Non-stationary Channel Research Articles

Algorithms for noncoherent iterative reception of signals based on serial turbo codes and Walsh signals during transmission over nonstationary channels

The results of simulating the algorithms developed for noncoherent iterative reception of signals based on highly redundant serial turbo codes and Walsh signal ensembles are presented. It is assumed that transmission is carried out over nonstationary channels.

Amplitude-goniometric passive location of an emitting target in the nonstationary radio channel

The further development of the concept related to passive direction finders (DFs) equipped with an energy-measurement channel is implemented. The goniometric-energy method of passive detection and ranging, according to which the slant distance to a target can be determined from its emission in the form of a constant-envelope signal, is generated as applied to the given stationary DFs. In the spatial case, the passive location problem is solved using the time-dependent behavior of the generalized radiolocation coefficient. A complex algorithm is constructed with the aim at jointly estimating the given coefficient and the detection range under the condition that rectilinear uniform motion of an emitting target is simulated on the estimation interval. The computational experiment results are presented to confirm the possibility of practical application of the proposed method.

Exploiting Mobility in Proportional Fair Cellular Scheduling: Measurements and Algorithms

Proportional Fair (PF) scheduling algorithms are the de facto standard in cellular networks. They exploit the users' channel state diversity (induced by fast-fading) and are optimal for stationary channel state distributions and an infinite time-horizon. However, mobile users experience a nonstationary channel, due to slow-fading (on the order of seconds), and are associated with base stations for short periods. Hence, we develop the Predictive Finite-horizon PF Scheduling ((PF)2S) Framework that exploits mobility. We present extensive channel measurement results from a 3G network and characterize mobility-induced channel state trends. We show that a user's channel state is highly reproducible and leverage that to develop a data rate prediction mechanism. We then present a few channel allocation estimation algorithms that exploit the prediction mechanism. Our trace-based simulations consider instances of the ((PF)2S) Framework composed of combinations of prediction and channel allocation estimation algorithms. They indicate that the framework can increase the throughput by 15%-55% compared to traditional PF schedulers, while improving fairness.

A Random Trajectory Approach for the Development of Non-Stationary Channel Models Capturing Different Scales of Fading

This paper introduces a new approach to developing stochastic nonstationary channel models, the randomness of which originates from a random trajectory of the mobile station (MS) rather than from the scattering area. The new approach is employed by utilizing a random trajectory model based on the primitives of Brownian fields (BFs), whereas the position of scatterers can be generated from an arbitrarily 2-D distribution function. The employed trajectory model generates random paths along which the MS travels from a given starting point to a fixed predefined destination point. To capture the path loss, the gain of each multipath component is modeled by a negative power law applied to the traveling distance of the corresponding plane wave, whereas the randomness of the path traveled results in large-scale fading. It is shown that the local received power is well approximated by a Gaussian process in logarithmic scale, even for a very limited number of scatterers. It is also shown that the envelope of the complex channel gain follows closely a Suzuki process, indicating that the proposed channel model superimposes small-scale fading and large-scale fading. The local power delay profile (PDP) and the local Doppler power spectral density (PSD) of the channel model are also derived and analyzed.

Capacity Analysis for Spatially Non-Wide Sense Stationary Uplink Massive MIMO Systems

Channel measurements show that significant spatially non-wide-sense-stationary characteristics rise in massive MIMO channels. Notable parameter variations are experienced along the base station array, such as the average received energy at each antenna, and the directions of arrival of signals impinging on different parts of the array. In this paper, a new channel model is proposed to describe this spatial non-stationarity in massive MIMO channels by incorporating the concepts of partially visible clusters and wholly visible clusters. Furthermore, a closed-form expression of an upper bound on the ergodic sum capacity is derived for the new model, and the influence of the spatial non-stationarity on the sum capacity is analyzed. Analysis shows that for non-identically-and-independent-distributed (i.i.d.) Rayleigh fading channels, the non-stationarity benefits the sum capacity by bringing a more even spread of channel eigenvalues. Specifically, more partially visible clusters, smaller cluster visibility regions and a larger antenna array can all help to yield a well-conditioned channel, and benefit the sum capacity. This shows the advantage of using a large antenna array in a non-i.i.d. channel: the sum capacity benefits not only from a higher array gain, but also from a more spatially non-stationary channel. Numerical results demonstrate our analysis and the tightness of the upper bound.

A Correlation Model for Nonstationary Time-Variant On-Body Channels

The temporal variation of spatial correlation between on-body radio links is empirically characterized for different walking scenarios. Nonstationary behaviors are highlighted, and a model is proposed for the long-term fading correlation.

A Novel Non-Stationary Channel Model Utilizing Brownian Random Paths

This paper proposes a non-stationary channel model in which real-time dynamics of the mobile station (MS) are taken into account. We utilize Brownian motion (BM) processes to model targeted and non-targeted dynamics of the MS. The proposed trajectory model consists of both drift and random components to capture both targeted and non-targeted motions of the MS. The Brownian trajectory model is then employed to provide a non-stationary channel model, in which the scattering effects of the propagation area are modelled by a non-centred one-ring geometric scattering model. The starting point of the motion is a fixed point in the propagation environment, whereas its terminating point is a random point along a predetermined drift. The drift component can be controlled by a so-called drift parameter. Tracking the MS on the proposed Brownian path allows us to derive the local angles-of-arrival (AOAs) and local angles-of-motion (AOMs), which are expressed by stochastic processes rather than random variables. We compute the first-order densities of the AOA and AOM processes in closed form. The local power spectral density (PSD) of the Doppler frequencies and the autocorrelation function (ACF) of the complex channel gain are also provided. Given a walking speed scenario, the analytical results are demonstrated and explained in depth. It turns out that the proposed Brownian path model results in a non-stationary non-isotropic channel model. The proposed geometry-based channel model is very useful for the performance analysis of mobile communication systems under non-stationary conditions.

Non-stationary channel characterization for high-speed railway under viaduct scenarios

Non-stationary properties based on Markov chains are provided to characterize the wireless propagation mechanism of high-speed railway (HSR) under viaduct scenarios. This Markov modeling method reveals the temporal statistical behaviors of the persistence process corresponding to resolvable multipath components. Using the channel measurement data on Beijing–Tianjin HSR at 2.35 GHz, the steady-state probability matrices and the transition probability matrices of Markov chains are specified. The non-stationary channel parameters are informative for the link-level simulation and can be used for prototype verification for non-stationary HSR channels. In addition, we propose and investigate the concepts of the medium-scale fading entropy and lifetime, which quantitatively describe the degrees of uncertainty and stability, respectively. Furthermore, our provided models are compared with the experimental results by means of the Kullback–Leibler (KL) distance. It shows that the simulated results match the measured data very well.

Challenges Toward Wireless Communications for High-Speed Railway

High-speed railway (HSR) brings convenience to peoples' lives and is generally considered as one of the most sustainable developments for ground transportation. One of the important parts of HSR construction is the signaling system, which is also called the “operation control system,” where wireless communications play a key role in the transmission of train control data. We discuss in detail the main differences in scientific research for wireless communications between the HSR operation scenarios and the conventional public land mobile scenarios. The latest research progress in wireless channel modeling in viaducts, cuttings, and tunnels scenarios are discussed. The characteristics of nonstationary channel and the line-of-sight (LOS) sparse and LOS multiple-input-multiple-output channels, which are the typical channels in HSR scenarios, are analyzed. Some novel concepts such as composite transportation and key challenging techniques such as train-to-train communication, vacuum maglev train techniques, the security for HSR, and the fifth-generation wireless communications related techniques for future HSR development for safer, more comfortable, and more secure HSR operation are also discussed.

Adaptive Space Modulation With Partial CSIT in Spatially Correlated Fading Channels

The problem of adaptive space modulation (ASM) design using partial channel state information at the transmitter (CSIT) is investigated. ASM relies on adaptive modulation of information symbols in the spatial domain using multiple antennas based on some sort of CSIT. The CSIT is exploited to adjust the transmission such that the distances between the receive constel- lation vectors are increased to reduce the probability of error. We assume that the spatial correlation matrices are available as the partial CSIT and introduce two different approaches to design ASM. In the first approach, we consider that all the transmit antennas are active at each transmit interval and, using an upper bound on the average probability of error, design the transmit vectors based on the spatial correlation matrices to improve the performance. In the second approach and to avoid interantenna synchronization, we assume that only one transmit antenna is active at each transmit interval, and we modify a space shift keying (SSK) transmission by transmitting different complex values from different transmit antennas. Finally, we derive a power allocation to improve further the performance in nonstationary channels. By simulation, we show the effectiveness of the proposed approaches in improving the performance in terms of the symbol error rate (SER). Index Terms—Adaptive space modulation (ASM), multiple- input-multiple-output (MIMO), partial channel state informa- tion at the transmitter (CSIT), space shift keying (SSK), spatial modulation (SM).

A Nonstationary Wideband MIMO Channel Model for High-Mobility Intelligent Transportation Systems

The recent development of high-speed trains (HSTs), as a high-mobility intelligent transportation system, and the growing demands of broad-band services for HST users, introduce new challenges to wireless communication systems for HSTs. The deployment of mobile relay stations on top of the train carriages is one of the promising solutions for HST wireless systems. For a proper design and evaluation of HST wireless communication systems, we need accurate channel models that can mimic the underlying channel characteristics for different HST scenarios. In this paper, a novel nonstationary geometry-based stochastic model (GBSM) is proposed for wideband multiple-input multiple-output HST channels in rural macrocell scenarios. The corresponding simulation model is then developed with angle parameters calculated by the modified method of equal areas. Both channel models can also be used to model nonstationary vehicle-to-infrastructure channels in vehicular communication networks. The system functions and statistical properties of the proposed channel models are investigated based on a theoretical framework that describes nonstationary channels. Numerical and simulation results demonstrate that the proposed channel models have the capability to characterize the nonstationarity of HST channels. The statistical properties of the simulation model, verified by the simulation results, can match those of the proposed theoretical GBSM. An excellent agreement is achieved between the stationary intervals of the proposed simulation model and those of relevant measurement data, demonstrating the utility of the proposed channel models.

Two-Dimensional Interpolation-Assisted Channel Prediction for OFDM Systems

Channel prediction can provide up-to-date information about the state of a channel in OFDM systems at the expense of increasing the complexity of wireless systems. Therefore, this paper proposes a novel approach for optimizing the shape and intervals between samples in two-dimensions (2-D) for an orthogonal frequency-division multiplexing (OFDM) system to reduce the complexity of predicting the channel frequency response (CFR). Furthermore, the proposed prediction scheme has the flexibility to integrate with an adaptive algorithm which does not require any statistical prior knowledge and is able to track nonstationary channel statistics. The number of multipliers that are required to predict the CFR is reduced by predicting the CFRs at particular subcarriers and incorporating interpolation methods. This paper also deals with the proposal of a 2-D curve fitting (CF) interpolator to be used for predicting the CFR that allow improving the accuracy of the CFR prediction. Simulation and analysis results demonstrate that the 2-D CF interpolator combined with the proposed scheme has lower complexity than the other approaches to predicting CFR, without compromising the mean square error (MSE) or bit error ratio, even in a noisy and fast-fading channel environment.

Airport Surface Propagation Channel in the C-Band: Measurements and Modeling

In this paper, we assess the path loss and the multipath fading characteristics of the airport surface channel based on the measurement data collected at Munich airport at 5.2 GHz. Our goal is to present channel models for the ground, tower and ramp area of the airport surface, which are easy to implement in a channel emulator and suitable for performance evaluation of the future aeronautical airport data link AeroMACS. The channel is in general nonstationary, but within one data frame and correspondingly one simulation run, the WSSUS assumption can be adopted for all scenarios related to an aircraft. However, the assumption loses its validity in the case of service vehicles moving in the NLOS ramp area. The proposed stochastic model for the small scale fading channel uses a sum-of-sinusoids based tapped delay line with a fixed channel parameters which are randomly chosen from the suitable intervals for each new simulation run. Incorporating scatterer movements into the model enables modeling of a nonstationary channel impulse response.

An Information Theoretic Take on Time Reversal for Nonstationary Channels

It has been shown that time-reversal (TR) techniques focus energy back to the dominant scatters, lead to super-resolution focusing, and gains in detection. Time reversal has so far mainly been studied when the channel remains invariant between the initial and time-reversed signal transmission times. In this letter, we relax this assumption and study the benefits of TR over time-varying channels. To do so, we compare a time-reversed and a non time-reversed system by comparing the mutual information between the channel impulse response and channel outputs given the transmitted signals. We present analytical results for a simple scalar problem which illustrates the impact of nonstationary channels on TR, and for general channels, numerically evaluate the difference in mutual informations, which demonstrate that, if the channels are nonstationary yet correlated, TR may still provide mutual information gains over non time-reversed systems.

Characterization of Non-Stationary Channels Using Mismatched Wiener Filtering

A common simplification in the statistical treatment of linear time-varying (LTV) wireless channels is the approximation of the channel as a stationary random process inside certain time-frequency regions. We develop a methodology for the determination of local quasi-stationarity (LQS) regions, i.e., local regions in which a channel can be treated as stationary. Contrary to previous results relying on, to some extent, heuristic measures and thresholds, we consider a finite-length Wiener filter as realistic channel estimator and relate the size of LQS regions in time to the degradation of the mean square error (MSE) of the estimate due to outdated and thus mismatched channel statistics. We show that for certain power spectral densities (PSDs) of the channel a simplified but approximate evaluation of the matched MSE based on the assumption of an infinite filtering length yields a lower bound on the actual matched MSE. Moreover, for such PSDs, the actual MSE degradation is upper-bounded and the size of the actual LQS regions is lower-bounded by the approximate evaluation. Using channel measurements, we compare the evolution of the LQS regions based on the actual and the approximate MSE; they show strong similarities.

Base station identification in single-frequency network positioning system under mixed line-of-sight/non-line-of-sight condition

A base station (BS) identification algorithm which does not modify the transmitter hardware and digital terrestrial television broadcasting signal framework is proposed for single-frequency networks positioning system. Similar to the outlier detection in multi-object tracking environments, the BS identification is formulated as a data validation problem which is solved with gate construction. Compared with traditional gate algorithm, an additional mode probability parameter is introduced to describe the wireless channel condition and overcome its drawback in non-stationary wireless channel environments by the interacting multiple model approach. In the proposed algorithm, two parallel innovation statistical distribution deduction modes with line-of-sight and non-line-of-sight condition are employed to estimate the corresponding parameters, respectively. Then a combination scheme is utilised to mix the two estimated statistical parameters by the predicted mode probabilities and obtains the final innovation distribution. At last, gate parameter is calculated like traditional gate algorithm and the BS identification is achieved. Simulation results demonstrate its robustness and high performance in different scenarios.

Quantum Capacity under Adversarial Quantum Noise: Arbitrarily Varying Quantum Channels

We investigate entanglement transmission over an unknown channel in the presence of a third party (called the adversary), which is enabled to choose the channel from a given set of memoryless but non-stationary channels without informing the legitimate sender and receiver about the particular choice that he made. This channel model is called arbitrarily varying quantum channel (AVQC). We derive a quantum version of Ahlswede's dichotomy for classical arbitrarily varying channels. This includes a regularized formula for the common randomness-assisted capacity for entanglement transmission of an AVQC. Quite surprisingly and in contrast to the classical analog of the problem involving the maximal and average error probability, we find that the capacity for entanglement transmission of an AVQC always equals its strong subspace transmission capacity. These results are accompanied by different notions of symmetrizability (zero-capacity conditions) as well as by conditions for an AVQC to have a capacity described by a single-letter formula. In he final part of the paper the capacity of the erasure-AVQC is computed and some light shed on the connection between AVQCs and zero-error capacities. Additionally, we show by entirely elementary and operational arguments motivated by the theory of AVQCs that the quantum, classical, and entanglement-assisted zero-error capacities of quantum channels are generically zero and are discontinuous at every positivity point.

Low-complexity resource allocation with rate balancing for the MISO-OFDMA broadcast channel

This paper presents a low-complexity algorithm for multiuser scheduling and resource allocation in the Multiple Input Single Output (MISO) downlink channel with Orthogonal Frequency Division Multiple Access (OFDMA). The goal of the algorithm is to maximize the sum-rate on the radio channel and to ensure that the rate assignment is suitably balanced among users. The proposed algorithm uses partial Channel State Information (CSI) and therefore has a reduced feedback requirement. It also allows an on-line implementation, based on an ergodic optimization framework with dual optimization and stochastic approximation. Performance and complexity reduction are quantified by considering comparison with other solutions in a realistic single-cell system configuration. It is shown that the algorithm is effective to balance average rate among users even in heterogeneous and non-stationary channel conditions with lower computational complexity and feedback requirements.

Joint evolutionary spectrum and autoregressive-based approach to modeling non-stationary flat fading channels

Modeling of wireless channels, especially non-stationary fading channels, is important for design and performance analysis of wireless communication systems. Recently, we proposed a new approach to modeling non-stationary fading channels, based on the theory of evolutionary spectrum ES. In this paper, we develop a time-varying autoregressive AR model for a non-stationary flat fading channel; specifically, we develop a method to determine the time-varying coefficients of the AR channel model, given the ES of a non-stationary process. Furthermore, with the ES theory, we develop a trace-driven time-varying AR channel simulator to generate a non-stationary flat fading process. Simulation results show that the ES of the channel gain process produced by our joint ES-and-AR-based channel model agrees well with the user-specified ES, indicating the accuracy of our joint ES-and-AR-based channel model. Copyright © 2012 John Wiley & Sons, Ltd.

Non-Regenerative Multi-Way Relaying: Space-Time Analog Network Coding and Repetition

In this letter, we investigate non-regenerative multi-way relaying when channel state information is not available at the multi-antenna relay station (RS). For stationary channels, space-time analog network coding (STANC) transmission is applied at the RS. For non-stationary channels, the RS applies repetition transmission. For both transmission schemes, in order to obtain the data streams of the other nodes, each node has to perform three receive processing operations successively: Zero Forcing (ZF) detection, back-propagated self-interference cancellation and joint detection. We assess the achievable sum rate performance of non-regenerative multi-way relaying for the proposed transmission schemes. It is shown that STANC with joint detection outperforms both benchmark transmissions, namely, ZF and Maximisation of Signal to Noise Ratio (MSNR) transceive beamforming with single stream decoding performed at each node. When the channels are non-stationary, the repetition transmission enables the multi-way communication and in medium to high SNR region, it outperforms MSNR.