Mobile Speed Classification for Cellular Systems Over Frequency Selective Rician Fading Channels

In this paper, a new algorithm is proposed for estimating mobile speed of cellular systems over frequency selective Rician fading channels. Theoretical analysis is first derived and practical algorithm is proposed based on the analytical results. The algorithm employs a modified auto-covariance of received signal power to estimate the speed of mobiles. The algorithm is based on the received signals which contain unknown transmitted data, unknown frequency selective multipaths including line-of-sight(LOS) component, and random receiver noise. The algorithm works very well for frequency selective Rician fading channels with large ranges of Rice factor and angle of arrival of the LOS component. Simulation results indicate that the new algorithm is very reliable and effective to distinguish slow speed and fast speed mobiles. The algorithm is computationally efficient. It only requires simple arithmetic operations such as multiplications, additions and subtractions

Mobile Speed Estimation for Broadband Wireless Communications

In this paper, a new algorithm is proposed to estimate mobile speed for broadband wireless communications, which often encounter large number of fading channel taps causing severe intersymbol interference. Theoretical analysis is first derived and practical algorithm is proposed based on the analytical results. The algorithm employs a modified auto-covariance of received signal power to estimate the speed of mobiles. The algorithm is based on the received signals which contain unknown transmitted data, unknown frequency selective multipaths possibly including line-of-sight (LOS) component, and random receiver noise. The algorithm works well for frequency selective Rayleigh and Rician channels. The algorithm is very resistant to noise, it provides accurate speed estimation even if the signal-to-noise (SNR) is as low as 0dB. Simulation results indicate that the new algorithm is very reliable and effective to estimation mobile speed corresponding maximum Doppler up to 500Hz. The algorithm has high computational efficiency and low estimation latency, with results being available within one second after communication is established

Doppler spread estimation in mobile fading channels

The Doppler spread, or equivalently, the mobile speed, is a measure of the spectral dispersion of a mobile fading channel. Accurate estimation of the mobile speed is important in wireless mobile applications which require such as knowledge of the rate of channel variations. In this dissertation, first the performance of classical crossing- and covariance-based speed estimators is studied. Next, the problem of mobile speed estimation using diversity combining is investigated. Then, a nonparametric estimation technique is proposed that is robust to different channel variations. Finally, cyclostationarity-based speed estimators which can be applied either blindly or with the aid of pilot data, are developed. A unified framework for the performance analysis of well-known crossing and covariance based speed estimation techniques is presented. This allows a fair analytical comparison among all the methods. Interestingly, it is proved that all these methods are asymptotically equivalent, i.e., for large observation intervals. The extensive performance analysis, supported by Monte Carlo simulations, has revealed that depending on the channel condition and the observation interval, one needs to use a crossing or a covariance based technique to achieve the desired estimation accuracy over a large range of mobile speeds. Two common diversity schemes, selection combining (SC) and maximal ratio combining (MRC), are considered for Doppler spread estimation. Four new estimators are derived which rely on the inphase zero crossing rate, inphase rate of maxima, phase zero crossing rate, and the instantaneous frequency zero crossing rate of the output of SC. Two estimators, which work based on the level crossing rates of the envelopes at the output of SC and MRC, are also proposed. The performances of all these estimators are investigated in realistic noisy environments with different kinds of scatterings and different numbers of diversity branches. Then a novel speed estimation technique is proposed that is applicable to both mobile and base stations, based on the characteristics in the power spectrum of mobile fading channels. The analytic performance analysis, verified by Monte Carlo simulations, shows that this low-complexity estimator is not only robust to both Gaussian and non-Gaussian noises, but also insensitive to nonisotropic scattering observed at the mobile. The estimator performs very well in both two- and three-dimensional propagation environments. By taking advantage of resolvable paths in wideband fading channels, the robustness against both nonisotropic scattering and line of sight can be further increased, due to the differences among the Doppler spectra observed at different paths. This technique is also extended to base stations with antenna arrays. By exploiting the spatial information, the proposed space-time estimator exhibits excellent performance over a wide range of noise power, nonisotropic scattering, and the line-of-sight component. This is all verified by simulation. The utility of the new method is further demonstrated by applying it to the measured data. Finally, to design robust blind and data-aided mobile speed estimators, a proposal is made to exploit the inherent cyclostationarity of linearly modulated signals transmitted through fading channels. Two categories of cyclic-correlation- and cyclic-spectrum-based methods are developed. Extension to space-time speed estimation at the base station in macrocells is also provided. In comparison with the existing methods, the new estimators can be used without any need for pilot tones and are robust to additive stationary noise or interference of any color or distribution. Unlike the conventional multi-antenna based method, the proposed space-time speed estimator does not assume the receiver noise to be spatially white. A suboptimal training sequence is also devised for pilot-symbol assisted methods, to reduce the estimation error. The performance of the proposed estimators are illustrated via extensive Monte Carlo simulations

Signal processing topics in multicarrier modulation : frequency offset correction for OFDM and multiuser interference cancellation for MC-CDMA

Orthogonal frequency division multiplexing (OFDM) is discussed as a special form of multi-carrier modulation (MCM). One major problem of the OFDM system is the sensitivity to an unknown frequency offset at the receiver. To improve the performance of the OFDM system, correction of the frequency offset is required before decision making. An adaptive method of frequency offset correction is presented. The adaptation algorithm used here is based on the LMS and the estimation is proven unbiased. A multiuser communications system having similar signal structure to the OFDM system, termed as multi-carrier code division multiple access (MC-CDMA), is discussed. The MC-CDMA system is susceptible to multiuser interference. Although orthogonal multiuser codes are used, the frequency selective fading might destroy the orthogonality between different codes and result in multiuser interference. The conventional decorrelator can be used to cancel such interference completely but has the disadvantage of enhancing noise power. An adaptive decorrelation algorithm, known as the Bootstrap algorithm, is implemented to separate interference from the desired user\u27s signal. Such algorithm is shown to perform better than the conventional decorrelator particularly in the low interference region

The Multi-Input Multi-Output (MIMO) Channel Modeling, Simulation and Applications

This thesis mainly focus on the Multi-Input Multi-Output (MIMO) channel modeling, simulation and applications. There are several ways to design a MIMO channel. Most of the examples are given in Chapter 2, where we can design channels based on the environments and also based on other conditions. One of the new MIMO channel designs based on physical and virtual channel design is discussed in Unitary-Independent- Unitary (UIU) channel modeling. For completeness, the different types of capacity are discussed in details. The capacity is very important in wireless communication. By understanding the details behind different capacity, we can improve our transmission efficiently and effectively. The level crossing rate and average duration are discussed.One of the most important topics in MIMO wireless communication is estimation. Without having the right estimation in channel prediction, the performance will not be correct. The channel estimation error on the performance of the Alamouti code was discussed. The design of the transmitter, the channel and the receiver for this system model is shown. The two different types of decoding scheme were shown - the linear combining scheme and the Maximum likelihood (ML) decoder. Once the reader understands the estimation of the MIMO channel, the estimation based on different antenna correlation is discussed. Next, the model for Mobile-to-Mobile (M2M) MIMO communication link is proposed. The old M2M Sum-of-Sinusoids simulation model and the new two ring models are discussed. As the last step, the fading channel modeling using AR model is derived and the effect of ill-conditioning of the Yule-Walker equation is also shown. A number of applications is presented to show how the performance can be evaluated using the proposed model and techniques

Communication-aware motion planning in mobile networks

Over the past few years, considerable progress has been made in the area of networked robotic systems and mobile sensor networks. The vision of a mobile sensor network cooperatively learning and adapting in harsh unknown environments to achieve a common goal is closer than ever. In addition to sensing, communication plays a key role in the overall performance of a mobile network, as nodes need to cooperate to achieve their tasks and thus have to communicate vital information in environments that are typically challenging for communication. Therefore, in order to realize the full potentials of such networks, an integrative approach to sensing (information gathering), communication (information exchange), and motion planning is needed, such that each mobile sensor considers the impact of its motion decisions on both sensing and communication, and optimizes its trajectory accordingly. This is the main motivation for this dissertation. This dissertation focuses on communication-aware motion planning of mobile networks in the presence of realistic communication channels that experience path loss, shadowing and multipath fading. This is a challenging multi-disciplinary task. It requires an assessment of wireless link qualities at places that are not yet visited by the mobile sensors as well as a proper co-optimization of sensing, communication and navigation objectives, such that each mobile sensor chooses a trajectory that provides the best balance between its sensing and communication, while satisfying the constraints on its connectivity, motion and energy consumption. While some trajectories allow the mobile sensors to sense efficiently, they may not result in a good communication. On the other hand, trajectories that optimize communication may result in poor sensing. The main contribution of this dissertation is then to address these challenges by proposing a new paradigm for communication-aware motion planning in mobile networks. We consider three examples from networked robotics and mobile sensor network literature: target tracking, surveillance and dynamic coverage. For these examples, we show how probabilistic assessment of the channel can be used to integrate sensing, communication and navigation objectives when planning the motion in order to guarantee satisfactory performance of the network in realistic communication settings. Specifically, we characterize the performance of the proposed framework mathematically and unveil new and considerably more efficient system behaviors. Finally, since multipath fading cannot be assessed, proper strategies are needed to increase the robustness of the network to multipath fading and other modeling/channel assessment errors. We further devise such robustness strategies in the context of our communication-aware surveillance scenario. Overall, our results show the superior performance of the proposed motion planning approaches in realistic fading environments and provide an in-depth understanding of the underlying design trade-off space