Kasturi Vasudevan

Coherent detection of turbo coded OFDM signals transmitted through frequency selective Rayleigh fading channels

This work addresses the problem of coherently detecting turbo coded orthogonal frequency division multiplexed (OFDM) signals, transmitted through frequency selective Rayleigh fading channels. A single transmit and receive antenna is assumed. The channel output is distorted by a carrier frequency and phase offset, besides additive white Gaussian noise (AWGN). A new frame structure for OFDM, consisting of a known preamble, cyclic prefix and data is proposed. A filter that is matched to the preamble is used for start-of-frame (SoF) detection. A two-step ML detector for frequency-offset estimation is proposed, which has a much lower complexity compared to the single step ML detector. Turbo decoding and data interleaving is used to significantly enhance the bit-error-rate (BER) performance of the coherent receiver. Simulation results show that the BER performance of the practical coherent receiver is close to the ideal coherent receiver, for data length equal to the preamble length, and attains a BER of about 4× 10-5 at an SNR of just 8 dB. It is also shown that the probability of erasure is less than 10-6 for a preamble length of 512 QPSK symbols. The proposed algorithms are well suited for implementation on a DSP-platform.

Synchronization of bursty offset QPSK signals in the presence of frequency offset and noise

This paper deals with the problem of synchronization of bursty offset QPSK signals in the presence of frequency offset and additive white Gaussian noise. The main tasks of the receiver are to detect a burst (a frame of data) with a low acquisition time, to estimate and cancel the frequency and phase offset (carrier recovery), perform timing recovery, matched filtering and finally recover the data such that the bit-error-rate (BER) is close to the theoretical limit. The key contribution of this paper is to develop synchronization techniques in discrete-time that perform effectively even at signal-to-noise ratio (SNR) close to 0 dB in additive white Gaussian noise (AWGN) channels. These techniques are well suited for implementation on a digital signal processing (DSP) platform.

Design of superimposed training sequence for spatially correlated multiple-input–multiple-output channels under interference-limited environments

In this study, the design of a superimposed training (ST) for an interference-limited spatially correlated multiple-input–multiple-output (MIMO) system is addressed and a closed-form solution for designing the training signal is proposed in a sub-optimal way. Earlier papers have considered noise limited MIMO systems. The authors also propose random/orthogonal variable spread factor (OVSF) codes as a choice for the ST signal. The mean-squared error of the channel estimate and symbol error rate performances are obtained through simulation. Considering the power allocation issue between the data and training symbols, a sub-optimal average training power that maximises the lower bound on the effective signal-to-interference ratio is also proposed. Simulation results show that the bit error rate performance of the ST is indistinguishable from the OVSF/random ST sequence.

Detection of signals in correlated interference using a predictive VA

In this paper, we address the problem of optimally detecting signals in correlated noise using a predictive Viterbi algorithm (PVA). We derive expressions for the probability of error for both coded and uncoded systems employing the PVA, which are corrupted by coloured noise. As an application, the PVA is used in conjunction with a fractionally spaced linear equalizer (LE-PVA), thereby improving the bit-error-rate performance by as much as 11 dB, over the conventional decision feedback equalizer with estimated decisions, when the channel has spectral nulls. The LE-PVA is also about 1 dB better than the DFE that uses per-survivor processing. Simulation results also show that the performance difference between the LE-PVA and the decision feedback equalizer with correct decisions fed back (ideal DFE), is just 1 dB, even when the channel has spectral nulls. Simulation results are also presented for multipath fading channels, where we again demonstrate that the LE-PVA is just 1 dB inferior to the ideal DFE and about 1 dB better than the DFE using per-survivor processing. Thus, we clearly demonstrate the superiority of the LE-PVA over a practical DFE.

Turbo decoding in ISI channels

Turbo codes are family of forward error correcting codes, whose performance is near Shannon limit. Turbo decoding is based on the maximum a-posterior algorithm (MAP) algorithm. In this paper, the problem of turbo decoding in ISI channel is studied. A Super-trellis structure method has been presented and modified turbo decoding is suggested. Two methods have been suggested for turbo decoding in ISI channel. In the first method, we take all possible combinations of output of encoder-2 and in method-2, output of each encoder is passed through channel filter independently. Method-2 performs better than method-1 but requires higher bandwidth. The improvement in performance is demonstrated through simulations.

Noncoherent detection of multilevel signals in frequency nonselective fading channels

Abstract This paper addresses the recovery of multilevel signals in the presence of frequency nonselective fading and additive white Gaussian noise. We first propose a novel detector which performs approximate noncoherent maximum likelihood estimation for slowly fading channels, where the channel gain and phase remain constant over several symbol durations. This maximum likelihood detector for signals with unknown amplitude and phase (ML-UAP) is then modified and implemented recursively using the Viterbi algorithm (VA) to obtain a lower complexity suboptimal noncoherent VA for multilevel signals (SNVA-M). Next, a forgetting-factor is introduced to deal with variations in gain and phase due to fast fading. The resulting forgetting-factor-based SNVA-M (FSNVA-M) does not require explicit carrier recovery or automatic gain control (AGC) procedures. The SNVA-M and the FSNVA-M detectors perform as well as a coherent detector for AWGN channels and for fast Rician fading channels, but are not suitable for fast Rayleigh fading channels. For fast fading Rayleigh channels, we propose three schemes based on the detection of differentially encoded circular 8-QAM. Although these schemes are suboptimal when compared to various other optimal receivers proposed for flat fading Rayleigh channels, they do not require the knowledge of the fade statistics and are computationally more efficient. We refer to these techniques as the symbol-by-symbol differential detector for multilevel signals (SSDD-M), multiple symbol differential detector using VA for multilevel signals (MSDDVA-M) and the quotient space VA (QSVA) approach. The simulated error-rate performance of these three approaches for differentially encoded 8-QAM are found to perform better than the conventional detector for differentially encoded 8-PSK in fast fading Rayleigh channels. Moreover, the proposed detectors are highly suited for DSP-based receiver implementations.

An efficient pilot pattern design for channel estimation in OFDM systems

In this paper, channel estimation methods based on pilot patterns are investigated. LS and MMSE techniques are used for estimating channel at pilot subcarriers in block type and comb type methods. Channel estimation at data subcarriers is done using interpolation methods like linear interpolation, spline interpolation, low-pass interpolation, time domain interpolation. Window based channel estimation using Hann window is also studied. A new pilot pattern is proposed for channel estimation at pilot based on comb-type. The performances of all schemes are compared with QPSK as modulation technique with Rayleigh fading channel in presence of additive white Gaussian noise. Simulations show that proposed pattern shows better improvement in terms of BER comparisons and MSE plots.

Turbo equalization of serially concatenated turbo codes using a predictive DFE-based receiver

This paper investigates the performance of various “turbo” receivers for serially concatenated turbo codes transmitted through intersymbol interference (ISI) channels. Both the inner and outer codes are assumed to be recursive systematic convolutional (RSC) codes. The optimum turbo receiver consists of an (inner) channel maximum a posteriori (MAP) decoder and a MAP decoder for the outer code. The channel MAP decoder operates on a “supertrellis” which incorporates the channel trellis and the trellis for the inner error-correcting code. This is referred to as the MAP receiver employing a SuperTrellis (STMAP). Since the complexity of the supertrellis in the STMAP receiver increases exponentially with the channel length, we propose a simpler but suboptimal receiver that employs the predictive decision feedback equalizer (PDFE). The key idea in this paper is to have the feedforward part of the PDFE outside the iterative loop and incorporate only the feedback part inside the loop. We refer to this receiver as the PDFE-STMAP. The complexity of the supertrellis in the PDFE-STMAP receiver depends on the inner code and the length of the feedback part. Investigations with Proakis B, Proakis C (both channels have spectral nulls with all zeros on the unit circle and hence cannot be converted to a minimum phase channel) and a minimum phase channel reveal that at most two feedback taps are sufficient to get the best performance. A reduced-state STMAP (RS-STMAP) receiver is also derived which employs a smaller supertrellis at the cost of performance.

Detection of turbo coded signals transmitted through ISI channels using the predictive iterative decoder

This paper addresses the problem of detecting turbo-coded signals transmitted through channels that introduce inter-symbol interference (ISI). The receiver is simple to implement and it consists of a linear minimum mean squared error (MMSE) equalizer followed by a predictive iterative decoder (PID). Simulation results show that depending on the noise correlation, significant performance improvement can be obtained by using the PID, over that of the conventional iterative decoder (CTD).

DSP-based noncoherent detectors for multilevel signals in flat fading channels

This paper addresses the issue of recovering multilevel signals in the presence of slow, frequency nonselective fading and additive white Gaussian noise (AWGN). First, we present a novel noncoherent detector which performs approximate maximum likelihood detection in unknown amplitude and phase (ML-UAP). This ML-UAP detector is implemented using the Viterbi algorithm (VA), which we call the suboptimal noncoherent VA for multilevel signals (SNVA-M). Next, we propose a forgetting-factor based SNVA-M (FSNVA-M) which is quite insensitive to gain and phase changes of the signal, and thereby, avoids the need for explicit carrier recovery and AGC procedures. For differentially encoded multilevel signals, we propose three other schemes namely: symbol-by-symbol differential detector for multilevel signals (SSDD-M), VA-based multiple symbol differential detection for multilevel signals (MSDDVA-M) and the VA-based quotient space approach (QSVA). Finally, we present-results from computer simulations, which indicate that the FSNVA-M detector is best suited for AWGN and Rician fading channels, whereas the SSDD-M, MSDDVA-M and the and SVA detectors are best suited for Rayleigh fading channels. An important feature of all the proposed detectors is that they do not assume any knowledge of the fade statistics. Moreover, they easily lend themselves to DSP-based implementations.