Time-varying Rician Fading Channel Research Articles

UAV-enabled reliable mobile relaying under the time-varying Rician fading channel

This paper adopts an unmanned aerial vehicle (UAV) relay to forward data from a source sensor to a remote base station (BS). To ensure reliable data transmission, our objective is to minimize the average outage probability along the three-dimensional (3D) UAV trajectory under the UAV mobility and source/relay power allocation constraints. The UAV mobility causes the time-varying Rician fading channel, thus the outage probability function considers both the distance-based large-scale fading and a time-varying Rician factor. To tackle our formulated non-convex problem, we approximate the outage probability by its first-order asymptotic form, based on which we propose a block coordinate descent (BCD) iteration algorithm by alternatively solving the 3D UAV trajectory and power allocation subproblems. The successive convex optimization (SCO) method is applied to deal with the 3D UAV trajectory subproblem. To reveal the advantage by designing the 3D UAV trajectory, we also consider joint optimization of the two-dimensional (2D) UAV trajectory and power allocation to minimize the average outage probability. Extensive simulations verify the accuracy of the approximate outage probability, and the results show that considering the time-varying Rician fading channel, the 3D UAV trajectory helps to obtain a lower link outage probability than the 2D UAV trajectory.

Self-Interference Channel Training for Full-Duplex Massive MIMO Systems.

Full-duplex (FD) is a promising technology for increasing the spectral efficiency of next-generation wireless communication systems. A major technical challenge in enabling FD in a real network is to remove the self-interference (SI) caused by simultaneous transmission and reception at the transceiver, and the SI cancellation performance depends significantly on the estimation accuracy of the SI channel. In this study, we proposed a novel partial SI channel training method for minimizing the residual SI power for FD massive multiple-input multiple-output (MIMO) systems. Based on an SI channel training framework under a limited training overhead, using the proposed scheme, the BS estimates only a part of the SI channel vectors, while skipping the channel training for the other remaining SI channel vectors by using their last estimates. With this partial training framework, the proposed scheme finds the optimal partial SI channel training strategy for pilot allocation to minimize the expected residual SI power, considering the time-varying Rician fading channel model for the SI channel. Therefore, the proposed scheme can improve the sum-rate performance compared with other simple partial training schemes for FD massive MIMO systems under a limited training overhead. Numerical results confirm the effectiveness of the proposed scheme for FD massive MIMO systems compared with the full training scheme, as well as other partial training schemes.

Impact of Doppler shift error on least‐squares MIMO channel estimation for high‐speed railway

Owing to the availability of Doppler shift measurement and the existence of dominant line-of-sight (LOS) path in high-speed railway (HSR) communications, Doppler shift is often pre-compensated on the received signal before performing further processing. In this study, the authors address the impact of erroneous Doppler shift measurement on the tracking performance of least-squares multiple-input multiple-output (MIMO) channel estimation for HSR. The closed-form tracking mean-square error (MSE) is derived over time-varying Rician fading channel assuming Gaussian distributed Doppler shift measurement. By transforming the Gaussian distributed measurement into its characteristic function and performing approximations with practical considerations, the tracking MSE of the approach with Doppler shift pre-compensation is written as a function of that with no pre-compensation, contributed from the previous research. Accordingly, they are able to develop a simple relation between MSE gain and MSE loss for channels with dominant LOS path. It is revealed that erroneous Doppler shift measurement impacts stronger LOS or faster time-varying channel more severely. However, if the measurement is perfect, the presence of a dominant LOS path provides tremendous gain approximately equal to the Rician factor in high signal-to-noise ratio (SNR) regime.

Performance of Convolutional Codes in A-CDMA Systems over Time-Varying Rician Fading Channels

In this letter, the analytical and simulated performance of punctured convolutional codes in an Asynchronous Code Division Multiple Access (A-CDMA) system under imperfect phase tracking conditions are discussed. A time-varying Rician fading channel is assumed. Analytical results show the variation of the Bit Error Rate (BER) with nominal loop Signal-to-Noise Ratio (SNR) and the ratio of the loop bandwidth to the local oscillator bandwidth, $${\dfrac{B_o}{B_{Lo}}}$$ , in a phase locked loop. Simulated results are found to agree well with the analytical results.

Performance of convolutional codes with finite-depth interleaving and noisy channel estimates

In this paper, we derive the Chernoff bound of the pairwise error probability (PEP) and the exact PEP of convolutional codes in a time-varying Rician fading channel. With the assumptions that the channel estimator is a finite impulse response filter and the interleaving depth is finite, we are able to investigate the estimation-diversity tradeoff resulting from the effects of the Doppler spread on the system performance via the channel-estimation accuracy and the channel diversity. In addition, we verify that, in the special case when the pilot signal-to-noise ratio is infinitely large and the channel estimator is well-designed, our analysis leads to the same result as the existing perfect channel-state information analysis. Finally, the analytical results are compared with results from Monte Carlo simulation, and the comparison shows that the analytical results match well with the simulation results

Performance of Convolutional Codes With Finite-Depth Interleaving and Noisy Channel Estimates

In this paper, we derive the Chernoff bound of the pairwise error probability (PEP) and the exact PEP of convolutional codes in a time-varying Rician fading channel. With the assumptions that the channel estimator is a finite impulse response filter and the interleaving depth is finite, we are able to investigate the estimation-diversity tradeoff resulting from the effects of the Doppler spread on the system performance, via the channel estimation accuracy and the channel diversity. In addition, we verify that, in the special case when the pilot signal-to-noise ratio is infinitely large and the channel estimator is well-designed, our analysis leads to the same result as the existing perfect channel-state information analysis. Finally, the analytical results are compared with results from Monte Carlo simulation, and the comparison shows that the analytical results match well with the simulation results.

Differential detection with IIR filter for improving DPSK detection performance

This paper presents a method for improving the performance of differential detection of differentially encoded phase shift keying (DPSK). The structure of the proposed detection scheme consists of a conventional differential detection circuit equipped with an infinite impulse response (IIR) filter combined with decision feedback. The results of theoretical analysis and computer simulation show that performance of the proposed detection method can approach that of coherent detection of DPSK under additive white Gaussian noise (AWGN) conditions without any increase in architectural complexity. Furthermore, a parameter of the proposed detector can be varied to optimize performance for static or fading conditions. An adaptive scheme suitable for time varying Rician-fading channel conditions is presented, and performance results obtained by computer simulation are given.