This letter presents a comprehensive analytical framework for average pairwise error probability (PEP) of decode-and-forward cooperative network based on various distributed space-time block codes (DSTBCs) with antenna switching (DDF-AS) technique over quasi-static Rayleigh fading channels. Utilizing the analytical framework, exact and asymptotic PEP expressions can be effectively formulated, which are based on the Lauricella multiplicative hypergeometric function, when various DSTBCs are adopted for the DDF-AS system. The derived asymptotic PEP formulas and some numerical results enable us to verify that the DDF-AS scheme outperforms the conventional cooperative schemes in terms of error rate performance. Furthermore, the asymptotic PEP formulas can also provide explicit and useful insights into the full diversity transmission achieved by the DDF-AS system.

In super-Nyquist wavelength division multiplexed systems, performance of forward error correction (FEC) can be improved by an iterative decoder between a maximum likelihood decoder for polybinary shaping and an FEC decoder. The typical iterative decoder includes not only the iteration between the first and second decoders but also the internal iteration within the FEC decoder. Such two-fold loop configuration would increase the computational complexity for decoding. In this paper, we propose the simplified iterative decoder, where the internal iteration in the FEC decoder is not performed, reducing the computational complexity. We numerically evaluate the bit-error rate performance of polybinary-shaped QPSK signals in the simplified iterative decoder. The numerical results show that the FEC performance can be improved in the simplified scheme, compared with the typical iterative decoder. In addition, the performance of the simplified iterative decoder has been investigated by the extrinsic information transfer (EXIT) chart.

This paper analyzes the performance of single-cell massive multiple-input multiple-output (MIMO) systems with non-orthogonal pilots. Specifically, closed-form expressions of the normalized channel estimation error and achievable uplink capacity are derived for both least squares (LS) and minimum mean square error (MMSE) estimation. Then a pilot reconstruction scheme based on orthogonal Procrustes principle (OPP) is provided to reduce the total normalized mean square error (NMSE) of channel estimations. With these reconstructed pilots, a two-step pilot assignment method is formulated by considering the correlation coefficient among pilots to reduce the maximum NMSE. Based on this assignment method, a step-by-step pilot power allocation scheme is further proposed to improve the average uplink signal-to-interference and noise ratio (SINR). At last, simulation results demonstrate the superiority of the proposed approaches.

The influence of pump phase error on phase-sensitive optical amplifier (PSA) repeaters and the waveform degradation due to chromatic dispersion and fiber nonlinearities in the optical multi-relay transmission of quadrature phase-shift keying phase-conjugated twin waves are considered theoretically. First, the influence of noise from the pump phase error, optical local oscillator, receiver, and the amplified spontaneous-emission (ASE) in PSA repeaters is investigated with the assumption that transmission fibers are linear lossy channels. The bit-error rate (BER) is estimated as a function of the signal-to-noise ratio, and the relationship between the number of transmission relays and the fiber launch power is clarified. Waveform degradation due to chromatic dispersion and the optical fiber nonlinearities in transmission fibers are investigated with the noiseless condition, and the maximum repeatable number as a function of the fiber launch power is calculated. Finally, we show the relationship among the maximum repeatable number, standard deviation of pump phase error in PSA repeaters, and the fiber launch power to clarify the optimum transmission condition with consideration of the noise and the waveform degradation.

All digital phased arrays generate multiple beams concurrently through the digital beam forming technique, which features digital processing with multiple identical receiving/transmitting channels in RF or microwave frequencies. However, the performance of this process strongly depends on accurately matching the amplitude and phase of the channels, as mismatching is likely to degrade radar performance. In this paper, we present a method to calibrate receiving array by using NCO phase increasing algorithm, which simplifies array system by removing the external far-field calibration signals often needed in array systems. Both analysis and simulation results suggest that the proposed method attains better calibration performance than existing approaches, even with a low SNR input signal. Experiments also varify that the proposed calibration method is effective and achieves a desired radiation pattern. We can further boost calibration accuracy and reduce calibration time by programming NCO phase width and NCO phase resolution.

Soft error jeopardizes the reliability of semiconductor devices, especially those working at low voltage. In recent years, silicon-on-thin-box (SOTB), which is a FD-SOI device, is drawing attention since it is suitable for ultra-low-voltage operation. This work evaluates the contributions of SRAM, FF and combinational circuit to chip-level soft error rate (SER) based on irradiation test results. For this evaluation, this work performed neutron irradiation test for characterizing single event transient (SET) rate of SOTB and bulk circuits at 0.5 V. Using the SBU and MCU data in SRAMs from previous work, we calculated the MBU rate with/without error correcting code (ECC) and with 1/2/4-col MUX interleaving. Combining FF error rates reported in literature, we estimated chip-level SER and each contribution to chip-level SER for embedded and high-performance processors. For both the processors, without ECC, 95% errors occur at SRAM in both SOTB and bulk chips at 0.5 V and 1.0 V, and the overall chip-level SERs of the assumed SOTB chip at 0.5 V is at least 10 x lower than that of bulk chip. On the other hand, when ECC is applied to SRAM in the SOTB chip, SEUs occurring at FFs are dominant in the high-performance processor while MBUs at SRAMs are not negligible in the bulk embedded chips.

This paper presents the bit error rate (BER) performance of human body communication (HBC) receivers in interference-rich environments. The BER performance was measured while applying an interference signal to the HBC receiver to consider the effect of receiver performance on BER performance. During the measurement, a signal attenuator was used to mimic the signal loss of the human body channel, which improved the repeatability of the measurement results. The measurement results showed that HBC is robust against the interference when frequency selective digital transmission (FSDT) is used as a modulation scheme. The BER performance in this paper can be effectively used to evaluate a communication performance of HBC.

In this paper, we analyze the impact of channel estimation errors in an amplify-and-forward (AF)-based two-way relaying network (TWRN) where adaptive modulation (AM) is employed in individual relaying path. In particular, the performance degradation caused by channel estimation error is investigated over Nakagami-m fading channels. We first derive an end-to-end signal-to-noise ratio (SNR), a cumulative distribution function, and a probability density function in the presence of channel estimation error for the AF-based TWRN with adaptive modulation (TWRN-AM). By utilizing the derived SNR statistics, we present accurate expressions of the average spectral efficiency and bit error rates with an outage-constraint in which transmission does not take place during outage events of bidirectional communications. Based on our derived analytical results, an optimal power allocation scheme for TWRN-AM is proposed to improve the average spectral efficiency by minimizing system outages.

This letter proposes a representation learning framework of convolutional neural networks (Convnets) that aims to rectify and improve the feature representations learned by existing transformation-invariant methods. The existing methods usually encode feature representations invariant to a wide range of spatial transformations by augmenting input images or transforming intermediate layers. Unfortunately, simply transforming the intermediate feature maps may lead to unpredictable representations that are ineffective in describing the transformed features of the inputs. The reason is that the operations of convolution and geometric transformation are not exchangeable in most cases and so exchanging the two operations will yield the transformation error. The error may potentially harm the performance of the classification networks. Motivated by the fractal statistics of natural images, this letter proposes a rectifying transformation operator to minimize the error. The proposed method is differentiable and can be inserted into the convolutional architecture without making any modification to the optimization algorithm. We show that the rectified feature representations result in better classification performance on two benchmarks.

Quasi cyclic LDPC (QC-LDPC) codes consisting of circulant permutation matrices (CPM-QC-LDPC) are one of the most attractive types of LDPC codes due to their many advantages. In this paper, we mainly do some research on CPM-QC-LDPC codes. We first propose a two-stage decoding scheme mainly based on parity check matrix transform (MT), which can efficiently improve the bit error rate performance. To optimize the tradeoff between hardware implementation complexity and decoding performance, an improved method that combines our proposed MT scheme with the existing CPM-RID decoding scheme is presented. An experiment shows that both schemes can improve the bit error rate (BER) performance. Finally, we show that the MT decoding mechanism can be applied to other types of LDPC codes. We apply the MT scheme to random LDPC codes and show that it can efficiently lower the error floor.

We propose a novel bit error rate (BER) analysis model of weighted-type fractional Fourier transform (WFRFT)-based systems with WFRFT order offset Δα. By using the traditional BPSK BER analysis method, we deduce the equivalent signal noise ratio (SNR), model the interference in the channel as a Gaussian noise with non-zero mean, and provide a theoretical BER expression of the proposed system. Simulation results show that its theoretical BER performance well matches the empirical performance, which demonstrates that the theoretical BER analysis proposed in this paper is reliable.

Maximal designed distances for nonbinary narrow-sense quantum Bose-Chaudhuri-Hocquenghem (BCH) codes of length $n=rac{q^4-1}{r}$ and new constructions for them are given, where q is an odd prime power. These constructions are capable of designing quantum BCH codes with new parameters. Furthermore, some codes obtained here have better parameters than those constructed by other known constructions.

Two kinds of problems - multiterminal hypothesis testing and one-to-many lossy source coding - are investigated in a unified way. It is demonstrated that a simple key idea, which is developed by Iriyama for one-to-one source coding systems, can be applied to multiterminal source coding systems. In particular, general bounds on the error exponents for multiterminal hypothesis testing and one-to-many lossy source coding are given.

Performance of network coded cooperation over the Gaussian channel in which multiple communication nodes send each one's message to a common destination is analyzed. The nodes first broadcast the message, and subsequently relay the XOR of subset of decoded messages to the destination. The received vector at the destination can be equivalently regarded as the output of a point-to-point channel, except that the underlying codes are drawn probabilistically and symbol errors may occur before transmission of a codeword. We analyze the error performance of this system from coding theoretic viewpoint.

For voice-enabled car navigation systems that use a multi-purpose cloud speech recognition service (cloud ASR), utterance classification that is robust against speech recognition errors is needed to realize a user-friendly voice interface. The purpose of this study is to improve the accuracy of utterance classification for voice-enabled car navigation systems when inputs to a classifier are error-prone speech recognition results obtained from a cloud ASR. The role of utterance classification is to predict which car navigation function a user wants to execute from a spontaneous utterance. A cloud ASR causes speech recognition errors due to the noises that occur when traveling in a car, and the errors degrade the accuracy of utterance classification. There are many methods for reducing the number of speech recognition errors by modifying the inside of a speech recognizer. However, application developers cannot apply these methods to cloud ASRs because they cannot customize the ASRs. In this paper, we propose a system for improving the accuracy of utterance classification by modifying both speech-signal inputs to a cloud ASR and recognized-sentence outputs from an ASR. First, our system performs speech enhancement on a user's utterance and then sends both enhanced and non-enhanced speech signals to a cloud ASR. Speech recognition results from both speech signals are merged to reduce the number of recognition errors. Second, to reduce that of utterance classification errors, we propose a data augmentation method, which we call “optimal doping,” where not only accurate transcriptions but also error-prone recognized sentences are added to training data. An evaluation with real user utterances spoken to car navigation products showed that our system reduces the number of utterance classification errors by 54% from a baseline condition. Finally, we propose a semi-automatic upgrading approach for classifiers to benefit from the improved performance of cloud ASRs.

Racetrack memory (RM) has attracted much attention. In RM, insertion and deletion (ID) errors occur as a result of an unstable reading process and are called position errors. In this paper, we first define a probabilistic channel model of ID errors in RM with multiple read-heads (RHs). Then, we propose a joint iterative decoding algorithm for spatially coupled low-density parity-check (SC-LDPC) codes over such a channel. We investigate the asymptotic behaviors of SC-LDPC codes under the proposed decoding algorithm using density evolution (DE). With DE, we reveal the relationship between the number of RHs and achievable information rates, along with the iterative decoding thresholds. The results show that increasing the number of RHs provides higher decoding performances, although the proposed decoding algorithm requires each codeword bit to be read only once regardless of the number of RHs. Moreover, we show the performance improvement produced by adjusting the order of the SC-LDPC codeword bits in RM.

Spatially “Mt. Fuji” coupled (SFC) low density parity check (LDPC) codes are constructed as a chain of block LDPC codes. A difference between the SFC-LDPC codes and the original spatially coupled (SC) LDPC codes is code lengths of the underlying block LDPC codes. The code length of the block LDPC code at the middle of the chain is larger than that at the end of the chain. It is experimentally confirmed that the bit error probability in the error floor region of the SFC-LDPC code is lower than that of the SC-LDPC code whose code length and design rate are the same as those of the SFC-LDPC code. In this letter, we calculate the weight distribution of the SFC-LDPC code and try to explain causes of the low bit error rates of the SFC-LDPC code.

As LSI chips integrate more transistors and the operating power supply voltage decreases, LSI chips are becoming more vulnerable to the soft error caused by neutrons induced from cosmic rays. The soft error is detected by comparing the duplicated operation results in double modular redundancy (DMR) and the error is corrected by re-executing necessary operations. In this paper, based on the error recovery scheme of re-executing necessary operations, the minimization of the vote operations for error checking with respect to given resource constraints is considered. An ILP model for the optimal solution to the problem is presented and a heuristic algorithm is proposed to minimize the vote operations.

Locally repairable codes, which can repair erased symbols from other symbols, have attracted a good deal of attention in recent years because its local repair property is effective on distributed storage systems. (ru, δu)u∈[s]-locally repairable codes with multiple localities, which are an extension of ordinary locally repairable codes, can repair δu-1 erased symbols simultaneously from a set consisting of at most ru symbols. An upper bound on the minimum distance of these codes and a construction method of optimal codes, attaining this bound with equality, were given by Chen, Hao, and Xia. In this paper, we discuss the parameter restrictions of the existing construction, and we propose explicit constructions of optimal codes with multiple localities with relaxed restrictions based on the encoding polynomial introduced by Tamo and Barg. The proposed construction can design a code whose minimum distance is unrealizable by the existing construction.

In this paper, we deal with coding for synchronous errors. We introduce a synchronously erroneous finite state Markov channel model whose SIR is computable. We apply density evolution analysis [1] and the extended version for FSMC [2] to the channel Numerical experiments demonstrated spatially-coupled codes approach the SIR of the channel.