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Ambient backscatter technology has attracted much attention recently, because it enables battery-free devices, such as tags or sensors, to communicate through wireless energy harvesting and radio backscattering. Existing studies about ambient backscatter assume that the tags have only two states: backscatter or non-backscatter. Actually, some references have shown that the tags can readily realize three states: positive and negative phase backscatter, and non-backscatter. In this paper, we propose a new coding scheme for these tags with three states to improve the throughput of the ambient backscatter communication system. We then design a maximum a posteriori (MAP) detector for the reader to extract binary information from ternary coded signals. We also analyze the detection performance in terms of closed-form bit error rate (BER) expressions. It is found that the proposed coding scheme can improve the throughput of an ambient backscatter system, and there exists an error floor for the BER curve. Finally, simulation results are provided to corroborate our theoretical studies.

In this paper, we derive the maximum a posteriori (MAP) symbol detector for a multiple-input multiple-output system in the presence of Wiener phase noise due to noisy local oscillators, and quasi-static fading channels. As in single-antenna systems, the computation of the optimum receiver is an analytically intractable problem and is unimplementable in practice. In this purview, we propose three suboptimal, low-complexity algorithms for approximately implementing the MAP symbol detector, which involve joint phase noise estimation and data detection. Our first algorithm is obtained by means of the sum-product algorithm, where we use the multivariate Tikhonov canonical distribution approach. In our next algorithm, we derive an approximate MAP symbol detector based on the smoother-detector framework, wherein the detector is properly designed by incorporating the phase noise statistics from the smoother. The third algorithm is derived based on the variational Bayesian framework. By simulations, we evaluate the performance of the proposed algorithms for both uncoded and coded data transmissions and observe that the proposed techniques significantly outperform the other important algorithms from prior works, which are considered herein. [ABSTRACT FROM PUBLISHER]

Transmission over channels impaired by impulsive noise, such as in power substations, calls for peculiar mitigation techniques at the receiver side in order to cope with signal deterioration. For these techniques to be effective, a reliable noise model is usually required. One of the widely accepted models is the Middleton Class A, which presents the twofold advantage to be canonical (i.e., invariant of the particular physical source mechanisms) and to exhibit a simple probability density function (PDF) that only depends on three physical parameters, making this model very attractive. However, such a model fails in replicating bursty impulsive noise, where each impulse spans over several consecutive noise samples, as usually observed (e.g., in power substations). Indeed, the Middleton Class A model only deals with amplitude or envelope statistics. On the other hand, for models based on Markov chains, although they reproduce the bursty nature of impulses, the determination of the suitable number of states and the noise distribution associated with each state can be challenging. In this paper, 1) we introduce a new impulsive noise model which is, in fact, a Hidden Markov Model, whose realizations exactly follow a Middleton Class A distribution and 2) we evaluate optimum and suboptimum detections for a coded transmission impaired by the proposed noise model. [ABSTRACT FROM AUTHOR]

We compare several different detection and equalization methods for bit patterned media recording channels .We consider a scheme that utilizes a joint-track equalization technique followed by a Viterbi detector. For certain recording densities, simulation results show that it has essentially the same performance as an optimal detector but with reduced detection complexity. Furthermore, it outperforms another scheme of the same complexity previously described in the literature. [ABSTRACT FROM AUTHOR]

For turbo-coded differential phase-shift-keying (DPSK) systems under correlated flat-fading channels, a serial iterative structure of soft-input-soft-output (SISO) forward/backward MAP (FB-MAP) detection and SISO decoder is proposed to reduce the computational complexity of MAP detection without performance degradation. The simulation results show that the FB-MAP detection scheme offers the same or better bit error rate (BER) performance with lower computational complexity when compared with the a posteriori probability (APP) demodulator, the SISO MAP detection, and the SISO multiple-symbol differential sphere decoder (MSDSD) scheme. Although the computational complexity is higher than the iterative filtered multiple differential detection (IF-MDD) scheme, the proposed detection scheme can have better BER performance. [ABSTRACT FROM AUTHOR]

We report a study of bit-patterned media recording channels containing written-in errors. From a signal processing point of view, we consider an abstract model for the overall recording channel, incorporating errors caused by timing and write ability. Based on the resulting channel model, we develop various trellis structures, and propose several detection algorithms that can be used to recover the recorded data. Furthermore, we investigate achievable information rates for patterned media recording systems with different levels of written-in error probability, providing an information theoretical performance assessment for such systems. [ABSTRACT FROM AUTHOR]

Exact evaluation of bit- and symbol-error rates in a 2-D constellation is a fundamental problem of digital communications, which only for particular modulations and/or bits-to-symbol mapping has closed-form solutions. Here, we propose a general, numerically efficient algorithmic method, which yields the exact results for arbitrary modulation symbols' set and arbitrary bits-to-symbol mapping, and which deals with the case of nonuniform signaling. These three conditions define any digital transmission using memoryless modulation, so the proposed method is a general tool solving all problems tackled in the literature under constraints imposed on one or more of the parameters defining the modulation or signaling type. Such an evaluation tool is of practical importance during the design of the modulation. Our analysis and numerical simulations show the advantages offered by the new method when compared with the bounding techniques. [ABSTRACT FROM AUTHOR]

Techniques for computing soft information in the presence of unknown intersymbol interference are presented, with a particular focus on iterative detection of serially concatenated continuous phase modulation. The techniques are centered around the recursive least-squares algorithm, thus enabling unsupervised detection. In particular, we employ bidirectional estimation. [ABSTRACT FROM AUTHOR]

In recent years, combining multiuser detection (MUD) and channel decoding has received considerable attention. The maximum a posteriori (MAP) criterion-based iterative multiuser detector greatly improves the system performance and can approach the performance of single-user coded systems. However, its complexity increases exponentially with the number of users and can become prohibitive for systems with a medium-to-large number of users. In this paper, a reduced complexity MAP-based iterative MUD based on the use of a soft sensitive bits algorithm is proposed for coded multicarrier code-division multiple-access systems. It is shown that it can greatly reduce the computational complexity with a minimal penalty in performance compared to the conventional optimal scheme. [ABSTRACT FROM AUTHOR]

The performance loss due to separation of detection and decoding on the binary-input additive white Gaussian noise (AWGN) channel is quantified in terms of mutual information. Results are reported for both the code-division multiple-access (CDMA) channel In the large system limit and the Intersymbol interference (ISI) channel. The results for CDMA rely on the replica method developed in statistical mechanics. It Is shown that a previous result of Shamal and Verdú found for Gaussian input alphabet holds also for binary Input alphabets. For the ISI channel, the performance loss Is calculated via the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. Comparisons are made to the capacity of separate detection and decoding using suboptimum detectors such as a decision-feedback eqnalizer. [ABSTRACT FROM AUTHOR]

An adaptive maximum a posteriori (MAP) receiver withmultiple-access interference (MAI) mitigation is proposed for DS-CDMAsystems in frequency-flat, time-varying fading channels. The receiverconsists of a sequence matched filter (MF), an adaptive channelestimator, and a MAP demodulator. By oversampling the MF output, thereceiver can characterize the MAI symbol-by-symbol to suppress thestrong and time-varying MAI. Without any pilot insertion and apriori knowledge, the channel estimator can adapt to various fadingchannels using a general, model-based approach. For practicalimplementations, a reduction in complexity is introduced and is shownto have a negligible effect on both uncoded and decoded bit errorrates (BER's). [ABSTRACT FROM AUTHOR]