupwise space time block coded (GSTBC) MIMO OFDM system at BER of 10/sup -6/, and 1.5 dB better for vertical Bell Lab layered space-time (VBLAST) OFDM system at BER of 10/sup -5/.

A novel iterative receiver for coded MIMO OFDM systems

A multiple-input multiple-output (MIMO) system with serially concatenated bit-interleaved coded modulation (BICM) and linear dispersion code (LDC) is investigated. LDC is a member of the family of linear space-time block codes STBC. A tight upper bound for this system over a spatially correlated Rician fading channel is derived, based on the moment generation function (MGF) approach. We utilize this bound to study the impact of the propagation environment features, such as the Rician factor, geometry of the Rician component, and transmit and receive antenna correlation, on the performance of a bit-interleaved convolutional-coded LDC MIMO system.

Bit-interleaved coded modulation in linear dispersion coded MIMO system over spatially correlated Rician fading channel

In this letter, we investigate a coded full-duplex (FD) bidirectional transceiver based on single-input multiple-output (SIMO). Iterative detection and decoding (IDD) are proposed to mitigate the residual self-interference (SI) remaining after applying passive suppression and two stages of SI cancellation (SIC) filters in analog and digital domains. IDD comprises an adaptive minimum mean-squared error (MMSE) filter with log-likelihood ratio (LLR) demapping, while the soft-in soft-out (SISO) decoder utilizes the maximum a posteriori (MAP) algorithm. The proposed system’s performance is evaluated in the presence of additive white Gaussian noise (AWGN) over SIMO Rayleigh fading channels. Simulation results are presented to demonstrate the bit-error rate (BER) performance as a function of the signal-to-noise ratio (SNR), demonstrating a close match to the SI-free case for the proposed system. Furthermore, we validate our results by deriving a tight upper bound on the performance of the proposed system using rate-1/2 convolutional codes together with quadrature phase-shift keying (QPSK) modulation, which asymptotically exhibits a close agreement with the simulated BER performance.

A Tight Upper Bound on the Performance of Iterative Detection and Decoding for Coded Full-Duplex SIMO Systems

We derive the pairwise error probability of convolutional codes in a time-varying Rayleigh fading channel with finite interleaving depth and noisy channel estimates. The analysis quantifies the estimation-diversity tradeoff, which results from the opposite effects of the Doppler spread on the channel estimation accuracy and the channel diversity. It is also shown that when the channel estimates are correct, this analysis gives the same result as an existing perfect channel estimation analysis.

Performance of finite-depth interleaved convolutional codes in a Rayleigh fading channel with noisy channel estimates

In this paper, we have analyzed the convolutional coded error performance of a 2D-RAKE receiver, in combination with transmit diversity on the downlink of a WCDMA system The analyses assume correlated fading between receive antenna array elements, and an arbitrary number of independent but nonidentical resolvable multipaths combined by the RAKE receiver in the general Nakagami-m fading channel framework The closed form expression of pairwise error probability is given in the simple form of a single finite limit integral, with the integrand being an elementary function of array configuration parameters, spatial correlation and operating environment factors It is shown that the combination of coding and spatial-path combining lead to dramatic performance improvement in various fading environments

Coded error performance of MIMO systems in frequency selective Nakagami fading channels

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Coded error performance of MIMO systems in frequency selective Nakagami fading channels