Iterative channel estimation and decoding receivers have evolved over the years, most especially with Turbo and LPDC codes. Nevertheless, few works have determined the performance of symbol level Reed-Solomon (RS) codes in iterative receiver structures. The iterative channel estimation and symbol level RS decoding receiver structure found in literature concentrate on M-QAM systems over flat Rayleigh fading channels. In this paper, attention is focused on the performance of RS codes in iterative channel estimation and decoding receiver structures for Orthogonal Frequency Division Multiplexing (OFDM) systems on frequency-selective Rayleigh fading channels. Firstly, the paper extends the Koetter and Vardy (KV) RS iterative receiver structure over flat Rayleigh fading channels to frequency-selective Rayleigh fading channels. In addition, the paper develops a symbol level RS iterative receiver structure for OFDM systems on frequency-selective Rayleigh fading channels based on the Parity-check matrix Transformation Algorithm (PTA). The performance of the RS-KV and RS-PTA iterative receiver structures for OFDM systems are documented through computer simulation. The simulation results verify that both iterative receiver structures are suitable for real time RS OFDM wireless applications. The results also show that the developed RS-PTA iterative receiver structure is a low complexity and high performance alternative to the RS-KV iterative receiver structure.

In this paper, we investigate the channel characteristics of underwater optical wireless communications (UOWC) based on Monte Carlo simulation method. The impulse response and channel time dispersion of the link are discussed. Also we consider the channel parameters comprehensively like the water type, attenuation length, divergence angle, beam width, field-of-view (FOV), receiver aperture and position. Simulation results suggest that in clear water, the channel can effectively be considered as non inter-symbol interference (ISI) when working over distance of up to 40m. Therefore, in practice the receiver does not need to perform computationally complex signal processing operations. However, in harbor water, the channel time dispersion will enlarge with larger FOV or divergence angle, and reduce the data transmission efficiency. When the attenuation length is smaller than diffused length, larger receivers offer lower intensity than smaller ones. In contrast, the intensity enhances with larger receiver at the small FOV, however, they trend to similar regardless of the apertures at large FOV. Furthermore, we study the effect of misalignment of the transmitter and receiver on the received intensity. The results give us some insight in terms of what constitutes an accurate UOWC channel.

In the present paper, we propose a broadcast ARQ protocol based on the concept of index coding. In the proposed scenario, a server wishes to transmit a finite sequence of packets to multiple receivers via a broadcast channel with packet erasures until all of the receivers successfully receive all of the packets. In the retransmission phase, the server produces a coded packet as a retransmitted packet based on the side-information sent from the receivers via feedback channels. A notable feature of the proposed protocol is that the decoding process at the receiver side has low decoding complexity because only a small number of addition operations are needed in order to recover an intended packet. This feature may be preferable for reducing the power consumption of receivers. The throughput performance of the proposed protocol is close to that of the ideal FEC throughput performance when the erasure probability is less than 0.1. This implies that the proposed protocol provides almost optimal throughput performance in such a regime.

In this paper, we propose to use a strategy for the two-user Gaussian X channel with limited receiver cooperation in the general case consisting of two parts: 1) the transmission scheme where the superposition coding is used and 2) the cooperative protocol where the two-round strategy based on quantize-map-and-forward (QMF) is employed. We image that a Gaussian X channel can be considered as a superposition of two Gaussian interference channels based on grouping of the sent messages from each transmitter to the corresponding receivers. Finally, we give an achievable rate region for the general case of this channel.

A novel compact multi-input multi-output (MIMO) antenna system with split-ring resonator (SRR), a popular metamaterial structure, is presented. The MIMO antenna system consists of SRRs as radiator elements arranged close to each other on a printed circuit board. We evaluate the antenna characteristics with a single and two SRR elements arranged within various sizes of area. We also analyze MIMO channel capacities of SRR elements by using radiation patterns. The obtained results confirm that the proposed MIMO antenna system can achieve the same channel capacity as a conventional MIMO antenna system but with a 30% smaller footprint area and is very suitable for compact wireless equipment in next-generation wireless systems.

A simple but efficient method for evaluating the channel capacity of 2×2 multiple-input multiple-output (MIMO) antenna systems is proposed. First, the channel capacity of a half-wavelength dipole array antenna is calculated using the Monte Carlo method by changing the incident-wave signal-to-noise power ratio, the power difference between two elements, and the correlation coefficient. Using the calculated results, a polynomial function is derived by multivariate regression analysis to estimate the channel capacity. The validity of the developed function is confirmed by comparing the channel capacity estimated by the developed function with that calculated by the Monte Carlo method using a MIMO array antenna operated under various scenarios, including antenna-human body electromagnetic interactions and radio-wave propagation environments, for future MIMO systems. The function is also validated by means of two experimental approaches: the use of radiation patterns measured in an anechoic chamber and the use of a spatial fading emulator that can create a two-dimensional fading environment.

An interference-aware dynamic channel assignment scheme is proposed with consideration of co-tier interference for the downlink of an OFDMA/FDD based dense small-cell network. The proposed scheme adaptively assigns subchannels to the small-cell user equipment (SUE) according to the given traffic load and interference effect from neighbor small-cell access points. The simulation results show that the proposed scheme outperforms the other schemes based on the graph coloring algorithm in terms of the mean SUE capacity.

This paper proposes a dynamic spectrum controlled (DSTC) channel allocation algorithm to increase the total throughput of satellite communication (SATCOM) systems. To effectively use satellite resources such as the satellite's maximum transponder bandwidth and maximum transmission power and to handle the propagation gain variation at all earth stations, the DSTC algorithm uses two new transmission techniques: spectrum compression and spectrum division. The algorithm controls various transmission parameters, such as the spectrum compression ratio, number of spectrum divisions, combination of modulation method and FEC coding rate (MODCOD), transmission power, and spectrum bandwidth to ensure a constant transmission bit rate under variable propagation conditions. Simulation results show that the DSTC algorithm achieves up to 1.6 times higher throughput than a simple MODCOD-based algorithm.

In this paper, we study the achievable degrees of freedom (DoF) of a multiple-input multiple-output (MIMO) multi-way relay channel with asymmetric message set that models the scenario of the two-way communication between a base station and multiple users through a relay. Under the assumption of delayed channel state information at transmitters (CSIT), we propose an amplify-and-forward relaying scheme based on the scheme proposed by Maddah-Ali and Tse to support signal space alignment, so that the available dimensions of the signal spaces at the relay and the users can be efficiently utilized. The proposed scheme outperforms the traditional one-way scheme from the perspective of DoF, and is useful to relieve the communication bottleneck caused by the asymmetric traffic load inherent in cellular networks.

In this paper, we propose two secure multiuser multiple-input multiple-output (MIMO) transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To deal with the information leakage to the eavesdropper as well as the interference signals from undesired transmitters (Txs) at desired receivers (Rxs), our approaches aim to design the transmit precoding and receive subspace matrices to minimize both the total inter-main-link interference and the wiretapped signals (WSs). The first proposed IA scheme focuses on aligning the WSs into proper subspaces while the second one imposes a new structure on the precoding matrices to force the WSs to zero. In each proposed IA scheme, the precoding matrices and the receive subspaces at the legitimate users are alternatively selected to minimize the cost function of a convex optimization problem for every iteration. We provide the feasible conditions and the proofs of convergence for both IA approaches. The simulation results indicate that our two IA approaches outperform the conventional IA algorithm in terms of the average secrecy sum rate.

In this paper, we study the degrees of freedom (DoF) of a multiple-input multiple-output (MIMO) multiway relay channel (mRC) with two relays, two clusters and K (K≥3) users per cluster. We consider a clustered full data exchange model, i.e., each user in a cluster sends a multicast (common) message to all other users in the same cluster and desires to acquire all messages from them. The DoF results of the mRC with the single relay have been reported. However, the DoF achievability of the mRC with multiple relays is still an open problem. Furthermore, we consider a more practical scenario where no channel state information at the transmitter (CSIT) is available to each user. We first give a DoF cut-set upper bound of the considered mRC. Then, we propose a distributed interference neutralization and retransmission scheme (DINR) to approach the DoF cut-set upper bound. In the absence of user cooperation, this method focuses on the beamforming matrix design at each relay. By investigating channel state information (CSI) acquisition, we show that the DINR scheme can be performed by distributed processing. Theoretical analyses and numerical simulations show that the DoF cut-set upper bound can be attained by the DINR scheme. It is shown that the DINR scheme can provide significant DoF gain over the conventional time division multiple access (TDMA) scheme. In addition, we show that the DINR scheme is superior to the existing single relay schemes for the considered mRC.

In this letter, a novel and highly efficient haze removal algorithm is proposed for haze removal from only a single input image. The proposed algorithm is built on the atmospheric scattering model. Firstly, global atmospheric light is estimated and coarse atmospheric veil is inferred based on statistics of dark channel prior. Secondly, the coarser atmospheric veil is refined by using a fast Tri-Gaussian filter based on human retina property. To avoid halo artefacts, we then redefine the scene albedo. Finally, the haze-free image is derived by inverting the atmospheric scattering model. Results on some challenging foggy images demonstrate that the proposed method can not only improve the contrast and visibility of the restored image but also expedite the process.

One of the major subjects for marine resources development and information processing is how to realize underwater short-range and large-capacity data transmissions. The acoustic wave is an effective carrier and has been used for underwater data transmissions because it has lower attenuation in seawater than the radio wave, and has average propagation distance of about 10km or more. However, along with the imaging of transmission data, the inherent low speed of the acoustic wave makes it cannot and become an ideal carrier for high-speed and large-capacity communications. On the other hand, visible-light wave with wavelength of 400nm-650nm is an ideal carrier, which has received much attention. Its attractive features are high transparency and low attenuation rate in underwater, easily control the propagation direction and range by the visibility, and high data rate and capacity, making it excellent for application in underwater wireless communications. However, visible-light waves in the seawater have the spectral attenuation characteristics due to different marine environment. Therefore, in this paper an underwater optical wireless communication method with adaptation seawater function is considered for seawater turbidity of the spatio-temporal change. Two crucial components in the underwater optical wireless communication system, the light wavelength and the modulation method are controlled using wavelength- and modulation-adaptation techniques, respectively. The effectiveness of the method of the adaptation wavelength is demonstrated in underwater optical image transmissions.

It is necessary to estimate channel state information coherently to equalize the received signal in wireless communication systems. The pilot symbol, known at the receiver, aided channel estimator degrades the transmission efficiency because it requires the signal spaces and the energy for the transmission. In this paper, we assume a fixed wireless communication system in line of sight slowly varying channel and propose a new blind channel estimation method without help from the pilot symbol for Orthogonal Frequency Division Multiplexing systems. The proposed estimator makes use of the Expectation-Maximization algorithm and the correlation property among the channel frequency responses by considering the assumed channel environment. By computer simulations, we show that the proposed estimator can asymptotically achieve bit error rate performance by using the ideal channel estimation.

This paper explores the feasibility of power analysis attacks against low-latency block ciphers implemented with unrolled architectures capable of encryption/decryption in a single clock cycle. Unrolled architectures have been expected to be somewhat resistant against side-channel attacks compared to typical loop architectures because of no memory (i.e. register) element storing intermediate results in a synchronous manner. In this paper, we present a systematic method for selecting Points-of-Interest for power analysis on unrolled architectures as well as calculating dynamic power consumption at a target function. Then, we apply the proposed method to PRINCE, which is known as one of the most efficient low-latency ciphers, and evaluate its validity with an experiment using a set of unrolled PRINCE processors implemented on an FPGA. Finally, a countermeasure against such analysis is discussed.

Mutipath matching pursuit (MMP) is a new reconstruction algorithm based on compressed sensing (CS). In this letter, we applied the MMP algorithm to channel estimation in orthogonal frequency division multiplexing (OFDM) communication systems, and then proposed an improved MMP algorithm. The improved method adjusted the number of children generated by candidates. It can greatly reduce the complexity. The simulation results demonstrate that the improved method can reduce the running time under the premise of guaranteeing the performance of channel estimation.

Due to outsourcing of numerous stages of the IC manufacturing process to different foundries, the security risk, such as hardware Trojan becomes a potential threat. In this paper, we present a layout aware localized hardware Trojan detection method that magnifies the detection sensitivity for small Trojan in power-based side-channel analysis. A scan segmentation approach with a modified launch-on-capture (LoC) transition delay fault test pattern application technique is proposed so as to maximize the dynamic power consumption of any target region. The new architecture allows activating any target region and keeping others quiet, which reduces total circuit toggling activity. We evaluate our approach on ISCAS89 benchmark and two practical circuits to demonstrate its effectiveness in side-channel analysis.

In this paper, we investigate the problem of maximizing the weighted sum outage rate in multiuser multiple-input single-output (MISO) interference channels, where the transmitters have no knowledge of the exact values of channel coefficients, only the statistical information. Unfortunately, this problem is nonconvex and very difficult to deal with. We propose a new, provably convergent iterative algorithm where in each iteration, the original problem is approximated as second-order cone programming (SOCP) by introducing slack variables and using convex approximation. Simulation results show that the proposed SOCP algorithm converges in a few steps, and yields a better performance gain with a lower computational complexity than existing algorithms.

In this paper, we discuss an algebraic decoding of BCH codes over symbol-pair read channels. The channels output overlapping pairs of symbols in storage applications. The pair distance and pair error are used in the channels. We define a polynomial that represents the positions of the pair errors as the error-locator polynomials and a polynomial that represents the positions of the pairs of a received pair vector in conflict as conflict-locator polynomial. In this paper, we propose algebraic methods for correcting two-pair and three-pair errors for BCH codes. First, we show the relation between the error-locator polynomials and the conflict-locator polynomial. Second, we show the relation among these polynomials and the syndromes. Finally, we provide how to correct the pair errors by solving equations including the relational expression by algebraic methods.

Reliable wireless communication often requires accurate knowledge of the underlying multipath channels. Numerous measurement campaigns have shown that physical multipath channels tend to exhibit a sparse structure. Conventional blind channel identification (BCI) strategies such as the least squares, which are known to be optimal under the assumption of rich multipath channels, are ill-suited to exploiting the inherent sparse nature of multipath channels. Recently, l1-norm regularized least-squares-type approaches have been proposed to address this problem with a single parameter governing all coefficients, which is equivalent to maximum a posteriori probability estimation with a Laplacian prior for the channel coefficients. Since Laplace prior is not conjugate to the Gaussian likelihood, no closed form of Bayesian inference is possible. Following a different approach, this paper deals with blind channel identification of a single-input multiple-output (SIMO) system based on sparse Bayesian learning (SBL). The inherent sparse nature of wireless multipath channels is exploited by incorporating a transformative cross relation formulation into a general Bayesian framework, in which the filter coefficients are governed by independent scalar parameters. A fast iterative Bayesian inference method is then applied to the proposed model for obtaining sparse solutions, which completely eliminates the need for computationally costly parameter fine tuning, which is necessary in the l1-norm regularization method. Simulation results are provided to demonstrate the superior effectiveness of the proposed channel estimation algorithm over the conventional least squares (LS) scheme as well as the l1-norm regularization method. It is shown that the proposed algorithm exhibits superior estimation performance compared to both LS and l1-norm regularization methods.