Modeling Methods And Applications For Wideband Wireless Channels

The essential characteristics of radio signal transmission is multipath propagation where the received signals have different attenuation, Doppler frequency, arrival time and angle of arrival, which result in signal dispersion in time, frequency and space domain. Accordingly, wireless channels are power-limited, space-varying, time-varying, and frequency- varying, it may introduce considerable interference, distortion and noise which make a great impact on the infrastructure of the receivers, including the method of modulation and channel coding, equalizer, diversity and other relative signal processing techniques. In a word, channel modeling and simulation play an important role in the design of wireless communications. As a result, the key issues about channel modeling are treated firstly, which are the research outcomes of the auther during his Ph.d. studying, and then some applications on channel modeling are discussed based on the TD-SCDMA system.Channel models are the relation between the input and output of the channel by the forms of mathematics or arithmetic, which are multi-variable stochasitic process based on extensive measurements or the radio propagation theory. As a result, channel models are characterized by statistical descriptions. The effects of channels can be distinguished between large scale fading and small scale fading. The large scale fading results from the obstacles such as mountains, buildings or trees, it describes the path loss of antennuation in large areas used for estimating the range of signal covering and network optimization. On the other hand, small scall fading describes the fast fluctuations of received signals, which impact the structure of receivers, including equalizer, channel estimation, synchronization. So small scall fading is more important than large scale fading in the design of wireless systems. Consequently, the paper focuses on the modeling and simulation of small scale fading. The paper can be devided into five parts.The first part deals with the representation of wireless channels, comprising chapter 2. We consider some recent results and mthods of the large scale fading models, and extend the space domain to WSSUS models proposed by Bello for small scale fading.The second part considers the simulation of scalar channels, including frequency non-selective channels and frequency selective channels refered as WSSUS channels. The WSSUS channel is finished by the tap delay line model (TDL), and each tap may be modeled as a complex Gaussian process, namely, frequency non-selective channel. Firstly, we deal with the simulation of Rayleigh fading frequency non-selective channels based on SOS, FIR filter, and AR filter. The SoS Based simulation models for Rayleigh fading channels are divided into four categories by a uniform framework, depending on whether the parameter sets (amplitudes, phases, or Doppler frequencies) are fixed or random in simulation trials. Furthermore, the mechanisms of multipath radio propagation show that the fading phenomenon is a primary result of time variations in phases. Consequently, we summarize altogether three methods to define the initial phases for each category of the simulation models. For comparison purposes the second-order statistics of different kinds of simulation models are presented. Some conditions for an effective Rayleigh fading channel simulator are also concluded, and an improved simulator for generating multiple independent Rayleigh fading waveforms is achieved, which outperforms the other techniques in terms of its accuracy and convergence rate.The third part proposes a new wireless channel simulator, using an IIR filter to filter independent white Gaussian variables. Firstly, the IIR filter is implemented based on the desired power spectral density (PSD), employing the least mean square (LMS) algorithm in frequency domain. Then the arbitrary normalized maximal Doppler frequency, which is also known as the normalized digital bandwidth of the generated channel, is achieved by linear interpolation and decimation. Under the assumption of isotropic scattering Rayleigh fading channels, simulation shows the second order statistics of the proposed method is consistent with the traditional methods, such as the sum-of-sinusoids (SOS), the FFT, and the AR, with lower order of the IIR filter. Consequently, the new simulator is both efficient and fast. Furthermore, the new method is also suitable for non-isotropic scattering environments which are more practical than the isotropic scattering assumption, and the application is also treated under those cases.The fourth part provides a simplified and efficient MIMO radio channel simulator based on the most popular correlation-based MIMO radio channel model and the SOS approach which is traditionally used for generation Rayleigh fading waveforms with temporal correlation. First we give an overview of MIMO channel modeling. Then, we use the improved simulation model for the generation of multiple Rayleigh fading waveforms. Next, a simplified spatial correlation model of outdoor BS is introduced in closed-form expression, which has negligible difference compared to the reference correlation values. In the end, capacity of the simulated MIMO radio channel is evaluated with respect to different AOA. The presented simulator is suitable for the theoretical analyses of MIMO radio systems and dynamic MIMO channel simulation.The fifth part deals with the several applications of channel modeling which come from the author's research on TD-SCDMA during his P.h.d. studying. The first is the problem of Inter-BS Interference based on TD-SCDMA of TDD systems where the analysis method is presented in detail and the outcomes of simulation are given, which is of practical guiding in Wireless Network Planning. The second is about the improved channel estimation method based on the Steiner low cost channel estimatorwhich is used in TD-SCDMA (Time Division-Synchronous Code Division Multiple Access) cellular mobile radio systems. TD-SCDMA is also known as third-generation mobile systems where adaptive antennas are employed. As additive noise has a great adverse effect on the performance of the Steiner estimator, the proposed method employs time correlated post processing with a threshold filter to reduce channel noise and compensate channel variations. Furthermore, channel estimation combining direction-of-arrivals (DOAs) is performed, which can reduce channel interferences without adding computational complexity, for the information of DOAs has been obtained by the inherent adaptive antenna system. The performance of the improved channel estimator is compared with conventional channel estimation approaches, and numerical results show that the new approach can lead to considerable performance enhancement even in high speed vehicle propagation environments.In the end of the paper, the whole work of the dissertation is outlined and the further research issues are discussed.