Space time transceiver design over multipath fading channels

Imperial Users onl

Performance of Fractionally Spread Multicarrier CDMA in AWGN as Well as Slow and Fast Nakagami-m Fading Channels

Abstract—In multicarrier code-division multiple-access (MCCDMA), the total system bandwidth is divided into a number of subbands, where each subband may use direct-sequence (DS) spreading and each subband signal is transmitted using a subcarrier frequency. In this paper, we divide the symbol duration into a number of fractional subsymbol durations also referred to here as fractions, in a manner analogous to subbands in MC-CDMA systems. In the proposed MC-CDMA scheme, the data streams are spread at both the symbol-fraction level and at the chip level by the transmitter, and hence the proposed scheme is referred to as the fractionally spread MC-CDMA arrangement, or FS MCCDMA. Furthermore, the FS MC-CDMA signal is additionally spread in the frequency (F)-domain using a spreading code with the aid of a number of subcarriers. In comparison to conventional MC-CDMA schemes, which are suitable for communications over frequency-selective fading channels, our study demonstrates that the proposed FS MC-CDMA is capable of efficiently exploiting both the frequency-selective and the time-selective characteristics of wireless channels. Index Terms—Broadband communications, code-division multiple access (CDMA), fractionally spreading, frequency-domain spreading, multicarrier modulation, Nakagami fading, timedomain spreading

MMSE multiuser detection for array multicarrier DS-CDMA in fading channels

Published versio

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

Interference suppression and diversity for CDMA systems

In code-division multiple-access (CDMA) systems, due to non-orthogonality of the spreading codes and multipath channels, the desired signal suffers interference from other users. Signal fading due to multipath propagation is another source of impairment in wireless CDMA systems, often severely impacting performance. In this dissertation, reduced-rank minimum mean square error (MMSE) receiver and reduced-rank minimum variance receiver are investigated to suppress interference; transmit diversity is applied to multicarrier CDMA (MC-CDMA) systems to combat fading; packet combing is studied to provide both interference suppression and diversity for CDMA random access systems. The reduced-rank MMSE receiver that uses a reduced-rank estimated covariance matrix is studied to improve the performance of MMSE receiver in CDMA systems. It is shown that the reduced-rank MMSE receiver has much better performance than the full-rank MMSE receiver when the covariance matrix is estimated by using a finite number of data samples and the desired signal is in a low dimensional subspace. It is also demonstrated that the reduced-rank minimum variance receiver outperforms the full-rank minimum variance receiver. The probability density function of the output SNR of the full-rank and reduced-rank linear MMSE estimators is derived for a general linear signal model under the assumption that the signals and noise are Gaussian distributed. Space-time coding that is originally proposed for narrow band systems is applied to an MC-CDMA system in order to get transmit diversity for such a wideband system. Some techniques to jointly decode the space-time code and suppress interference are developed. The channel estimation using either pilot channels or pilot symbols is studied for MC-CDMA systems with space-time coding. Performance of CDMA random access systems with packet combining in fading channels is analyzed. By combining the current retransmitted packet with all its previous transmitted copies, the receiver obtains a diversity gain plus an increased interference and noise suppression gain. Therefore, the bit error rate dramatically decreases with the number of transmissions increasing, which in turn improves the system throughput and reduces the average delay

Transmitter precoding for multi-antenna multi-user communications

Emerging wireless sensor networks and existing wireless cellular and ad hoc networks motivate the design of low-power receivers. Multi-user interference drastically reduces the energy efficiency of wireless multi-user communications by introducing errors in the bits being detected at the receiver. Interference rejection algorithms and multiple antenna techniques can significantly reduce the bit-error-rate at the receiver. Unfortunately, while interference rejection algorithms burden the receiver with heavy signal processing functionalities, thereby increasing the power consumption at the receiver, the small size of receivers, specifically in sensor networks and in downlink cellular communications, prohibits the use of multiple receive antennas. In a broadcast channel, where a central transmitter is transmitting independent streams to decentralized receivers, it is possible for the transmitter to have a priori knowledge of the interference. Multiple antennas can be used at the transmitter to enhance energy efficiency. In some systems, the transmitter has access to virtually an infinite source of power. A typical example would be the base station transmitter for the downlink of a cellular system. The power consumption at receivers can be reduced if some of the signal processing functionality of the receiver is moved to the transmitter.;In this thesis, we consider a wireless broadcast channel with a transmitter equipped with multiple antennas and having a priori knowledge of interference. Our objective is to minimize the receiver complexity by adding extra signal processing functions to the transmitter. We need to determine the optimal signal that should be transmitted so that interference is completely eliminated, and the benefits that can be obtained by using multiple transmit antennas can be maximized. We investigate the use of linear precoders, linear transformations made on the signal before transmission, for this purpose

Multi-carrier CDMA using convolutional coding and interference cancellation

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN016251 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

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