Performance of direct-oversampling correlator-type receivers in chaos-based DS-CDMA systems over frequency non-selective fading channels

In this paper, we present a study on the performance of direct-oversampling correlator-type receivers in chaos-based direct-sequence code division multiple access systems over frequency non-selective fading channels. At the input, the received signal is sampled at a sampling rate higher than the chip rate. This oversampling step is used to precisely determine the delayed-signal components from multipath fading channels, which can be combined together by a correlator for the sake of increasing the SNR at its output. The main advantage of using direct-oversampling correlator-type receivers is not only their low energy consumption due to their simple structure, but also their ability to exploit the non-selective fading characteristic of multipath channels to improve the overall system performance in scenarios with limited data speeds and low energy requirements, such as low-rate wireless personal area networks. Mathematical models in discrete-time domain for the conventional transmitting side with multiple access operation, the generalized non-selective Rayleigh fading channel, and the proposed receiver are provided and described. A rough theoretical bit-error-rate (BER) expression is first derived by means of Gaussian approximation. We then define the main component in the expression and build its probability mass function through numerical computation. The final BER estimation is carried out by integrating the rough expression over possible discrete values of the PFM. In order to validate our findings, PC simulation is performed and simulated performance is compared with the corresponding estimated one. Obtained results show that the system performance get better with the increment of the number of paths in the channel.Peer ReviewedPostprint (author's final draft

Code-timing synchronization in DS-CDMA systems using space-time diversity

The synchronization of a desired user transmitting a known training sequence in a direct-sequence (DS) asynchronous code-division multiple-access (CDMA) sys-tem is addressed. It is assumed that the receiver consists of an arbitrary antenna array and works in a near-far, frequency-nonselective, slowly fading channel. The estimator that we propose is derived by applying the maximum likelihood (ML) principle to a signal model in which the contribution of all the interfering compo-nents (e.g., multiple-access interference, external interference and noise) is modeled as a Gaussian term with an unknown and arbitrary space-time correlation matrix. The main contribution of this paper is the fact that the estimator makes eÆcient use of the structure of the signals in both the space and time domains. Its perfor-mance is compared with the Cramer-Rao Bound, and with the performance of other methods proposed recently that also employ an antenna array but only exploit the structure of the signals in one of the two domains, while using the other simply as a means of path diversity. It is shown that the use of the temporal and spatial structures is necessary to achieve synchronization in heavily loaded systems or in the presence of directional external interference.Peer ReviewedPostprint (published version

Low order channel estimation for CDMA systems

New approaches and algorithms are developed for the identification and estimation of low order models that represent multipath channel effects in Code Division Multiple Access (CDMA) communication systems. Based on these parsimonious channel models, low complexity receivers such as RAKE receivers are considered to exploit these propagation effects and enhance the system performance. We consider the scenario where multipath is frequency selective slowly fading and where the channel components including delays and attenuation coefficients are assumed to be constant over one or few signalling intervals. We model the channel as a long FIR-like filter (or a tapped delay line filter) with the number of taps related to the ratio between the channel delay-spread and the chip duration. Due to the high data rate of new CDMA systems, the channel length in terms of the chip duration will be very large. With classical channel estimation techniques this will result in poor estimates of many of the channel parameters where most of them are zero leading to a reduction in the system performance. Unlike classical techniques which estimate directly the channel response given the number of taps or given an estimate of the channel length, the proposed techniques in this work will firstly identify the significant multipath parameters using model selection techniques, then estimate these identified parameters. Statistical tests are proposed to determine whether or not each individual parameter is significant. A low complexity RAKE receiver is then considered based on estimates of these identified parameters only. The level of significance with which we will make this assertion will be controlled based on statistical tests such as multiple hypothesis tests. Frequency and time domain based approaches and model selection techniques are proposed to achieve the above proposed objectives.The frequency domain approach for parsimonious channel estimation results in an efficient implementation of RAKE receivers in DS-CDMA systems. In this approach, we consider a training based strategy and estimate the channel delays and attenuation using the averaged periodogram and modified time delay estimation techniques. We then use model selection techniques such as the sphericity test and multiple hypotheses tests based on F-Statistics to identify the model order and select the significant channel paths. Simulations show that for a pre-defined level of significance, the proposed technique correctly identifies the significant channel parameters and the parsimonious RAKE receiver shows improved statistical as well as computational performance over classical methods. The time domain approach is based on the Bootstrap which is appropriate for the case when the distribution of the test statistics required by the multiple hypothesis tests is unknown. In this approach we also use short training data and model the channel response as an FIR filter with unknown length. Model parameters are then estimated using low complexity algorithms in the time domain. Based on these estimates, bootstrap based multiple hypotheses tests are applied to identify the non-zero coefficients of the FIR filter. Simulation results demonstrate the power of this technique for RAKE receivers in unknown noise environments. Finally we propose adaptive blind channel estimation algorithms for CDMA systems. Using only the spreading code of the user of interest and the received data sequence, four different adaptive blind estimation algorithms are proposed to estimate the impulse response of frequency selective and frequency non-selective fading channels. Also the idea is based on minimum variance receiver techniques. Tracking of a frequency selective varying fading channel is also considered.A blind based hierarchical MDL model selection method is also proposed to select non-zero parameters of the channel response. Simulation results show that the proposed algorithms perform better than previously proposed algorithms. They have lower complexity and have a faster convergence rate. The proposed algorithms can also be applied to the design of adaptive blind channel estimation based RAKE receivers

A General Framework for Analyzing, Characterizing, and Implementing Spectrally Modulated, Spectrally Encoded Signals

Fourth generation (4G) communications will support many capabilities while providing universal, high speed access. One potential enabler for these capabilities is software defined radio (SDR). When controlled by cognitive radio (CR) principles, the required waveform diversity is achieved via a synergistic union called CR-based SDR. Research is rapidly progressing in SDR hardware and software venues, but current CR-based SDR research lacks the theoretical foundation and analytic framework to permit efficient implementation. This limitation is addressed here by introducing a general framework for analyzing, characterizing, and implementing spectrally modulated, spectrally encoded (SMSE) signals within CR-based SDR architectures. Given orthogonal frequency division multiplexing (OFDM) is a 4G candidate signal, OFDM-based signals are collectively classified as SMSE since modulation and encoding are spectrally applied. The proposed framework provides analytic commonality and unification of SMSE signals. Applicability is first shown for candidate 4G signals, and resultant analytic expressions agree with published results. Implementability is then demonstrated in multiple coexistence scenarios via modeling and simulation to reinforce practical utility

Performance of Asynchronous MC-CDMA Systems with Maximal Ratio Combining in Frequency-Selective Fading Channels

The bit error rate (BER) performance of the asynchronous uplink channel of multicarrier code division multiple access (MC-CDMA) systems with maximal ratio combining (MRC) is analyzed. The study takes into account the effects of channel path correlations in generalized frequency-selective fading channels. Closed-form BER expressions are developed for correlated Nakagami fading channels with arbitrary fading parameters. For channels with correlated Rician fading paths, the BER formula developed is in one-dimensional integration form with finite integration limits, which is also easy to evaluate. The accuracy of the derived BER formulas are verified by computer simulations. The derived BER formulas are also useful in terms of computing other system performance measures such as error floor and user capacity

Signal Processing in Arrayed MIMO Systems

Multiple-Input Multiple-Output (MIMO) systems, using antenna arrays at both receiver and transmitter, have shown great potential to provide high bandwidth utilization efficiency. Unlike other reported research on MIMO systems which often assumes independent antennas, in this thesis an arrayed MIMO system framework is proposed, which provides a richer description of the channel charac- teristics and additional degrees of freedom in designing communication systems. Firstly, the spatial correlated MIMO system is studied as an array-to-array system with each array (Tx or Rx) having predefined constrained aperture. The MIMO system is completely characterized by its transmit and receive array man- ifolds and a new spatial correlation model other than Kronecker-based model is proposed. As this model is based on array manifolds, it enables the study of the effect of array geometry on the capacity of correlated MIMO channels. Secondly, to generalize the proposed arrayed MIMO model to a frequency selective fading scenario, the framework of uplink MIMO DS-CDMA (Direct- Sequence Code Division Multiple Access) systems is developed. DOD estimation is developed based on transmit beamrotation. A subspace-based joint DOA/TOA estimation scheme as well as various spatial temporal reception algorithms is also proposed. Finally, the downlink MIMO-CDMA systems in multiple-access multipath fading channels are investigated. Linear precoder and decoder optimization problems are studied under different criterions. Optimization approaches with different power allocation schemes are investigated. Sub-optimization approaches with close-form solution and thus less computation complexity are also proposed

OPTIMIZING RADIO RESOURCE MANAGEMENT IN VERY BAD CHANNEL CONDITIONS

Radio resource management is one of the most important parts of modern multi-user wireless communication systems. The main reason for this importance comes from the fact that the radio resources, such as bandwidth and power, are scarce. For instance, UMTS systems use 5MHz bandwidth for voice as well as data services. The optimum usage of the radio resource guarantees the highest efficient utilization of wireless networks. To optimize the radio resources, the transmitters need to estimate the channel conditions. This channel estimation is done by using pilot signal from the receiver. There are usually small delays between the measurements and the radio resource allocation. When the channel is highly correlated, this delay will not affect the performance, because the channel will not be significantly changed between the time of measurement and the time of transmission. However, if the mobile speed is high or the channel is very high dynamic, the correlation becomes very low. This is due to the timevarying nature of the channel. We call channels with very low correlation in time as bad condition channels. In this thesis we discuss this extremely important topic. The tools for analyzing bad condition channels are also proposed and discussed. Two power control algorithms to mitigate the low correlation of channels have been proposed. Our algorithms are validated through several simulations.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format