Polar coding subject to memoryless impulse noise described by a Gaussian mixture model is investigated. In contrast with existing approaches resorting to latency-laced interleaving, this paper tackles statistical dependence between in-phase and quadrature components of impulse noise, attributable to employing higher order modulation schemes, with meticulous revision in successive cancellation decoding. Furthermore, forfeiting using the statistical knowledge of impulse noise, a density evolution-based code construction method is proposed. Challenges of the aggravated complexity-ensued from addressing the aforementioned statistical dependence-are subsequently overcome by an approximation approach. The block error rate performance for the proposed framework is investigated by computer simulations and the experimental results exhibit the markedly performance gain over the conventional construction method under certain circumstances.

Communications systems suffer from impulsive in- terference, generally modeled as a memory channel to account for the inherent bursts of impulse even though conventional receivers take into account the additive white Gaussian noise only. In this paper, finite- field based constructions of Low Density Parity Check (LDPC) coding over the Markov Gaussian channel are investigated. In contrast with existing approaches assuming the impulse noise statistics, this paper proposes a modified maximum- a-priori method, which forfeits using the statistical knowledge of impulse, to estimate whether or not each transmitted symbol is corrupted by impulse noise. Subsequently, the sum-product algorithm LDPC decoder invokes a clipper to diminish impulsive interference when the channel state is identified to be impulse- corrupted. The bit error rate (BER) performance versus the signal-to-noise ratio for the proposed decoder is conducted using computer simulation. The experimental results in terms of the BER performance justified the robustness of our proposed receiver and also revealed its competitiveness with the optimal benchmark decoder in the hostile environment. Moreover, using the proposed receiver, our calibrated quasi-cyclic LDPC code is shown to slightly outperform its 5G New Radio counterpart under certain circumstances.

An efficient approach to alleviating performance loss caused by unknown (non-stationary) impulse noise, which is typically sparse and whose statistics are difficult to model accurately, was made possible in power line communications systems when the clipping operation is properly implemented. As reported in numerous papers, the clipping threshold, which impacts system performance profoundly, is closely related with the probability of impulse occurrence and the strength of the background noise. This paper first highlights that the least-absolute-shrinkage-and-selection-operator (LASSO) algorithm, aimed at estimating the regularization parameter λ and sparse vector of regression coefficients, can be interpreted as an effective clipping operation. Subsequently, a hybrid of the Bayesian LASSO and the maximum a posteriori algorithm using the Monte Carlo expectation maximization (MCEM) is proposed to simultaneously estimate the regularization parameter and detect the convolutional codeword in single-carrier coded systems subject to the impulse noise. Moreover, by exploiting information exchangeable between those two aforementioned entities, a novel termination rule on the EM iteration stage is devised. Numerical results attest the efficacy of the proposed scheme, despite a lack of statistical knowledge on impulse noise models.

By assuming the impulse statistics, channel coding has long served as an effective tool against fairly frequent occurrence of strong impulses, which impedes the guaranteed quality of service of communication systems. Nevertheless, impulse statistics are generally hard to be modeled and likely to be time-varying, posing a great challenge to system design. Our previous work reveals that, without assuming any impulse noise model, the metric erasure Viterbi algorithm (MEVA) can achieve the performance derived from the (benchmark) maximum likelihood decoding in single-carrier convolutionally coded system subject to memoryless strong impulses, provided that the clipping threshold is judiciously selected and the power strength of the background noise, σ2is known. In an attempt to alleviate the assumption of using σ2, this paper proposes the iterative MEVA (IMEVA): the information regarding the indicator sequence (which is induced by the MEVA) is leveraged and passed to the σ2-estimator for refining the clipping threshold estimate at the next iteration. Regardless of the impulse noise model encountered, simulation results show that the IMEVA performs remarkably close to that of the Baum-Welch algorithm, which, at the cost of receiver complexity, relies on knowing the underlying impulse noise model.

Wireless communications in cognitive radio systems are susceptible to in-band interference caused by other communication systems simultaneously sharing partial frequency band. Thus, if not properly coordinated, the CR systems can critically fall short of the guaranteed system performance. This paper proposes a robust and efficient decoding scheme to combat the nuisance without resorting to laborious estimation of in-band interference statistics, which are generally time-varying and difficult to accurately model. Taking into account the system framework as well as incorporating the clipping operation, the decoding scheme performs an erasure marking of the bit metric regarding a higher order modulation format jointly with the Viterbi algorithm in an iterative manner. Simulation results reveal that, in fairly general scenarios, the proposed method, when appropriately setting the bit metric clipping threshold, can achieve the bit error probability performance of its sophisticated counterpart, which uses the in- band interference statistics. Furthermore, compared with an existing scheme, the complexity of the proposed method is significantly reduced.

It is well known that communication systems are susceptible to strong impulsive noises. To combat this, convolutional coding has long served as a cost-efficient tool against moderately frequent memoryless impulses with given statistics. Nevertheless, impulsive noise statistics are difficult to model accurately and are typically not time-invariant, making the system design challenging. In this paper, because of the lack of knowledge regarding the probability density function of impulsive noises, an efficient decoding scheme was devised for single-carrier narrowband communication systems; a design parameter was incorporated into recently introduced joint erasure marking and Viterbi decoding algorithm, dubbed the metric erasure Viterbi algorithm (MEVA). The proposed scheme involves incorporating a well-designed clipping operation into a Viterbi algorithm, in which the clipping threshold must be appropriately set. In contrast to previous publications that have resorted to extensive simulations, in the proposed scheme, the bit error probability performance associated with the clipping threshold was characterized by deriving its Chernoff bound. The results indicated that when the clipping threshold was judiciously selected, the MEVA can be on par with its optimal maximum-likelihood decoding counterpart under fairly general circumstances.

In this paper, we consider amplify-and-forward relaying scheme with a single-relay framework, where the involved links between transmit-receive pairs may experience different delay spread. Without channel state information assumed or estimated at the destination terminal, unitary spacetime modulation (USTM) derived from complex orthogonal spreading sequence set was adopted for the distributed single-carrier block transmission. Our pairwise error probability (PEP) analysis indicates that the multipath diversity can be exploited based on the USTM in couple with the noncoherent demodulation rule. Numerical results vindicate the merit of multipaths under certain circumstances such as the link quality from the source to relay as well as power control at relay node.

It is well known that an anti-collision protocol plays an essential role in the overall tag read time in radio-frequency identification systems because of the obstruction caused by tag collision. With an aim at speeding up the tag identification process, the authors propose an anti-collision algorithm, the spread partial-Q slot count (SPSC) algorithm, based on a slotted ALOHA code division multiple access technique along with tag set partitioning. A new packet structure is introduced preceded by a description of the mechanism of partition-wise identification process. In fact, according to received power levels, tags are partitioned into a certain number of groups. In the partition-wise identification process, tags belonging to two subsets are regrouped as a partition with a guarantee of having a uniformly largest received power level difference in a tag set so as to be interrogated by the reader simultaneously. The identification process for each partition is then operated sequentially. Indeed, tag set partitioning in conjunction with spread spectrum techniques could enable a simple multi-tag access detection scheme and improve system throughput as well. Simulations demonstrated that the SPSC algorithm outperforms some existing anti-collision algorithms in terms of throughput.

Space-time trellis coding systems employing orthogonal frequency division multiplexing (OFDM) technique over frequency-selective channels is considered, where the fading gains could vary within a frame interval encompassing a number of OFDM symbol times. The frequency-domain channel time evolution of sub-carriers associated with OFDM symbol is first approximated by a state space model. The per-survivor processing (PSP) incorporated into Kalman filtering (KF) thus enables a recursive receiver for channel tracking along with data decoding. In view of the computational complexity of this PSP-Kalman growing exponentially with the number of sub-carriers, a reduced-complexity alternative by capitalizing on channel cross-correlation on the basis of per- group of neighboring sub-carriers in a sequential order within an OFDM symbol is proposed. Computer simulations are provided to demonstrate the efficacy of the addressed approaches in terms of root mean squared error (RMSE) and frame error rate (FER) in certain different scenarios.

It is well known that anti-collision protocol plays an essential role in overall tag read time in radio frequency identification (RFID) systems due to the obstruction caused by tag-collision. With an aim at speeding up tag identification process, we propose an anti-collision algorithm, spread partial-Q slot count (SPSQ) algorithm, based on a slotted ALOHA code division multiple access (CDMA) technique along with tag set partitioning. A new packet structure is introduced preceded by a description of the mechanism of partition-wise identification process. In fact, according to received power levels tags are partitioned into a certain number of groups. In the partition-wise identification process tags belonging to two subsets are regrouped as a partition with a guarantee of uniformly largest received power-level difference in a tag set so as to be interrogated by the reader simultaneously. The identification process for each partition is then operated sequentially. Indeed, tag set partitioning in conjunction with spread spectrum techniques could enable a simple multi-tag access detection scheme and improve system throughput as well. Simulations demonstrated that SPSC algorithm outperforms some existing anti-collision algorithms in terms of throughput.

We employ time-reversal space-time block coding (TR-STBQ in single-carrier direct sequence code- division multiple access (DS-CDMA) block transmission in the presence of multiple access interference (MAI) as well as intersyrnbol interference (ISI), which is subject to fairly long delay spread. We introduce the transmission rate improvement by capitalizing on the assignment of additional spreading codes to each user so as to expand the cardinality of space-time code matrix. Given perfect channel state information at the receiver, a simple linear frequency-domain interference suppression scheme on a basis of symbol-by-symbol processing is developed under certain circumstances. A soft receiver is facilitated by exploiting the serially concatenated structure at the transmitter to further enhance system performance. Simulation results justify the efficacy of our proposed system and also present performance comparison with well-known OFDM systems in terms of bit error rate (BER).

An uplink direct sequence spread spectrum communications systems employing a multi-sequence model over a quasi-static frequency-selective fading channel is considered. In analogy with bit-interleaved coded modulation (BICM) technique, a group of bits at the output of a bit-wise interleaver is mapped uniquely to a complex signalling vector belonging to an orthogonal plane sequence modulation signal space, which is constructed over a set of expanded signature sequences. This transmission system provides not only bandwidth efficiency offered by additional signal planes but also time diversity resulting from the BICM technique. It is observed that at high system traffic load error performance could degrade substantially due to user cross-correlations, multi-access asynchronism as well as channel frequency selectivity. The authors employ a ‘turbo principle’ receiver, consisting of a soft interference cancellation scheme, soft demappers and maximum a posteriori decoders, to avert this capacity loss by exploiting the serially concatenating structure at the transmitter. After simple mathematical manipulation, a soft space–time linear minimum mean-square error multi-user detector could even be explored on the basis of per signal plane per user. Both analytical performance-bound and computer simulation of the proposed framework in terms of bit-error rate (BER) are revealed. Further, performance comparisons with convolutionally coded and conventional bandwidth-efficient coded direct sequence code division multiple access systems under the same system conditions are illustrated. The authors have also investigated the impact of labelling maps on the BER performance.

In this paper, an iterative multiuser detector (MUD) is addressed for asynchronous direct sequence spread spectrum communications systems employing multi-sequence signaling over a quasi-static frequency-selective fading channel. A bit-interleaved coded modulation (BICM) scheme, facilitating the "turbo principle" receiver through iterative processing, is introduced to increase the time diversity. With a multi-sequence signaling set mapper constructed over expanded spreading sequences, each of which is regarded as a signal plane with uniformly distributed signal points assumed, user cross-correlations could be nevertheless increased under certain situations. A soft interference cancellation scheme, derived by the minimum mean-squared error (MMSE) sense on a basis of per sequence plane per user, is employed to compensate for the increased multiple access interference (MAI) at high system traffic load. Simulation results demonstrate system performance in comparison with both conventional standard coded and bandwidth-efficient coded DS-CDMA systems in terms of bit error rate under the same system traffic load, channel condition and given power and spectral efficiency.

This paper addresses an iterative receiver with joint detection and decoding for multi-carrier code division multiple access (MC-CDMA) systems employing multi-sequence signaling. A bit-interleaved coded modulation (BICM) technique, facilitating the "turbo principle" receiver through iterative processing, is utilized to maximize the frequency diversity, followed by a multi-sequence signaling set mapper with functionality of modulation in conjunction with spreading. User cross-correlations could be adversely increased due to the channel frequency selectivity and utilization of expanded signature sequences per user. To account for this ensuring performance loss, we employ a soft space-time interference cancellation receiver derived by minimum mean-squared error (MMSE) sense on a basis of per sequence plane per user to provide reliabilities of code bits. Simulation results justify our proposed approach in terms of bit error rate over a quasistatic fading channel with the number of users a significant fraction of spreading length. Performance comparison between our proposed scheme and conventional bandwidth-efficient coded MC-CDMA system is also manifested via simulations.