Pseudo-maximum-likelihood data estimation algorithm and itsapplication over band-limited channels

A pseudo-maximum-likelihood data estimation (PML) algorithm for discrete channels with finite memory in additive white Gaussian noise environment is developed. Unlike the traditional methods that utilize the Viterbi algorithm (VA) for data sequence estimation, the PML algorithm offers an alternative solution to the problem. The simplified PML algorithm is introduced to reduce the computational complexity of the PML algorithm for channels with long impulse response. The adaptive version of the PML algorithm suitable for time-varying channels such as frequency-selective Rayleigh fading channels is also introduced. Computer simulation results demonstrate the performance of these algorithms and compare them to the VA-based techniques for different types of channels. The performance design criterion for the PML algorithm is derived in the Appendix     

Rate distortion over band-limited feedback channels (Corresp.)

Although linear feedback is by itself sufficient to achieve capacity of an additive Gaussian white noise (AGWN) channel, it can not, in general, achieve the theoretical minimum mean-squared error for analog Gaussian data. This correspondence gives the necessary and sufficient conditions under which this optimum performance can be achieved.     

On the performance of band-limited asynchronous DS-CDMA over nakagami-m channels

In this paper we investigated the BER performance of DS-CDMA using various chip-waveforms, which include three time-limited chip-waveforms and two band-limited chip-waveforms. Closed-form formulae were derived for evaluating the achievable bit-error rate performance with the aid of the standard Gaussian approximation, when communicating over a Nakagami-m channel. The time-limited waveforms impose a low implementational complexity, since they maybe over sampled and read from a look-up table. However, they are outperformed by the frequency-domain raised-cosine waveform as well as the optimum waveform specifically designed by Cho and Lehnert for achieving the lowest possible bit error rate     

High-speed binary data transmission over the additive band-limited Gaussian channel

The transmission of the linear sum ofmbiphase modulated signals in a time intervalTis considered for an additive Gaussian white noise channel of bandwidthW. Previous analyses consider the case wherem leq n equiv 2WT. In this paper, the probability of error is derived form > n, a situation which arises when the channel bandwidth is insufficient to support the data rate. Two distinct problems are considered. In the first, termed uncoded transmission, allmsignals are independently biphase modulated. It is shown, for this case, that if the channel signal-to-noise ratio increases linearly withn, the error probability can be made to go to zero approximately exponentially innfor any value ofm/n. In the second problem, termed ceded transmission, onlyk < mof the signals are independently modulated. (The remaining(m - k)signals carry redundant information.) By using a suboptimum receiver, it is shown that for a fixed channel signal-to-noise ratio the error probability goes to0exponentially innifk/nis less than some numberC^{ast}. For high signal-to-noise ratio,C^{ast}is greater than1, a situation which could not occur ifm leq n.     

Precoded OFDM with adaptive vector channel allocation for scalable video transmission over frequency-selective fading channels

Orthogonal frequency division multiplexing (OFDM) has been applied in broadband wireline and wireless systems for high data rate transmission where severe intersymbol interference (ISI) always occurs. The conventional OFDM system provides advantages through conversion of an ISI channel into ISI-free subchannels at multiple frequency bands. However, it may suffer from channel spectral s and heavy data rate overhead due to cyclic prefix insertion. Previously, a new OFDM framework, the precoded OFDM, has been proposed to mitigate the above two problems through precoding and conversion of an ISI channel into ISI-free vector channels. In this paper, we consider the application of the precoded OFDM system to efficient scalable video transmission. We propose to enhance the precoded OFDM system with adaptive vector channel allocation to provide stronger protection against errors to more important layers in the layered bit stream structure of scalable video. The more critical layers, or equivalently, the lower layers, are allocated vector channels of higher transmission quality. The channel quality is characterized by Frobenius norm metrics; based on channel estimation at the receiver. The channel allocation information is fed back periodically to the transmitter through a control channel. Simulation results have demonstrated the robustness of the proposed scheme to noise and fading inherent in wireless channels.     

System identification techniques for adaptive signal processing

Many problems in adaptive filtering can be approached from the point of view of system identification. The close interconnection between these two disciplines is explored in some detail. This approach makes it possible to apply recursive parameter estimation algorithms to adaptive signal processing. Several examples are discussed including: adaptive line enhancement, generalized adaptive noise cancelling, adaptive deconvolution and adaptive TDOA estimation. It is shown how the recursive maximum likelihood algorithm can be used for both FIR and IIR filtering, and some preliminary results are presented. Several alternative algorithms are briefly discussed.This work was supported by the Office of Naval Research, Contract No. N00014-79-C-0743.     

NRZ timing recovery technique for band-limited channels

Nonreturn-to-zero (NRZ) data, when transmitted over band-limited channels, suffer from the lack of zero crossings because the elongated tail of each pulse interferes with subsequent ones, causing intersymbol interference (ISI). An NRZ timing recovery technique working with a decision-feedback equalizer (DFE) recovers the clock from the equalized waveform and enables data transmission at a rate ten times higher than the channel bandwidth. The proposed timing recovery technique uses a data-triggered low-jitter phase detector to sustain phase locking even with 600 missing transitions, A data rate of 30 Mb/s in 3-MHz bandwidth is demonstrated with a peak-peak clock jitter of 2 ns using 2-μm CMOS     

Unbiased blind adaptive channel identification and equalization

The blind adaptive equalization and identification of communication channels is a problem of important current theoretical and practical concerns. Previously proposed solutions for this problem exploit the diversity induced by sensor arrays or time oversampling, leading to the so-called second-order algebraic/statistical techniques. The prediction error method is one of them, perhaps the most appealing in practice, due to its inherent robustness to ill-defined channel lengths as well as for its simple adaptive implementation. Unfortunately, the performance of prediction error methods is known to be severely limited in noisy environments, which calls for the development of noise (bias) removal techniques. We present a low-cost algorithm that solves this problem and allows the adaptive estimation of unbiased linear predictors in additive noise with arbitrary autocorrelation. This algorithm does not require the knowledge of the noise variance and relies on a new constrained prediction cost function. The technique can be applied in other noisy prediction problems. Global convergence is established analytically. The performance of the denoising technique is evaluated over GSM test channels     

Four novel quadrature overlapping modulations and their spectral efficiency analysis over band-limited non-linear channels

The power spectral density (PSD) analysis considering non-linearity is important in studying spectral efficiency of a digital modem for satellite systems. A general closed formula for numerical PSD calculation of quadrature overlapping modulations is derived in this paper. Four new quadrature overlapping modulation schemes are proposed because they have better spectral characteristics than those of conventional modulations, such as offset QPSK, MSK and staggered QORC, in both linear and nonlinear channels. The four new schemes are; overlapped minimum shift keying (OMSK), minimum shift keying triangular cosine (MSKTC), raised cosine triangular cosine (RCTC) and sinusoidal quadrature overlapped triangular cosine (SQOTC). The results show that for these new modulations, PSD side lobe regeneration caused by the channel non-linearity, is much less than that for the OQPSK, MSK and staggered QORC, a desirable feature enabling even tighter frequency band allocation in satellite communication systems. © 1997 John Wiley & Sons, Ltd.     

Efficient MMSE-based channel error mitigation techniques. Application to distributed speech recognition over wireless channels

This work addresses the mitigation of channel errors by means of efficient minimum mean-square-error (MMSE) estimation. Although powerful model-based implementations have been recently proposed, the computational burden involved can make them impractical. We propose two new approaches that maintain a good level of performance with a low computational complexity. These approaches keep the simple structure and complexity of a raw MMSE estimation, although they enhance it with additional source a priori knowledge. The proposed techniques are built on a distributed speech recognition system. Different degrees of tradeoff between recognition performance and computational complexity are obtained.     

Joint detection and channel estimation algorithms for QS-CDMAsignals over time-varying channels

We consider a quasi-synchronous code-division multiple access (QS-CDMA) cellular system, where the code delay uncertainty at the base station is limited to a small number of chips. For such QS-CDMA systems, the need for code acquisition is eliminated, however, the residual code tracking and channel estimation problems still have to be solved. An extended Kalman filter (EKF) is employed to track the user delays and channel coefficients. By separating data detection, based on the QR decomposition combined with the M-algorithm (QRD-M) from the delay/channel estimation process, the computational complexity can be significantly reduced as the number of users increases. Simulations show that the EKF channel estimator performance is improved when the QRD-M algorithm is used instead of the MMSE detector or decorrelator for data decisions     

Pilot-assisted channel estimation method for OFDMA systems over time-varying channels

Conventional time-varying (TV) channel estimation (CE) methods for OFDM systems need optimal evenly spaced pilots to track channel time variations in one symbol period and the inter-carrier interference (ICI) on pilots caused by Doppler spread are regarded as noise. For practical OFDMA systems, the required evenly spaced pilots are unsatisfied and the ICI on pilots increase estimation errors. In this letter, a TV CE method for practical OFDMA systems is proposed. The time variations of the frequency domain transmission function in one symbol period are approximated by a linear model in time-frequency blocks for each user. Time domain transformations are avoided and evenly spaced pilots are not required. Furthermore, the ICI on pilots are mitigated by correlative coding. Simulation results demonstrate the Symbol-Error-Rate (SER) and Mean-Square- Error (MSE) performances of the proposed OFDMA CE method over TV channels.     

An adaptive modulation scheme for simultaneous voice and datatransmission over fading channels

We propose a new adaptive modulation technique for simultaneous voice and data transmission over fading channels and study its performance. The proposed scheme takes advantage of the time-varying nature of fading to dynamically allocate the transmitted power between the inphase (I) and quadrature (Q) channels. It uses fixed-rate binary phase shift keying (BPSK) modulation on the Q channel for voice, and variable-rate M-ary amplitude modulation (M-AM) on the I channel for data. For favorable channel conditions, most of the power is allocated to high rate data transmission on the I channel. The remaining power is used to support the variable-power voice transmission on the Q channel. As the channel degrades, the modulation gradually reduces its data throughput and reallocates most of its available power to ensure a continuous and satisfactory voice transmission. The scheme is intended to provide a high average spectral efficiency for data communications while meeting the stringent delay requirements imposed by voice. We present closed-form expressions as well as numerical and simulation results for the outage probability, average allocated power, achievable spectral efficiency, and average bit error rate (BER) for both voice and data transmission over Nakagami-m fading channels. We also discuss the features and advantages of the proposed scheme. For example, in Rayleigh fading with an average signal-to-noise ratio (SNR) of 20 dB, our scheme is able to transmit about 2 bits/s/Hz of data at an average BER of 10 ^-5 while sending about 1 bit/s/Hz of voice at an average BER of 10^-2     

Sequence detection and adaptive channel estimation for ISI channels under class-a impulsive noise

In this paper, sequence detection and channel estimation for frequency-selective, intersymbol interference (ISI)-producing channels under Class-A impulsive noise are considered. We introduce a novel suboptimum sequence detection (SSD) scheme and show that although SSD employs a simplified metric, it achieves practically the same performance as maximum-likelihood sequence detection (MLSD). For both SSD and MLSD, a lower bound on the achievable performance is derived, which is similar to the classical matched-filter bound for frequency-selective (fading) channels under Gaussian noise. For channel estimation, we adopt a minimum entropy criterion and derive efficient least-mean-entropy and recursive least-entropy algorithms. For both adaptive algorithms, we analyze the steady-state channel-estimation error variance. Theoretical considerations and simulation results show that in Class-A impulsive noise, the proposed sequence detection and adaptive channel-estimation schemes yield significant performance gains over their respective conventional counterparts (designed for Gaussian noise). Although the novel algorithms require knowledge of the Class-A noise-model parameters, their computational complexity is comparable to that of the corresponding conventional algorithms.     

Blind adaptive multiuser detection for DS/CDMA over multipathfading channels

Using a hard null scheme, multipath fading and multiple access interference suppression can be realised for a multiple constrained minimum variance (MCMV) detector at the same time. A modified version of the MCMV detector is also presented, which utilises the eigenstructure of the correlation matrix to enhance the performance of the MCMV detector. Numerical results demonstrate the effectiveness of the proposed detectors     

Noncoherent adaptive channel identification algorithms fornoncoherent sequence estimation

In this letter, two novel noncoherent adaptive algorithms for channel identification are introduced. The proposed noncoherent least-mean-square (LMS) and noncoherent recursive least squares (RLS) algorithms can be combined easily with noncoherent sequence estimation (NSE) for M-ary differential phase-shift keying signals transmitted over intersymbol interference (ISI) channels. It is shown that the resulting adaptive noncoherent receivers are very robust against carrier phase variations. For zero frequency offset, the convergence speed and the steady-state error of the noncoherent adaptive algorithms are similar to those of conventional LMS and RLS algorithms. However, the conventional algorithms diverge even for relatively small frequency offsets, whereas the proposed noncoherent algorithms converge for relatively large frequency offsets. Simulations confirm the good performance of NSE combined with noncoherent adaptive channel estimation in time-variant (fading) ISI channels     

Robust adaptive transmission of images and video over multiple channels

Reliable transmission of images and video over wireless networks must address both potentially limited bandwidths and the possibilities of loss. When bandwidth sufficient to transmit the bit stream is unavailable on a single channel, the data can be partitioned over multiple channels with possibly unequal bandwidths and error characteristics at the expense of more complex channel coding (i.e., error correction). This paper addresses the problem of efficiently channel coding and partitioning pre-encoded image and video bit streams into substreams for transmission over multiple channels with unequal and time-varying characteristics. Within channels, error protection is unequally applied based on both data decoding priority and channel packet loss rates, while cross-channel coding addresses channel failures. In comparison with conventional product codes, the resulting product code does not restrict the total encoded data to a rectangular structure; rather, the data in each channel is adaptively coded according to the channel's varying conditions. The coding and partitioning are optimized to achieve two performance criteria: maximum bandwidth efficiency and minimum delay. Simulation results demonstrate that this approach is effective under a variety of channel conditions and for a broad range of source material.     

Reliable channel regions for good binary codes transmitted over parallel channels

We study the average error probability performance of binary linear code ensembles when each codeword is divided into J subcodewords with each being transmitted over one of J parallel channels. This model is widely accepted for a number of important practical channels and signaling schemes including block-fading channels, incremental redundancy retransmission schemes, and multicarrier communication techniques for frequency-selective channels. Our focus is on ensembles of good codes whose performance in a single channel model is characterized by a threshold behavior, e.g., turbo and low-density parity-check (LDPC) codes. For a given good code ensemble, we investigate reliable channel regions which ensure reliable communications over parallel channels under maximum-likelihood (ML) decoding. To construct reliable regions, we study a modifed 1961 Gallager bound for parallel channels. By allowing codeword bits to be randomly assigned to each component channel, the average parallel-channel Gallager bound is simplified to be a function of code weight enumerators and channel assignment rates. Special cases of this bound, average union-Bhattacharyya (UB), Shulman-Feder (SF), simplified-sphere (SS), and modified Shulman-Feder (MSF) parallel-channel bounds, allow for describing reliable channel regions using simple functions of channel and code spectrum parameters. Parameters describing the channel are the average parallel-channel Bhattacharyya noise parameter, the average channel mutual information, and parallel Gaussian channel signal-to-noise ratios (SNRs). Code parameters include the union-Bhattacharyya noise threshold and the weight spectrum distance to the random binary code ensemble. Reliable channel regions of repeat-accumulate (RA) codes for parallel binary erasure channels (BECs) and of turbo codes for parallel additive white Gaussian noise (AWGN) channels are numerically computed and compared with simulation results based on iterative decoding. In addition, an examp     

Joint channel estimation and data demodulation algorithms for fast time varying band-limited frequency selective Rayleigh fading channels : a comparison study

In this paper, a comparison study is proposed between two recent algorithms which both perform joint channel and data estimation. The first one is the well known psp : per survivor processing algorithm and the second is called adaptive bloc sequence estimation (bse). Compared to the existing literature, we add, for our comparison study, the case of trellis coded transmissions combined with interleaving and deinterleaving techniques which are now currently employed for digital communications.     

Dynamic channel allocation techniques using adaptive modulation andadaptive antennas

This article studies the impact of adaptive quadrature amplitude modulation (AQAM) on network performance when applied to a cellular network, using adaptive antennas in conjunction with both fixed channel allocation (FCA) and locally distributed dynamic channel allocation (DCA) schemes. The performance advantages of using adaptive modulation are investigated in terms of the overall network performance, mean transmitted power, and the average network throughput. Adaptive modulation allowed an extra 51% of users to be supported by an FCA 4-QAM network, while in conjunction with DCA, an additional 54% user capacity was attained