In this paper a technique for the deconvolution of signals in the wavelet-domain is presented. It makes use of the Discrete Wavelet Transform (DWT) implemented with filter banks, and is based on expressing the convolution of two signals using the Forward Merge Approach for DWT-based convolution. The DWT-based deconvolution technique is then applied to the problem of pilot-based channel estimation, which can be used in the design of wavelet-based agile radio systems. \par DWT-based deconvolution is first described analytically and is then implemented in MATLAB to validate the theory and evaluate its performance. Monte Carlo simulations of DWT-based deconvolution of transmitted signals from received signals, both known a priori, are performed to estimate channel impulse responses. Transmitted signals are corrupted by Additive White Gaussian Noise (AWGN) resulting in E_b/N_0 ratios ranging from 0 dB to 30 dB. Fast-fading channels with Gaussian and "hilly area" Power Delay Profiles (PDPs) are used, along with four different wavelets for the DWTs. The results of the simulations show that DWT-based deconvolution is a viable technique and its performance in some cases is comparable to direct discrete time-domain deconvolution.

In this paper communications receivers that implement Zero-Forcing (ZF) equalization using the Discrete Wavelet Transform (DWT) are examined. In such receivers, noisy faded received signals are first decomposed using the DWT into detail and approximation coefficients. Instead of the received signals being directly equalized in the discrete time-domain the DWT coefficients of the signals are equalized using ZF equalization. In this work the performance of such receivers under various transmission channel conditions is evaluated. Both slow- and fast- fading multipath channels are considered. In addition, the effect of using different wavelets on receiver performance is also examined. Overall system performance is evaluated using Monte Carlo simulations employing 16-QAM modulation. For all cases considered, the transmitted signals have also been corrupted by additive White Gaussian Noise (WGN). It is found that performance of receivers using wavelet-domain ZF equalization is similar to the performance of receivers using discrete time-domain ZF equalization.

In this study, we first quantify cell-wide mean throughputs in interference-limited single-input-single-output (SISO) and multi-element antenna (MEA) cellular systems along various system-level design dimensions, including: MEA array size; frequency-reuse factor; antenna pattern (omni-directional or sectorized); degree of coding; allowable constellation size; and transmitor receive-adaptation. Next, we examine the validity of a noise-model for co-channel interference present in MEA links. Using system simulations, we show that this model is valid under all conditions, with varying levels of accuracy.

Cell-wide mean throughputs on cellular system downlinks using multiple-input/multiple-output (MIMO) techniques is a topic of interest to researchers, cellular operators and equipment manufacturers. In previous work, the authors have tested the validity of the noise model (in the MIMO context) for the co-channel interference (CCI), wherein multipath-averaged CCI powers are added to the thermal noise power that results in an overall interference-plus-noise floor. This approximation simplifies throughput computation with only a minor loss of accuracy, while allowing the cell-wide mean throughput per user to be derived analytically. The key to the analysis is (i) the invocation of the noise model for CCI, and (ii) the demonstration that the overall CCI power has a distribution that is log-normal for any user distance from the base station (BS). This enables us to extend a previous analysis for single-cell (noise-only) MIMO systems to the interference-limited case.We present the analytical method and demonstrate its accuracy.

OFDM spectrum sensing algorithms are presented in this paper. The proposed spectrum sensing algorithms are based on Time-Domain Symbol Cross-Correlation (TDSC-MRC and TDSC-NP methods) and can be applied to all existing wireless OFDM systems. The statistical behaviors of the TDSCbased spectrum sensors are explicitly analyzed. The sensing performances of the TDSC-based spectrum sensors in terms of misdetection probability are derived in detail. In addition, the spectrum sensing method employing the Cyclic Prefix of the OFDM modulated signals (CP method) is described for comparison purposes. The DVB-T Standard [5] is adopted as an application example to illustrate the proposed spectrum sensing algorithms. Simulation results show that the TDSC-MRC method outperforms the CP method for all values of CP ratio considered. The TDSC methods have the advantage that the detection performances are the same for different CP ratios, while the detection performance of the CP method degrades dramatically when the CP ratio becomes small. From simulation results, for a sensing time of 50 ms, the TDSC-MRC method can achieve misdetection probabilities of 0.1 and 0.01 with respect to a false alarm probability of 0.01 for SNR values of -20.5 dB and -19.5 dB, respectively.

We compute cell-wide mean throughputs for a wide range of multiple-input-multiple-output (MIMO) system design parameters, in both single- and multi-cell scenarios, using realistic models for channel dispersion, path correlations, and cochannel interference. We assume the use of single-carrier modulation, and quantify the degradation in downlink throughput as the channel dispersion increases. Our results highlight the potential harm even from mild dispersion in MIMO links. In studying path correlations, we assume linear arrays at each end of the link, and quantify the interplay among device size, number of antenna elements, path correlation, and carrier frequency. We show that, under practical size constraints, the use of additional antenna elements can be counterproductive.

Spectrum sensing is one of the core technologies of cognitive radio (CR) systems which provide a viable solution to the problem of sparsity of wireless spectrum. Nowadays, OFDM techniques are adopted by many existing or progressing wireless communication standards. Thus, a robust spectrum sensing algorithm for OFDM modulated signals is highly desired to implement CR when the primary signal uses OFDM modulation. Motivated by this demand, a time-domain symbol cross-correlation based spectrum sensing algorithm (TDSC method) is presented in this paper. The algorithm makes use of the property that the mean of the TDSC of two OFDM symbols is not zero if they have embedded the same frequency-domain pilot tones. The statistical behavior of the proposed spectrum sensor is explicitly analyzed and a theoretical lower bound on the misdetection probability is derived in this paper. An intuitive spectrum sensing method which utilizes the cyclic prefix nature of the OFDM modulated signals (CP method) is also described in this paper as a reference for comparison. Finally, we use the DVB-T Standard [8] as an application example to illustrate the proposed spectrum sensing algorithm. The simulated channel environments are the Ricean and Rayleigh channels defined in the DVB-T Standard and the additive white Gaussian noise (AWGN) channel. Four CP ratios defined in the DVB-T Standard are simulated for the probability of false alarm equaling 0.01 and the sensing time set equal to 50 ms. Simulation results show that the TDSC method can achieve a misdetection probability of 0.1 when the SNR equals -20.5 dB for all four CP ratios. The TDSC method outperforms the CP method in all cases. Furthermore, the proposed method has approximately the same detection performance for different CP ratios while the detection performance of the CP method degrades dramatically when the CP ratio becomes small. Results also reveal that the simulated performance is very close to the theoretical lower bound indicating that the lower bound can be used as a good prediction of performance.

Spectrum sensing for the China digital television terrestrial broadcasting system is considered in this paper. The spectrum sensing algorithms utilize PN sequences embedded in the frame headers to perform spectrum sensing. A theoretical lower bound on the misdetection probability for each spectrum sensor presented in this paper is derived. The performances of the proposed spectrum sensing algorithms are demonstrated by computer simulation for the multipath Rayleigh fading and steady state multipath Rayleigh fading channels. Simulation results show that the misdetection probability evaluated by computer simulations is close to the lower bound on the misdetection probability for a steady state multipath Rayleigh channel. When the probability of false alarm is 0.01 and a 50 ms of sensing time is used, a misdetection probability equal to 0.1 is achieved when the signal to noise power ratio is -16 dB, -18.8 dB, and -18 dB for modes 1, 2, and 3 in the multipath Rayleigh fading channel, respectively.

Analytical results are derived for the performance of maximal-ratio combining (MRC) over correlated Gaussian vector channels. Generality is maintained by assuming arbitrary- power users and no specific form for the covariance matrices of the received faded signals. The scenarios of Rayleigh fading and statistical independence among diversity branches are considered as special cases of the general analysis. The analysis is presented within the context of a system with receive diversity and cochannel interference. The results obtained are applicable to antipodal signaling over a multiuser single-input multiple-output (SIMO) channel.

Spectrum sensing in a very low SNR environment (less than -20 dB) is considered in this paper. We make use of the noise rejection property of the cyclostationary spectrum. The sensing algorithms are based on measurement of the cyclic spectrum of the received signals. The statistics of the cyclic spectrum of the stationary white Gaussian process are fully analyzed for three measurement methods of the cyclic spectrum. The application to IEEE 802.22 WRAN is presented and the probability of false alarm is analytically derived. The operating characteristic curves for the sensing algorithms are determined from computer simulations using ATSC A/74 DTV signal captures as a test database.

Spectral sensing for the presence of ATSC DTV signals in VHF/UHF TV bands under a very low SNR environment is one of the core technologies in IEEE 802.22 WRAN. There are multiple signatures embedded in the ATSC DTV signals and these signatures can be utilized to perform spectrum sensing. Signature-based spectrum sensing algorithms have an advantage in that when the signals other than noise are detected, we are almost sure that they are signals we want to detect. Thus, in this paper, several signature based spectrum sensing algorithms are presented. The false alarm rate for detectors employing different algorithms is analytically derived. The operating characteristic curves for different detectors are determined from computer simulations using ATSC A/74 DTV signal captures as a test database.

Multiband-OFDM (MB-OFDM) is one of the promising candidates for UWB-based alternative PHY layer for WPAN. However, the coverage radius of MB-OFDM UWB system is very short, and single-hop transmission may not be adequate for very high-data-rate WPAN. Therefore, multi-hop ad hoc WPAN is considered to extend the UWB radio coverage. Since IEEE 802.15.3 MAC layer is designed for peer-to-peer communication, the following question arises: can the quality-of-service parameters still be preserved in multi-hop scenarios? In our study, thorough investigations using simulation are conducted by avoiding as many assumptions as possible, and the performances are evaluated to answer this question. It can be observed that 802.15.3 TDMA MAC layer functions well in the context of multihop network with on-demand rate-based scheduling scheme and the proper routing protocol. Multihop WPAN based on OFDM UWB physical layer could be a viable approach to extend the network coverage for very high data rate multimedia traffic

The generation of correlated Rayleigh fading envelopes based on mobile radio channel characteristics for realistic simulation of diversity systems was documented in 1974 by Jakes. In this letter, a survey of recent algorithms which draw upon Jakes' work will be given, as well as an illustration of their shortcomings. Subsequently, a procedure is presented for the generation of multiple equal-power correlated Rayleigh fading envelopes, with desired cross-correlations and autocorrelation functions specified so as to model channel conditions under the general assumption of isotropic scattering. The algorithm presented will enable accurate simulation and investigation of the effect of correlated fading on diversity schemes

A combination of multi-carrier modulation (e.g., OFDM) and spread-spectrum (e.g., DS-CDMA) called MC-SS is considered as a potential candidate for the wireless 4G technology. Most present synchronization techniques for OFDM can also be used for the downlink MC-SS system. However, they are not suitable for the uplink MC-SS system because every user's signal arrives at the base station asynchronously. In this paper, we propose a patterned timing synchronization algorithm which can estimate the signal arrival times for every user. Simulation results show that the performance of the proposed timing synchronization algorithms are close to ideal in the presence of multipath fading channels with frequency offsets up to several carrier spacings.

In this paper, we propose a technique to approximate the traffic aggregation processes described by Markov modulated Poisson processes (MMPP) models. It is found that the decaying time constants of the aggregated traffic process are the product of the eigenvalues of the transition matrix of the individual traffic. If the time constants are well clustered around some representative time constants (RTC's), the corresponding states can be merged in the state space. In the worst case, if the time constants are uniformly distributed over the log-scale, we prove that there exist a minimum number of states that can approximate the traffic aggregation. We develop a clustering algorithm to search for the RTC's and extend the rate limit algorithm to the case that the limit of the arrival rate is unknown.

The embedded codestream structures, associated with a variety of progressive image compression methods, suffer from severe error sensitivity when transmitted over wireless channels. In addition to employing forward error correction (FEC) codes, joint source-channel coding (JSCC) is a typical approach to combat the significant quality degradation. In this paper, a joint source-channel decoding (JSCD) method is designed when transmitting the JPEG2000 codestream over uncorrelated flat fading channels using low-density parity-check (LDPC) codes. Error resilience modes implemented in the JPEG2000 codec makes it possible to provide new messages as feedback to the channel decoder. Thus, the log-domain sum-product decoding procedure for LDPC codes is updated during each iteration according to the feedback information from the JPEG2000 decoder. Two adaptive modification algorithms are proposed to update the log-likelihood ratio (LLR) of the bit nodes at the receiver with and without channel side information (CSI), respectively. Simulation results show that the joint source-channel decoding methods not only improve the quality of the reconstructed image greatly but also reduce the number of iterations significantly.

Incorporating a framework from multivariate statistical theory, analytical results for the performance of (he downlink and uplink of multicarrier code division multiple access (MC-CDMA) in presence of correlated Rayleigh fading are presented. Complete generality is maintained by assuming no specific form for the covariance matrix of the desired user and interference. Statistical independence amongst subcarriers is considered only as a special case. The analysis is exact in the sense that the conventional Gaussian assumption is not invoked on the multiple access interference.

The generation of correlated Rayleigh fading envelopes based on mobile radio channel characteristics for realistic simulation of diversity systems was formally introduced and documented in 1974 by Jakes [W.C. Jakes, 1974]. Recently, several algorithms which draw upon Jakes' work have been introduced. In this paper a brief survey of these algorithms is given, as well as an illustration of their shortcomings. A straightforward and systematic procedure will be given for the generation of N /spl ges/ 2 equal power correlated Rayleigh fading envelopes with desired covariance matrix chosen to model channel conditions under the general assumption of isotropic scattering. This procedure will enable the accurate investigation and simulation of the effect of correlation on diversity schemes.

A new design algorithm for integrated digital transmission systems operating over noisy channels has been developed. Taking all system design aspects into consideration, the algorithm provides a general methodology for designing a typical digital communication system as a whole. Based on information-theoretic principles and on practical system design restrictions, the algorithm first eliminates design options that are unacceptable. A set of system configurations, i.e., the key parameters for the source/channel coding and modulation subsystems, are then generated for acceptable overall system designs. A large variety of existing methods for source coding, error-correction coding and modulation can be used in conjunction with the proposed system design algorithm. Applications to speech and image transmission have been considered as concrete examples for communication systems designed in accordance with this algorithm. Simulations have demonstrated that the system design algorithm can efficiently reduce the number of design options to a limited set of acceptable options with corresponding key parameters specifically identified. The methodology described in this paper provides communication engineers with means to rapidly produce the best possible system design configurations.

Mathematical morphology is used for image analysis for the purpose of flaw detection in materials that are represented by very poor-contrast digital images. In particular, an algorithm for flaw detection in the case of TV tube matte surfaces has been developed. The object skeletons within binary-valued images are obtained, and directional connectivity information in the skeletons is used to discriminate noise patterns from flaws according to a specified criteria. After the discriminating process, the skeletons that remain correspond to flaws and can be used to recover the actual shape of the flaws. An alarm flag may arise if the sizes of the detected flaws are found to exceed industrial standards. In the case of a gray-scale image, the image is first converted in a binary version using an adaptive threshold algorithm; then the flaw detection algorithm for binary images is applied. Experimental results are obtained for both binary and gray-scale digital image data obtained from imperfect glass samples.>

Detection of calcification in mammograms is analyzed based on mathematical morphology. A method of adaptively thresholding gray-level mammogram images is discussed. The threshold set is controlled by the index numbers in the skeleton of shapes which represent calcifications in mammograms. The parameters of the adaptive threshold sets are obtained from interpreting umbra shadows from an image function. The objective is to extract the suspicious areas from a mammogram and provide location information on certain predefined shapes and sizes of calcifications to radiologists for further examination.>

A column array processor (CAP) architecture for real-time (video rate) morphological image processing is proposed. The basic idea for this structure is that of a serial-to-parallel data input format and circular data stream processing. As compared to other structures, the column array processor appears to be more economical and flexible compared to a cellular array processor and more functional than a pipelined systolic array. The authors describe the concept and the structure of the processor and compare its operations to that of other processors. The primary motivation behind such an array processor is to implement morphological image analysis and processing algorithms in real-time for applications to video signals. Use of the processor is not limited to morphological operations.>

A morphological hit-or-miss algorithm is presented which can distinguish a distorted shape from among others and locate it. Shape recognition is presented in noisy environments as a problem of recognizing imperfect shapes. The method employs only one hit-or-miss operation. The resultant shape location is presented by a small cluster of points within a known set. The role of window W in the hit-or-miss transformation is discussed, and it is shown that the boundary of the complement of the shape, delta A/sup c/, can be used as a structuring element on the complement of the image, I/sup c/, with the result of the hit-or-miss transformation being the same as that when a window is used in the transformation. Without a window restriction, the hit-or-miss transformation is more practical in shape recognition.>

Automated shape recognition in two dimensions is analyzed, and an efficient approach is provided to reduce the redundancy of the matching process. Shape recognition is achieved through locating the objects to be recognized within the field of view. Two theorems are presented. The first theorem is applied to the shape-recognition problem and indicates a clear advantage in reducing the redundancy involved in the matching process when morphological operations are used. Experiments show that a large amount of computing time is saved as a consequence of this theorem. This theorem also offers advantages when performing automated shape recognition on images acquired in a noisy environment. The second theorem suggests that edges of shapes can be used as a structuring element, and all possible outcomes due to noisy environments need to be exhausted.>

A combined source-channel coding approach is described for the encoding, transmission, and remote reconstruction of image data. The transmission medium considered is that of a fading dispersive communications channel. Both the Rician fading and Rayleigh fading channel models are considered. The image source encoder employs two-dimensional (2-D) differential pulse code modulation (DPCM). This is a relatively efficient encoding scheme in the absence of channel errors. In the presence of fading, however, the performance degrades rapidly. By providing error control protection to those encoded bits which contribute most significantly to image reconstruction, it is possible to minimize this degradation without sacrificing transmission bandwidth. Several modulation techniques are employed in evaluation of system performance including noncoherent multiple frequency shift-keyed (MFSK) modulation. Analytical results are provided for assumed 2-D autoregressive image models, while simulation results are described for real-world images.

New short constraint length convolutional code constructions are tabulated for ratesR=(n-k)/n, k=1,2, \cdots ,n-1withn=2, 3,\cdots ,8, and for constraint lengthsK=3,4, \cdots,8. These codes have been determined by iterative search based upon a criterion of optimizing the free distance profile. Specifically, these codes maximize the free distanced_{f}while minimizing the number of adversaries in the distance, or weight, spectrum. In several instances we demonstrate the superiority of these codes over previously published code constructions at the same rate and constraint length. These codes are expected to have a number of applications, including combined source-channel coding schemes as well as coding for burst or impulsive noise channels.

A new approach to the design of the feedback predictor in a two-dimensional (2-D) DPCM encoder is presented. This approach is based upon an assumed stochastic image model which exhibits the predominant and pronounced edge structure typical of real-world imagery and is in distinction from the conventional approach based upon 2-D autoregressive (AR) modeling assumptions. The performance of the resulting DPCM encoder is shown to offer significant performance advantages over existing DPCM design approaches at transmission rates of 2 bits/pixel or less. Furthermore, this new approach results in improved ability to cope with channel errors.

An approach is described for exploiting the tradeoffs between source and channel coding in the context of image transmission. The source encoder employs two-dimensional (2-D) block transform coding using the discrete cosine transform (DCT). This technique has proven to be an efficient and readily implementable source coding technique in the absence of channel errors. In the presence of channel errors, however, the performance degrades rapidly, requiring some form of error-control protection if high quality image reconstruction is to be achieved. This channel coding can be extremely wasteful of channel bandwidth if not applied judiciously. The approach described here provides a rationale for combined source-channel coding which provides improved quality image reconstruction without sacrificing transmission bandwidth. This approach is shown to result in a relatively robust design which is reasonably insensitive to channel errors and yet provides performance approaching theoretical performance limits. Analytical results are provided for assumed 2-D autoregressive image models, while simulation results are provided for real-world images.

A combined source-channel coding approach is described for the encoding, transmission and remote reconstruction of image data. The source encoder employs two-dimensional (2-D) differential pulse code modulation (DPCM). This is a relatively efficient encoding scheme in the absence of channel errors. In the presence of channel errors, however, the performance degrades rapidly. By providing error control protection to those encoded bits which contribute most significantly to image reconstruction, it is possible to minimize this degradation without sacrificing transmission bandwidth. The result is a relatively robust design which is reasonably insensitive to channel errors and yet provides performance approaching the rate-distortion bound. Analytical results are provided for assumed 2-D autoregressive image models while simulation results are described for real-world images.