We propose a novel joint time-frequency modulation and coding scheme for wireless communication in the presence ofLinear Frequency Modulated(LFM) chirp radar interference. The time-frequency modulation framework, which is a simple form ofOrthogonal Frequency Division Multiplexing(OFDM), takes advantage of the localized, sparse, time-frequency structure of LFM chirp waveforms. The LFM chirp interference is shown to be given by the cross-ambiguity function of the interfering LFM chirp radar signal and the individual time-frequency chips in the OFDM time-frequency signaling frame. This results in a relatively small number of interference-induced errors that can be corrected using a Reed-Solomon or other types of error-correcting code. We present analytical and simulation results that show the efficacy of the approach and show the trade-off between the probability of error and code rate for the proposed scheme. The resulting performance shows that LFM chirp interference can be effectively mitigated with a relatively small reduction in communication rate.

We introduce a new chamfering paradigm, locally connecting pixels to produce path distances that approximate Euclidean space by building a small network (a replacement product) inside each pixel. These " RE -grid graphs" maintain near-Euclidean polygonal distance contours even in noisy data sets, making them useful tools for approximation when exact numerical solutions are unobtainable or impractical. The RE -grid graph creates a modular global architecture with lower pixel-to-pixel valency and simplified topology at the cost of increased computational complexity due to its internal structure. We present an introduction to chamfering replacement products with a number of case study examples to demonstrate the potential of these graphs for path-finding in high frequency and low resolution image spaces which motivate further study. Possible future applications include morphology, watershed segmentation, halftoning, neural network design, anisotropic image processing, image skeletonization, dendritic shaping, and cellular automata.

One of the 5G promises is to provide Ultra Reliable Low Latency Communications (URLLC) which targets an end to end communication latency that is <; 1ms. The very low latency requirement of URLLC entails a lot of work in all networking layers. In this paper, we focus on the physical layer, and in particular, we propose a novel formulation of the massive MIMO uplink detection problem. We introduce an objective function that is a sum of strictly convex and separable functions based on decomposing the received vector into multiple vectors. Each vector represents the contribution of one of the transmitted symbols in the received vector. Proximal Jacobian Alternating Direction Method of Multipliers (PJADMM) is used to solve the new formulated problem in an iterative manner where at every iteration all variables are updated in parallel and in a closed form expression. The proposed algorithm provides a lower complexity and much faster processing time compared to the conventional MMSE detection technique and other iterative-based techniques, especially when the number of single antenna users is close to the number of base station (BS) antennas. This improvement is obtained without any matrix inversion. Simulation results demonstrate the efficacy of the proposed algorithm in reducing detection processing time in the multi-user uplink massive MIMO setting.

In this paper, we study the problem of Quality of Experience (QoE) aware resource allocation in wireless systems. In particular, we consider application-aware joint Bandwidth-Power allocation for a small cell. We optimize a QoE metric for multi-user video streaming in a small cell that maintains a trade-off between maximizing the playback rate of each user and ensuring proportional fairness (PF) among users. We formulate the application-driven joint bandwidth-power allocation as a non-convex optimization problem. However, we develop a polynomial complexity algorithm, and we show that the proposed algorithm achieves the optimal solution of the proposed optimization problem. Simulation results show that the proposed QoE-aware algorithm significantly improves the average QoE. Moreover, it outperforms the weighted sum rate allocation which is the state-of-the-art physical resource allocation scheme.

This paper studies a nanosensor coordination scheme to effectively deliver nanosensors to deep targets. Deep targets are far away from the main patrolling paths of nanosensors (e.g. blood vessels) and hence the delivery ratio relying on natural diffusion can be very low. Inspired by the communication and motility capability of bacteria, we devise a decentralized coordination strategy so that once the deep target is identified by a small number of nanosensors, they can effectively recruit far-away nanosensors towards the target. Note that since the target is deep, patrolling nanosensors are typically outside the direct communication range of those nanosensors at the location of the target. Therefore, multi-hop communication is required to recruit replenishing agents from the main paths. We demonstrate that the proposed strategy can successfully pull the patrolling nanosensors to the deep target when the model parameters are properly selected. This suggests a potential solution to the open problem in cancer treatments that therapeutic agents are kept away from the central necrotic core of tumors.

In this paper, we consider the energy-bandwidth allocation for a network of multiple users, where the transmitters each powered by both an energy harvester and conventional grid, access the network orthogonally on the assigned frequency band. The tradeoff among the weighted sum throughput, the use of grid energy, and the amount of energy cooperation is studied through an optimization objective which is a linear combination of these quantities. To solve the problem efficiently, an iterative algorithm is proposed using the Proximal Jacobian ADMM. We show that this algorithm converges to the optimal solution with an overall complexity of O(N2K2). Numerical results show that the proposed algorithms can make efficient use of the harvested energy, grid energy, energy cooperation, and the available bandwidth.

In this study, authors propose structure to unit memory (UM) convolutional codes that greatly simplify their decoding when using sequential or suboptimal L ‐decoders. The multiscale structure proposed in this study preserves the word‐oriented nature of unit memory codes (UMCs), but allows for processing the code in blocks of sizes less than the memory of the code with non‐Viterbi‐type decoders. At one end of the multiscale structure are generic UMCs. At the other end are structured systematic UMCs that can be decoded with the same ease as conventional multimemory convolutional codes with sequential or L ‐decoders. As a special case, the authors show quick‐look parity check systematic codes of arbitrary rates that are better than previously known optimum minimum distance systematic convolutional codes. These codes are derived from block codes and the convolutional code can be decoded using the syndrome decoder of the underlying block code. The authors present simulation results and analysis to support the proposed multiscale UM convolutional codes.

A novel technique is described for distributed channel coding in wireless communication networks. The protocol is based on a block fading model of the multi-user uplink channel and on adapting multidimensional trellis coded modulation techniques to a coding theorem derived for the block fading channel. The coded modulation (CM) protocol is designed to optimise code performance, especially at high spectral efficiencies. The CM protocol is very simple to implement at the cooperating users. Complexity is completely transferred to the destination. The latency of the protocol is only one symbol. The CM protocol achieves full diversity order equal to the number of cooperating users and maximises coding gains by designing the code for the specific modulation used. We derive analytical results and present simulation results showing the benefits of CM protocol over other comparable schemes.

A novel technique for improving coding and diversity gains in orthogonal frequency division multiplexing (OFDM) systems is proposed. Multidimensional symbol design based on complex field codes with interleaving across frequency has been known for some time now. However, such symbols cannot be concatenated to convolutional codes owing to the prohibitive complexity of decoding. A novel way of designing multidimensional symbols that allow to concatenate them to convolutional codes while maintaining a low decoding complexity is shown. The proposed multidimensional symbols are based on tailbiting convolutional codes and the design of codes is discussed with desirable properties. Also the design of bit interleaved coded modulation-type and trellis-coded modulation-type codes over these multidimensional symbols is shown. Simulations show that the proposed coding scheme provides significant performance and/or complexity improvements over existing alternatives and also provides more degrees of freedom for channel-based link adaptation.

The problem of joint symbol synchronization and decoding of pulse position modulation (PPM) sequences in the deep-space photon-limited optical channel is considered. A new joint synchronizer and decoder for PPM on this channel is presented along with the design of codes having both good error control and synchronization properties for use with PPM signaling on this channel. The new approach presented in this paper provides a significant reduction in synchronizer/decoder complexity when compared to previous methods for joint synchronization and decoding.

In this paper, we present a novel concatenated trellis coded modulation (CTCM) scheme for limited diversity order fading channels. Examples for such channels include those encountered in indoor wireless networks like IEEE 802.11. It is first shown that when the diversity order afforded by the channel is fixed, bit interleaved coded modulation (BICM) is no longer the best way to encode. We then develop CTCM, which is superior to both BICM and conventional TCM of similar complexities. Unlike conventional TCM where convolutional codes are designed over modulated signal sets, CTCM has TCM concatenated to short length inner codes. Each trellis branch in the TCM now corresponds to a short block-code. We discuss design of good inner codes that allow for simple decoders. CTCM design incorporates useful features of both BICM and conventional TCM. Code design is explained with examples. Simulation results and information theoretic supporting the arguments are shown.

Recently, a coded modulation (CM) protocol was proposed for user cooperation diversity in wireless networks. The protocol was based on jointly encoding the data from all cooperating users into one code sequence. In this paper, further results relating to CM protocols are provided, including code analysis techniques. It is shown that tighter bounds are possible by merging a few successive trellis stages into a single bigger trellis with parallel transitions. Cooperation protocols depend critically on the performance over the channel between the cooperating users. Two adaptations of the CM protocol are shown that ensure robustness of the protocol for errors on the channel between the users. The single CM code is used in place of error correction codes anyway used by each user. So, CM based cooperation does not involve further constellation expansion. Hence, it is suitable for high spectral efficiencies also.

We propose a novel coded modulation (CM) protocol for user cooperation diversity in wireless networks. Unlike most existing protocols, the proposed scheme does not involve repetition. This translates to significant gains in terms of achievable rates. Hence, it is suitable for higher spectral efficiencies too. Each user transmits its own bits, along with bits of cooperating users, in every allotted symbol at appropriate positions on a specially labelled signal constellation. The scheme achieves full diversity order in the number of cooperating relays and obtains additional coding gains compared to repetition protocols. We show gains ranging from 2 dB to 3 dB over repetition protocols for cases involving two and three cooperating users. In its simplest form, the proposed scheme has a complexity at the relay equal to that of repetition protocols. Complexity at the base station, however, is increased.

An unbiased, maximum-likelihood (ML), channel parameter-estimation algorithm for direct-sequence spread-spectrum systems with strong interference is discussed in this paper. The algorithm includes correcting terms to the extended Kalman filter (EKF) based on the gradient of the negative log-likelihood function of the output of a conventional matched filter. By an asymptotic analysis, the algorithm is shown to determine the actual parameters. A complete implementation of the algorithm is given, and its transient behavior is examined by computer simulations. Results show the ML algorithm, albeit optimal in the sense of unbiased parameter estimation, is less robust than the modified EKF described in the first reference.

We propose an optically (though not all-optically) decodable error-correction code. The structure of the proposed code is defined in the Fourier spectrum domain. The Fourier spectrum of the codewords has zeros. Thus, we can view any signal appearing in these spectrum zeros as the "syndrome", since the codewords have no energy in these spectrum zeros. The optical technique of the Fourier transform is used for fast decoding speed. The proposed code is nonlinear and of length eight. This code has a total of eight codewords (so the code rate is (log/sub 2/8)/8=3/8) and can correct 1.75 consecutive bit errors on average.

In this paper, we propose techniques for the construction of frequency-coding sequences that give rise to frequency-coded waveforms having ambiguity functions with a clear area - containing no sidelobes - in a connected region surrounding the main lobe. These constructed sequences are called pushing sequences. First, two important properties of pushing sequences are investigated: the group D/sub 4/ dihedral symmetry property and the frequency omission property. Using the group D/sub 4/ dihedral symmetry property, we show how to construct additional pushing sequences from a given pushing sequence. Using the frequency omission property, we show how to construct pushing sequences of any length N and design proper frequency-coded waveforms that meet specific constraints in the frequency domain. Next, we use the Lempel T/sub 4/ construction of Costas sequences to construct pushing sequences with power 1. Finally, we show how to construct pushing sequences with any desired power using Lee codewords. Because these arbitrary-power pushing sequences constructed using Lee codewords do not have the Costas property, we derive expressions for the pattern of hits in the geometric array. Based on this, the general form of the positions and levels of all the sidelobe peaks are derived.

In designing a vector quantizer using a training sequence (TS), the training algorithm tries to find an empirically optimal quantizer that minimizes the selected distortion criteria using the sequence. In order to evaluate the performance of the trained quantizer, we can use the empirically minimized distortion that we obtain when designing the quantizer. Several upper bounds on the empirically minimized distortions are proposed with numerical results. The bound holds pointwise, i.e., for each distribution with finite second moment in a class. From the pointwise bounds, it is possible to derive the worst case bound, which is better than the current bounds for practical training ratio /spl beta/, the ratio of the TS size to the codebook size. It is shown that the empirically minimized distortion underestimates the true minimum distortion by more than a factor of (1-1/m), where m is the sequence size. Furthermore, through an asymptotic analysis in the codebook size, a multiplication factor [1-(1-e/sup -/spl beta//)//spl beta/]/spl ap/(1-1//spl beta/) for an asymptotic bound is shown. Several asymptotic bounds in terms of the vector dimension and the type of source are also introduced.

In this work, we will consider the problem of joint symbol synchronization and decoding of pulse position modulation (PPM) sequences in the deep-space photon-limited optical channel, where joint synchronization and decoding is significantly superior to separate synchronization and decoding. We also consider the design of codes having both good error control and synchronization properties for use with PPM signaling on this channel. While schemes for joint synchronization and decoding on this channel have been previously investigated, the complexity of these schemes has been prohibitive. In addition, their optimality with respect to computational complexity depends on the assumption that symbols are statistically independent and hence uncoded. We propose a two-stage joint synchronizer and decoder that achieve a selected performance requirement while reducing the complexity of joint synchronizer and decoder. The complexity is reduced by terminating synchronization once this error probability requirement is achieved, at which point the synchronizer/decoder functions only as a decoder on the remaining symbols in the received sequences. Therefore, the proposed scheme has practical complexity in the deep-space photon-limited optical channel, which may be used in the future deep-space missions.

It is often advantageous to acquire pulse-echo ground-penetrating radar (GPR) measurements from antennas that are offset from the air-ground interface by a nonnegligible distance, either because the ground's surface is rough, or because measurements must be collected remotely. This paper describes the effects of incorrectly estimating the location of the air-ground interface on GPR images created with the plane-to-plane backpropagation (PPB) method. To compensate for a nonplanar air-ground interface, the wideband time-domain synthetic aperture method is reviewed and reformulated, using Snell's law of refraction, to account for measurements taken some distance above an undulating interface. A modification of the PPB algorithm that accounts for a nonplanar interface is also formulated, and examples of imaging with both methods are given to validate, the algorithms' performance for surface variations that are relatively smooth with respect to the radar waveform wavelengths. Additionally, a method for inferring the surface topography from the radar returns is described. Finally, the modified PPB is demonstrated by imaging buried targets sensed in field-acquired data.

The use of sets of multiple spreading sequences per user in multicarrier code-division multiple-access (CDMA) is investigated. Each user is assumed to have a distinct set of spreading sequences, with a different spreading sequence for each carrier in each user's set. We show that when these sets of sequences are chosen to be the mutually orthogonal (MO) complementary sets of sequences, multiple-access interference is minimal on a nonfading channel. As a result of the autocorrelation sidelobe cancellation properties of the MO complementary sequences, it is possible to pack symbols more closely together on the nonfading channel, resulting in a higher data rate than in multicarrier CDMA using the same spreading sequence for each carrier. The resulting communication system scheme results in an easily parallelized receiver architecture that may be useful in nonfading coherent channels, such as the optical fiber channel or the Rician channel with a strong line-of-sight component. On the Rayleigh fading channel, the performance of the system is identical to that of multicarrier CDMA employing a single spreading sequence per user, with only a minimal increase in receiver complexity.

Transmitter diversity wireless communication systems over Rayleigh fading channels using pilot symbol assisted modulation (PSAM) are studied. Unlike conventional transmitter diversity systems with PSAM that estimate the superimposed fading process, we are able to estimate each individual fading process corresponding to the multiple transmitters by using appropriately designed pilot symbol sequences. With such sequences, special coded modulation schemes can then be designed to access the diversity provided by the multiple transmitters without having to use an interleaver or expand the signal bandwidth. The code matrix notion is introduced for the coded modulation scheme, and its design criteria are also established. In addition to the reduction in receiver complexity, simulation results are compared to, and shown to be superior to, that of an intentional frequency offset system over a wide range of system parameters.

The properties of the ambiguity function and the uncertainty relation of Fourier transforms assert fundamental limitations on the ability of any single radar waveform of constrained time-bandwidth product to distinguish two or more targets closely spaced in both time-delay (range) and Doppler-shift (radial velocity). These same mechanisms place fundamental limits on the ability radar imaging systems to distinguish separate scatterers in delay and Doppler. In this paper, the problem of using multiple waveform sets to make enhanced discrimination delay-Doppler measurements is considered. While small coded waveform sets for enhanced discrimination delay-only measurement are known (e.g., the Golay sequences), these waveforms do not have good Doppler discrimination properties. The problem of designing multiple waveform sets for enhanced discrimination delay-Doppler measurement is investigated, and the composite ambiguity function (CAF) is introduced as a tool to measure the delay-Doppler discrimination characteristics of these waveform sets. The problem of designing optimal coded waveform sets under a time-bandwidth product constraint is considered, and explicit optimal phase, frequency, and joint phase-frequency coded waveform sets having constant amplitude are presented. Algorithms for the construction of such waveform sets of arbitrary size and practical implementation issues are also presented.

We consider the problem of decoding a linear block code used over a binary symmetric channel with crossover probability p when the goal of the decoding is to minimize the probability of an information bit error. In general, there will be several different decoding strategies, each corresponding to the optimal rule over some range p/spl isin/[p/sub i-1/, p/sub i/]. Each of these strategies can be implemented by standard array with the appropriate choice of coset leaders that are not in general of minimum weight. We give optimal rules for selecting coset leaders in the first region [0, p/sub 1/] and the region [p/sub max/, 1/2] for any linear mapping between information bits and codewords. The determination of the optimal rule has been an open problem for small p. The rule for p>p/sub max/ is important because for many codes, when p is fixed the optimal rule for any coset corresponds to either the optimal rule for small p, or the optimal rule for p near 1/2. The optimal decoding strategy varies with the generator matrix used in general, but it is demonstrated that the optimal generator matrix is separable when d/sup /spl perp//>2. The results are shown to extend in a natural way to the case where the goal is to minimize the probability that arbitrary collections of information bits are in error. We examine some specific codes, and compare the performance under optimal decoding to the performance of previously suggested strategies.>

The use of information theory to design waveforms for the measurement of extended radar targets exhibiting resonance phenomena is investigated. The target impulse response is introduced to model target scattering behavior. Two radar waveform design problems with constraints on waveform energy and duration are then solved. In the first, a deterministic target impulse response is used to design waveform/receiver-filter pairs for the optimal detection of extended targets in additive noise. In the second, a random target impulse response is used to design waveforms that maximize the mutual information between a target ensemble and the received signal in additive Gaussian noise. The two solutions are contrasted to show the difference between the characteristics of waveforms for extended target detection and information extraction. The optimal target detection solution places as much energy as possible in the largest target scattering mode under the imposed constraints on waveform duration and energy. The optimal information extraction solution distributes the energy among the target scattering modes in order to maximize the mutual information between the target ensemble and the received radar waveform.>