Simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) introduces revolutionary capabilities by reaching full space coverage for wireless signals, significantly enhancing the efficiency and reliability of Internet of Things (IoT) networks compared to traditional RIS. In this article, we propose a novel framework that leverages STAR-RIS into wirelessly powered federated learning (FL) networks with a multiantenna access point, aiming to minimize system latency. A multivariable nonconvex optimization problem is formulated to optimize phase shift vectors of STAR-RIS, beamforming matrices, time, power, and computation frequency for each user in all phases of FL. Block coordinate descent (BCD) over the combination of an 1-D search algorithm and interior point method is employed to optimize time, power, computation frequency, phase shift vectors of STAR-RIS, and active beamforming matrix in the uplink transmission phase, while semi-definite relaxation via BCD addresses phase shift vectors of STAR-RIS and beamforming matrices optimization in harvesting and downlink transmission phases. On this basis, the optimized downlink transmission time and power are derived. The convergence of the proposed algorithm and the superiority of its performance compared to benchmark schemes are validated through comprehensive simulations. Our findings indicate the potential of FL, multiantenna aggregation server, and STAR-RIS in ushering in a new era of intelligent and efficient IoT networks.

The transceiver design for multi-hop multiple-input multiple-output (MIMO) relay is very challenging, and for a large scale network, it is not economical to send the signal through all possible links. Instead, we can find the best path from source-to-destination that gives the highest end-to-end signal-to-noise ratio (SNR). In this paper, we provide a linear minimum mean squared error (MMSE) based multi-hop multi-terminal MIMO non-regenerative half-duplex amplify-and-forward (AF) parallel relay design for a wireless sensor network (WSN) in an underground mines. The transceiver design of such a network becomes very complex. We can simplify a complex multi-terminal parallel relay system into a series of links using selection relaying, where transmission from the source to the relay, relay to relay, and finally relay to the destination will take place using the best relay that provides the best link performance among others. The best relay selection using the traditional technique in our case is not easy, and we need a strategy to find the best path from a large number of hidden paths. We first find the set of simplified series multi-hop MIMO best relays from source to destination using the optimum path selection technique found in the literature. Then we develop a joint optimum design of the source precoder, the relay amplifier, and the receiver matrices using the full channel diagonalizing technique followed by the Lagrange strong duality principle with known channel state information (CSI). Finally, simulation results show an excellent agreement with numerical analysis demonstrating the effectiveness of the proposed framework.

With the massive deployment of Internet of Things (IoT) devices in sixth-generation networks, several critical challenges have emerged, such as large communication overhead, coverage limitations, and limited battery lifespan due to high energy consumption. Federated learning (FL), wireless power transfer (WPT), multi-antenna access point (AP), and reconfigurable intelligent surfaces (RIS) can mitigate these challenges by reducing the need for large data transmissions, enabling sustainable energy harvesting, and optimizing the propagation environment. Compared to conventional RIS, simultaneously transmitting and reflecting (STAR)-RIS not only extends coverage from half-space to full-space but also improves energy saving through appropriate mode selection. Motivated by the need for sustainable, low-latency, and energy-efficient communication in large-scale IoT networks, this paper investigates the efficient STAR-RIS mode in the uplink and downlink phases of a WPT-FL multi-antenna AP network with non-orthogonal multiple access to minimize energy consumption, a joint optimization that remains largely unexplored in existing works on RIS or STAR-RIS. We formulate a non-convex energy minimization problem for different STAR-RIS modes, i.e., energy splitting (ES) and time switching (TS), in both uplink and downlink transmission phases, where STAR-RIS phase shift vectors, beamforming matrices, time and power for harvesting, uplink transmission, and downlink transmission, local processing time, and computation frequency for each user are jointly optimized. To tackle the non-convexity, the problem is decoupled into two subproblems: the first subproblem optimizes STAR-RIS phase shift vectors and beamforming matrices across all WPT-FL phases using block coordinate descent over either semi-definite programming or Rayleigh quotient problems, while the second one allocates time, power, and computation frequency via the one-dimensional search algorithms or the bisection algorithm. Simulation results demonstrate that TS STAR-RIS in both uplink and downlink transmissions achieves the lowest energy consumption, outperforming ES and conventional RIS schemes due to its flexible phase shift adaptation and lower interference levels.

This paper considers the scenario where multiple Internet-of-Things (IoT) devices collaborate to train a distributed model using federated learning. Wireless power transfer (WPT) is employed to address the issue of limited battery life of IoT devices, while non-orthogonal multiple access (NOMA) is utilized to facilitate data transmission. Besides, an intelligent reflecting surface (IRS) is applied to assist both energy transfer and data transmission. On this basis, a joint resource allocation problem is formulated to minimize the total energy consumption for the considered IRS-aided FL-WPT networks with NOMA. The non-convex problem is first solved by developing a combination of semi-definite programming relaxation (SDR) with a two-dimensional search algorithm. To lower the computational complexity, SDR with a bisection algorithm is further employed by exploiting the inherent structure of the formulated problem. Numerical results not only validate the equivalence of these two algorithms in performance but also unequivocally establish the superior efficiency of the proposed method over benchmark schemes in terms of energy consumption.

System-on-chip (SoC) field programmable gate array (FPGA) devices are becoming increasingly prominent in a vast range of applications. The fusion of the FPGA’s unmatched parallel computing capacity and flexibility with a full-bore processing system makes these devices extremely powerful. With recent technological progress, SoC FPGA devices are implemented in increasingly complex systems where security and safety are often issues of concern. To cater to these concerns, these devices are commonly fit with encryption and authentication capabilities to ensure the confidentiality and authenticity of externally stored bitstreams, firmware, and bootloaders. However, while much effort is placed into securing these partitions when stored in external memory, little attention seems to be paid to the security of this data once it is decrypted for execution. This article investigates how vulnerable systems are to attacks that target decrypted data during execution. We demonstrate that data stored in external synchronous dynamic random access memory (SDRAM) can provide access to trusted and secured interfaces of SoC FPGA devices even with diligently applied security features.

Hardware-in-the-Loop (HIL) simulators play a critical role in the automotive industry by providing extensive testing and validation capabilities for electronic control units (ECUs). One of the main challenges faced by HIL simulators involves the task of constructing a virtual environment that accurately replicate the behavior of the actual system. Artificial intelligence (AI) algorithms can be useful in generating precise virtual environments for HIL simulations of complex systems. Moreover, minimal latency is essential for establishing a reliable virtual environment. FPGA (Field Programmable Gate Array) can effectively reduce latency in HIL simulations by providing high-performance computing resources. This paper aims to address these challenge by introducing a machine learning-driven HIL simulator implemented on FPGA. The proposed architecture employs FPGA technology to enhance the computational speed of a temporal convolutional neural network (TCN).

Federated learning (FL) has been envisioned as a promising distributed learning framework for next-generation wireless communication systems. FL introduces new challenges in system design, since users need to consider the local processing optimization in addition to traditional communication resources allocation. In this paper, we aim to address this challenge by considering a wireless-powered FL network with multiple users, where non-orthogonal multiple access (NOMA) is employed for uplink transmission. A latency minimization problem is formulated, requiring to jointly optimize the power and time allocation for all FL phases together with the local processing computation frequency at each user. An one-dimensional search algorithm (ODSA) is proposed to obtain the optimal solution for the formulated non-convex problem. Presented numerical results demonstrate that the proposed scheme outperforms its orthogonal counterpart.

This article presents a critical literature review on the security aspects of field-programmable gate array (FPGA) devices. FPGA devices present unique challenges to cybersecurity through their reconfigurable nature. The article also pays special attention to emerging system-on-chip (SoC) FPGA devices that incorporate a hard processing system (HPS) on the same die as the FPGA logic. While this incorporation reduces the need for vulnerable external signals, the HPS in SoC FPGA devices adds a level of complexity that is not present for stand-alone FPGA devices. This added complexity necessarily hands over the task of securing the device to developers. Even with standard security features in place, the HPS might still have unhindered access to the FPGA logic. A single software flaw could open up a breach that might allow an attacker to extract the FPGA’s configuration data. A robust cybersecurity strategy is thus required for developers. As such, this work aims to provide the groundwork to build a solid threat-based cybersecurity design strategy that is specially adapted to SoC FPGA devices.

Abstract This paper analyzes the error probability performance of low‐density parity‐check (LDPC) coded generalized frequency division multiplexing (GFDM) systems over Rayleigh fading and additive white Gaussian noise (AWGN) channels. The initial log‐likelihood ratio (LLR) expressions used in the sum‐product algorithm (SPA) decoder are first derived for the system model presented in this paper. Based on the decoding threshold of the system, the frame error rate (FER) in the low region is estimated by modeling the channel variations using the observed bit error rate (BER). Then, a lower bound based on the absorbing sets is proposed for FER when quantized SPA decoders are used. For AWGN channels, the lower bound can act as an estimate of the FER in the error‐floor region if the absorbing set is dominant and its multiplicity is known. For Rayleigh channels, the lower bound can still be used to estimate the FER performance of selected codes. The estimation approach for the FER in the low region and the lower bound on the FER in the high region can be used as practical tools for evaluating different designs of GFDM‐based systems in terms of the error probability performance. The quantization scheme has an important impact on the FER and BER performances. Randomly constructed and array‐based LDPC codes are used to obtain numerical results that show the system performance and the accuracy of the proposed FER estimations.

Fingerprinting (FP) localization methods are used in massive multiple-input multiple-output (MIMO) systems due to their high reliability and accuracy. The Gaussian process regression (GPR) method could potentially be used, as an FP-based localization method, in a massive MIMO system to provide high accuracy. However, it is limited by high complexity, especially in a large-scale environment. In this paper, we propose an FP-based localization method, using affinity propagation (AP) clustering and Gaussian process regression (GPR) to estimate user's location in a distributed massive MIMO system based on the uplink received signal strength (RSS) vectors. First, the training RSS vectors are clustered using the AP algorithm to reduce the computational complexity. Then, the data distribution within each cluster is accurately modeled using GPR to provide excellent support for further positioning. Simulation studies reveal that the proposed method improves root-mean-squared estimation error (RMSE) performance significantly by reducing the location estimation error compared to using only GPR for all training RSS data. Also, it reduces the computational complexity of using GPR.

The mining industry has been acting as a leader in the development of fully autonomous vehicles. Mining equipment manufacturers have been developing and testing autonomous vehicle technologies for many years. There are many ongoing innovations in autonomous vehicle technology. One of these is the Dedicated Short Range Communications (DSRC). The DSRC is a one-way or two-way short-to-medium-range wireless communications capability. In this paper, we present a review of the DSRC large-scale fading channel at 5.9 GHz in the tunnels and underground mines. The requirements for DSRC receiver performance for VANET- Vehicular Ad-hoc Networks applications in an underground mine is calculated. This paper also reports the overall performance evaluation of three existing routing protocols, namely, Emergency Message Dissemination for Vehicular Environments (EMDV), Enhanced Multi-Hop Vehicular Broadcast (MHVB), and Efficient Directional Broadcast (EDB) for active safety applications. Finally, a comparative study of these three routing protocols for cooperative collision warning in underground mining galleries was evaluated.

In this paper, we propose a local search based detector for cooperative diversity systems. The considered system involves one source, one destination and multiple single-antenna relays. It adopts the decode and forward (DF) protocol where relays could commit errors in decoding the data. At the destination, we propose a detector based on the likelihood ascent search (LAS) approach. It is well known that LAS algorithm requires a maximum likelihood (ML) decoding metric that will be improved from one iteration to another to refine the solution. The main contribution of this work consists in providing a closed-form expression for the aforementioned ML decoding metric. We prove that the proposed detector dramatically reduces the computational complexity compared with the ML detector. However, numerical results show that, for PAM constellations, the proposed scheme has the same performance as the ML detector, and for QAM and PSK constellations, it has near ML performances.

Localization has been a notable feature in wireless communications due to the increasing demand for location information. Fingerprinting-based (FP) localization methods are promising for rich scattering environments due to their high reliability and accuracy. The Gaussian process regression (GPR) method could potentially be used as an FP-based localization method to facilitate localization and provide high accuracy. However, it is limited by high complexity, especially in a large-scale environment. In this paper, we propose an FP-based localization method in collocated massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems using the affinity propagation clustering (APC) algorithm and Gaussian process regression (GPR) to estimate the user’s location. Fingerprints are extracted based on instantaneous channel state information (CSI) by taking full advantage of the high resolution in the angle and delay domains. Then, the training fingerprints are clustered using the (APC) algorithm to reduce matching complexity and computational complexity. Finally, the data distribution within each cluster is accurately modeled using GPR to provide excellent support for further localization. Simulation studies reveal that the proposed method improves localization performance significantly by reducing the location estimation error. Additionally, it reduces the matching complexity and computational complexity.

In an asynchronous environment, optical code division multiple access (OCDMA) is an advanced technique. However, this technique shows limitations in terms of the low spectral density and inefficient bandwidth utilization when implemented with one-dimensional (1D) codes. Thus, this study presented a novel two dimensional (2D) spectral/spatial multi-wavelength code to overcome these limitations. The proposed code is formulated using a 1D balanced incomplete block design (BIBD) technique. It is designed and implemented for spectral amplitude coding (SAC) based OCDMA networks and constructed using a 1D BIBD code matrix. Optisystem software-based simulation results indicate that the proposed code provided improvement in the number of simultaneous users, code construction, cross-correlation, and minimize the noises. Due to its practical code design approach, the proposed code family yields large cardinality with optimal code length. Moreover, system performance illustrates that the system with the proposed code maintains required optical transmission property by supporting six clients for source power -10 dBm with the data transmission rate of 1 Gbps.

In this paper, low-complexity channel estimators are proposed for massive multiple-input multiple-output generalized frequency division multiplexing (MIMO-GFDM) systems. In order to combat the effect of non-orthogonality in GFDM, interference-free pilots are used in frequency-domain minimum mean square error (MMSE) channel estimation. Polynomial expansion is used to approximately compute the matrix inverse in conventional MMSE estimation, consequently reducing the cubic computational complexity to square order. The degree of the matrix polynomial can be properly selected to get a required trade-off between complexity and estimation performance. Different weights can be assigned to the terms in the polynomial expansion and be optimized to achieve a minimal mean square error (MSE). Performance limits on the MSE of the proposed estimators are derived. The computational complexity of the proposed MMSE estimators is analyzed and the impacts of the polynomial degree and the pilot subcarrier spacing are also investigated. Numerical results show the accuracy of the proposed channel estimators.

Likelihood ascent search (LAS) detector is a neighbourhood search algorithm and one of the simplest schemes for low‐complexity near‐optimal detection in massive multiple‐input multiple‐output systems. LAS detector design under the assumption of perfect channel state information has been an area of research for decades. However, channel estimation errors have never been taken into account by conventional LAS detectors when calculating the maximum‐likelihood decoding metric. As a result, the bit error rate performance of LAS detectors can be significantly degraded. This study proposes robust LAS detectors which take channel estimation errors into account in the computation of the ML decoding metric. The proposed approach involves the computation of the equivalent noise covariance matrix inverse, which may increases the computational complexity. Therefore, the authors also propose a low complexity method to inverse the covariance matrix. Simulation results show that the proposed schemes outperform the conventional LAS detector.

Almost all existing channel estimation schemes, for multi-user multiple-input multiple-output (MU-MIMO) systems, were designed based on a fixed and known number of active users. However, in random access MU-MIMO systems, some users may be inactive and the estimation techniques designed with the assumption that all users are available may lead to performance losses. In this paper, we consider the popular least squares (LS) and linear minimum mean square error (LMMSE) estimations approaches. For such techniques, when the number of users varies, the channel estimation filter coefficients must be re-derived. The fundamental problem of interest here is to reduce the computational complexity of the LS and LMMSE channel estimation methods when some users are inactive. For each techniques, we propose an estimation approach with a low complexity and without performance loss. The proposed algorithms avoid the direct computation of matrix inverses required by the LS and LMMSE methods. Moreover, the mean square error (MSE) losses, due to the use of the LS and LMMSE estimator intended for the scenario without inactive users, are evaluated and compared with Monte-Carlo simulations results.

This paper presents an FPGA implementation of a DNA assembly algorithm, called Ray, initially developed to run on parallel CPUs. The OpenCL language is used and the focus is placed on modifying and optimizing the original algorithm to better suit the new parallelization tool and the radically different hardware architecture. The results show that the execution time is roughly one fourth that of the CPU and factoring energy consumption yields a tenfold savings.

The impact of feedback errors on the security performances of multiple-input multiple-output (MIMO) wiretap channels is analyzed. For the legitimate MIMO system, two schemes are considered: 1) transmit antenna selection/maximal ratio combining (TAS/MRC) and 2) transmit antenna selection/receive antenna selection (TAS/RAS). The eavesdropper uses either MRC or RAS techniques. We derive closed-form expressions for the exact secrecy outage probability (SOP) and the probability of strictly positive secrecy capacity (PSPSC). In order to obtain the secrecy diversity order and the secrecy array gain, on asymptotic SOP expression is also derived.

This study analyses the physical layer security in the wiretap channel for multiple‐input–multiple‐output transmit‐beamforming (TB) systems with maximal ratio combining (MRC) receivers. The TB is designed to maximise the signal‐to‐noise ratio (SNR) at the main receiver output. The authors assume that both legitimate and eavesdropper receivers have the knowledge of their own channel state information (CSI). Furthermore, they consider that the transmitter has the full CSI of the main channel and does not have the CSI of the eavesdropper's channel. At the eavesdropper, two combining methods are considered: (i) MRC technique and (ii) selection combining method. They derive closed‐form expressions for the exact secrecy outage probability (SOP) and the probability of strictly positive secrecy capacity. Expressions of the asymptotic SOP and the asymptotic ε ‐outage secrecy capacity are also derived. The secrecy diversity order and the secrecy SNR gain are then obtained.

We investigate the performances of MIMO channel, signal-to-noise ratio (SNR) and noise covariance estimation in the presence of correlated noise. The Cramer-Rao lower bounds (CRLBs) for the estimated parameters are evaluated. The CRLB of the channel matrix estimation is minimized with respect to the training sequence. When the noise covariance matrix is available, the minimum variance and unbiased estimator (MVUE) of the channel matrix corresponds to the generalized least squares (GLS) estimator. When the covariance matrix is unknown, we propose to use the feasible generalized least squares (FGLS) technique. We prove that this two-step procedure is asymptotically equivalent to the GLS algorithm. The analytic analysis is confirmed by Monte Carlo simulations.

Ultra-wideband (UWB) has attracted a lot of attention in the past few years. UWB offers several advantages over traditional narrow band. Transmitted reference (TR) receivers have been known for many decades, but there is a renewed interest for applications of TR receivers as a suboptimal solution for UWB communications because of the difficulty in estimating the channel accurately for an optimal solution. In this paper, the performance of a UWB-TR receiver in an UWB underground mine channel is evaluated. The performance at higher data rates in the case of inter-symbol interference (ISI) is also investigated.

This paper analyzes an adaptive modulation scheme for precoded multiple-input multiple-output MIMO systems with minimum-mean-squared-error decision feedback equalizer. The MIMO channel is assumed to be spatially correlated with multipath Rayleigh fading. The zero-padding technique is used to eliminate the inter-block interference. To adjust the constellation size, the signal-to-interference-plus-noise (SINR) ratio at the equalizer output is sent back to the transmitter. In this paper, we derive the probability density function of the SINR for flat fading and frequency selective channels. Then, we present accurate closed-form expressions of the spectral efficiency and the average BER. The derived expressions are compared to simulation results.

In this paper, a code division multiple access (CDMA) enabled dynamic bandwidth allocation (CDBA) algorithm is proposed for the upstream access scheme for Ethernet passive optical networks (EPON). The CDBA algorithm is based on two major components: The first is the parallel transmission capacity offered by CDMA according to the quality of service (QoS) requirement and the second component is the scheduling algorithm which uses the round robin technique. Extensive simulations have been performed in order to compare the proposed CDBA with existing dynamic bandwidth allocation (DBA) algorithms that achieve good bandwidth utilization by use of polling schemes. It is shown that the CDBA can significantly improve the network performance in terms of packet delay, throughput, and queue size management as compared with the well known IPACT algorithm.

This study addresses the problem of resource allocation for a multi-class time-slotted optical overlapped code-division multiple access network. A delay-constraint fair resource allocation (DC-FRA) scheme is considered with the quality of service requirements on both physical layer signal-to-interference ratio and network layer average packet delay. A cross-layer approach in allocating the transmission power and rate for every class of users in the network is considered. The performances of the S-ALOHA, R-ALOHA and R3T medium access control protocols have been investigated in the DC-FRA scheme. It is shown that the R-ALOHA protocol has the highest throughput and the minimum average packet delay. On the other hand, although the DC-FRA allocates the largest bandwidth under the R-ALOHA protocol, it forces the users to transmit with relatively higher power in comparison with the power required for the S-ALOHA and the R3T protocols. In addition, the packets exhibit much smaller delay when using the DC-FRA, especially at low and moderate throughput for the three protocols.

A baseband multi-input, multi-output (MIMO) multi-carrier code division multiple access (MC-CDMA) downlink system meeting wideband CDMA (WCDMA) bandwidth requirements is simulated and its receiver part is implemented into a field programmable gate array (FPGA). The receiver was designed by integrating an existing single-input, single-output (SISO) fixed-point MC-CDMA receiver with an existing floating-point MIMO receiver. The receiver employs temporal multiplexing in order to use a single Vertical Bell Laboratories LAyered Space-Time (V-BLAST) detector. Simulation results of a complete MIMO MC-CDMA system show improvements over the SISO case. Implementation results show that it is possible to implement this receiver design into a single FPGA device.

In this work we develop a fair resource allocation scheme for a multi-class time-slotted optical overlapped code- division multiple-access (OV-CDMA) network. The resource management scheme is fair in the sense that the users have their power and rate allotted according to their quality of service (QoS) requirements. In addition, no class of users can dominate over the other classes. A unified framework is proposed, which consists of finding a single control parameter based on which the optimal transmission rate and power are obtained for every class of users. Analytical results show that the maximum transmission rate for a given class of users is only achievable when the users in that class are transmitting with the highest possible laser transmission power. In addition, we have demonstrated that the optimal transmission rates can be obtained via the solution of the rate characteristic polynomial.

We propose a new semi-analytic method for the study of the performance of a RAKE receiver in a direct-sequence code-division multiple-access (DS-CDMA) based ultra wideband (UWB) system. This method is intended as a tool to facilitate further performance studies of this type of system and, ultimately, to lead to a fully analytical model. We also analyze system performance, in the presence of intersymbol interference (ISI) and narrowband interference (NBI), using two RAKE-based receivers. The first receiver is the classical RAKE, which employs maximal ratio combining (MRC). In the second receiver, MRC combining is replaced by linear minimum mean-squared error (MMSE) combining.

Underground mine galleries can be considered as complex transmission lines where multipath, attenuation, reflection, diffraction and scattering effects are dominants. However, some companies have started to deploy modern wireless system networks in mine galleries with the objective of increasing safety and productivity. In the last decade, ultra-wideband (UWB) technology has gained much interest for its application to wireless communications. This paper reports on experimental results of UWB channel propagation in an underground mine. Eigen-decomposition and subspace-based statistical signal processing on the autocorrelation matrix of the channel impulse response are used. We apply information theoretic criteria to estimate the number of significant eigenvalues. This result is then used to calculate the RMS delay spread of the channel.

Low-density parity-check codes using the belief-propagation decoding algorithm tend to exhibit a high error floor in the bit error rate curves, when some problematic graphical structures, such as the so-called trapping sets, exist in the corresponding Tanner graph. This paper presents a joint row-column decoding algorithm to lower the error floor, in which the column processing is combined with the processing of each row. By gradually updating the pseudo-posterior probabilities of all bit nodes, the proposed algorithm minimizes the propagation of erroneous information from trapping sets into the whole graph. The simulation indicates that the proposed joint decoding algorithm improves the performance in the waterfall region and lowers the error floor. Implementation results into field programmable gate array (FPGA) devices indicate that the proposed joint decoder increases the decoding speed by a factor of eight, compared to the traditional decoder.

This paper addresses the problem of resource allocation in a multiservice optical network based on an overlapped-CDMA system. A joint transmission power and overlapping coefficient (transmission rate) allocation strategy is provided via the solution of a constrained convex quadratic optimization problem. The solution to this problem maximizes the aggregate throughput subject to peak lasers transmission power constraints. The optimization problem is solved in a closed form, and the resource allocation strategy is simple to implement in an optical network. Results are presented showing a total agreement between the derived analytical solution and the one obtained using a numerical search method. In addition, analytical and numerical results show that the proposed resource allocation strategy can offer substantial improvement in the system throughput.

This paper presents a joint row-column decoding algorithm for the decoding of low-density parity-check (LDPC) codes. Simulation indicates that the proposed algorithm improves the performance in both the waterfall region and the error floor region. By combining row processing with column processing, the joint row-column decoding algorithm reduces the storage requirements of extrinsic messages and avoids memory conflicts and routing congestion during the exchanges of extrinsic messages. Implementation results into field programmable gate array (FPGA) devices indicate that the proposed algorithm reduces the hardware costs by 30% and increases the decoding speed by a factor of four. A 40-parallel decoder attains a throughput of 2 Gbits/sec by using up to 20 % of the generic logic resources in a Xilinx XC4LX160 device

The necessity for wireless communications in underground mines is well understood. Some companies have started to deploy modern wireless system networks in mine galleries with the objective of increasing safety and productivity. In the last decade, ultra-wideband (UWB) technology has gained much interest for its applications in wireless communications. A number of UWB channel measurement have been published in the literature. However, all these works treated environments such as office buildings, residential or industrial. This paper reports on experimental results of UWB channel characterization in underground mines. The communication channel is still not well modelled in these environments. Important channel parameters such as path loss exponent, shadow fading, spatial correlation, small-scale fading, RMS delay spread and mean excess delay are investigated. This work has been carried out at the underground communications research laboratory LRCS, and at the experimental mine CANMET (Canadian Center for Minerals and Energy Technology) in Val-d'Or, Canada.

This paper discusses the design of a high-speed encoder for low density parity check (LDPC) codes. To minimize hardware costs and memory requirements of such encoders, a class of high-performance quasi-cyclic LDPC codes which can be encoded in linear time has been proposed by designing the parity check matrix in a triangular plus dual-diagonal form. Based on the proposed codes, parallel architectures and pipelining technology have been used to increase the throughput of encoders. Moreover, collisions which occur when parallel processors contend for write access to the same memory module are avoided by exploiting an iterative encoding approach which involves repeated usage of the processors. The implementation results into field programmable gate array (FPGA) devices indicate that the encoder for the LDPC code with a block length of 2048 and a code rate of 0.5 attains a throughput of 12.8 Gbit/s using 352 exclusive-OR gates.

A procedure of measurement and analysis for the UWB channel in underground mines is presented. The measured data is saved in the frequency-domain via a vector network analyzer (VNA). We first compare two methods for the analysis of the path loss dependence on frequency. Then, we present results from an autoregressive modeling technique. We show that a two pole model is sufficient to represent the characteristics of the UWB channel in underground mines. This work was carried out by the underground communications research laboratory LRCS1, and the CANMET (Canadian Center for Minerals and Energy Technology) experimental mine in Val-d'Or, Canada.

Highly parallel decoders for convolutional turbo codes have been studied by proposing two parallel decoding architectures and a design approach of parallel interleavers. To solve the memory conflict problem of extrinsic information in a parallel decoder, a block-like approach in which data is written row-by-row and read diagonal-wise is proposed for designing collision-free parallel interleavers. Furthermore, a warm-up-free parallel sliding window architecture is proposed for long turbo codes to maximize the decoding speeds of parallel decoders. The proposed architecture increases decoding speed by 6%-34% at a cost of a storage increase of 1% for an eight-parallel decoder. For short turbo codes (e.g., length of 512 bits), a warm-up-free parallel window architecture is proposed to double the speed at the cost of a hardware increase of 12%

In this paper we propose a new multirate optical network based on a hybrid S-ALOHA/overlapped-CDMA system as an effective way of integrating multi-class traffic. The key issue in this proposal is to exploit the potential of the optical overlapped CDMA using fiber Bragg grating when jointly used with the S-ALOHA protocol in a link layer. The newly proposed system is modeled using general Markov chain from which both the system throughput and the average packet delay are derived. Our system is then compared to the classical S-ALOHA/variable processing gain (VPG) CDMA system. Numerical results show that our system outperforms the latter especially at high transmission rates

We consider an optical code-division multiple-access (OCDMA) network that supports multiple traffic classes. Each class has different processing gain and performance requirements. In this paper, a new method is proposed to analyze the cutoff rates for a multiclass, multirate optical frequency-hopping code-division multiple-access system using fiber Bragg gratings and direct detection. This approach exploits the linear structure of passive OCDMA systems and the nominal time required to accomplish the encoding-decoding operations in such systems. A system model is presented and analyzed, based on a newly introduced bit-overlap procedure. An expression for the cutoff rate of a single-class system is derived. In addition, for a multiclass system, an expression that relates the cutoff rates of the offered classes is introduced, and it is called the service curve. It is shown that for a required quality of service guarantee, a number of active users, and a given probability of hit, the system's data rate can be increased beyond the nominal limit imposed by the physical constraint of the encoder-decoder set.

Power control is essential for code-division multiple-access CDMA cellular systems to overcome the near-far problem since all users share the same bandwidth. In this paper, we solve the power control problem for the multicarrier direct sequence CDMA (MC-DS-CDMA) system. We propose two algorithms based on the measure of the signal to interference ratio (SIR) allowing for the elimination of the effect of distance and slow shadowing in the case of indoor and outdoor environments.

An optical CDMA network that supports multiple traffic classes is considered. Each class has different processing gain (PG) and performance requirements. In this paper, we generalize the method that we have previously proposed to analyze the cutoff rates for a single-class multirate optical frequency hopping code division multiple access system (OFFH-CDMA), to the case of multiclass multirate OFFH-CDMA system. This approach exploits the linear structure of passive optical CDMA systems and the nominal time required to accomplish the encoding-decoding operations in such systems. A system model is presented and analyzed based on a newly introduced bit-overlap procedure. An expression that relates the cutoff rates of the offered classes is introduced and it is termed the service curve. It is shown that for a required quality of service (QoS) guarantee, a number of active users, and a given probability of hit, the system's data rates can be increased beyond the nominal limits imposed by the physical constraint of the encoder-decoder sets.

Maximum-ratio combining (MRC) is a simple and effective combining scheme for adaptive antenna arrays to combat noise, fading, and to a certain degree, cochannel interference. However, it requires estimation of the spatial signature (i.e., the channel gain and phase at each antenna element) of the desired signal across the array. Assuming that this estimate is obtained by correlation using a known training sequence of K symbols embedded in the useful signal, we proceed to develop a fully analytical assessment of the impact of estimation error on the output signal-to-noise ratio (SNR) of the array. The originality of the approach revolves around the derivation of the distribution of the normalized SNR, that is the real SNR normalized to the ideal (i.e., perfect estimation) SNR. The end result is a set of distributions which can potentially reduce or in certain cases eliminate the need for simulation to determine certain design parameters such as array size, training sequence length, etc. These are then applied to find closed-form expressions for the outage probability and the error probability in differential phase-shift keying and quarternary phase-shift keying after training in uncorrelated Rayleigh fading.

This letter proposes a simple analytical model to accurately quantify the degree of fading envelope correlation among the received signals at the antenna elements of an adaptive array operating in a frequency-selective environment. The adaptive array is assumed to be at an elevated base station with scattering being confined to a local region around the subscriber station. This corresponds to the so-called "local scattering" or "macrocell" assumption and it results in most of the received energy at the base station array being concentrated within a given beamwidth. Our formulation provides closed-form, finite sum expressions for the covariance and correlation coefficients as a function of spatial and frequency separation.

A new method is proposed to analyze the cutoff rate of a variable-bit-rate (VBR) optical fast frequency hopping code division multiple access system (OFFH-CDMA) using fiber Bragg gratings and direct detection. This approach exploits the linear structure of passive optical CDMA systems and the nominal time required to accomplish the encoding-decoding operations in such systems. A system model is presented and analyzed based on a newly introduced bit-overlap procedure. An expression for the cutoff rate of a VBR OFFH-CDMA system is derived. It is shown that for a required quality of service (QoS) guarantee, the system's data rate can be increased beyond the nominal limit imposed by the physical constraint of the encoder-decoder set.

Many equalizers based on neural networks have been proposed across the literature. Unfortunately, the complexity and the slow convergence still have to be overcome for neural equalizers to be implemented in real time. This paper presents neural equalizers suitable for multi-level QAM constellations, and trained using complex extended Kalman and RLS algorithms, which makes them more robust against severely dispersive channels, like broadband outdoor or indoor mobile communication channels. The activation function is optimized to obtain good performance for large size signal constellations (i.e. up to 256-QAM). Extensive simulations show the benefits and limitations of these neural equalizers over traditional decision-feedback equalizers.

This paper analyses a new transmitter-receiver architecture based on a modified version of unipolar-bipolar correlation proposed for noncoherent multirate optical fast frequency hopping CDMA (OFFH-CDMA) system. The system assigns a frequency-shifted version (FSV) of the code used to transmit data bit "1" in order to transmit data bit "0". For the original system, we show that due to the nature of multimedia network, the fluctuation in the MAI average causes a threshold drift and thus an increase in the probability of error. This paper also provides a stochastic description of the MAI average amplitude fluctuation using a predefined multimedia probability density function. A system model is presented. From the theoretical analysis and numerical results, it is shown that the proposed system has good performance without dynamic estimation of the detection threshold, thus is independent of both the number of users and the distribution of those users in the offered multimedia classes.

In this paper, we propose an importance sampling (IS) analysis of an OFDM system which employs local equalization. IS is a fast Monte-Carlo simulation technique which aims to reduce the variance of a given simulation estimator (or the number of required simulation samples). The simulated system is a an equalized OFMD model with 512 sub-carriers. The equalizers, using a learning sequence, estimate the frequency response of the channel at each sub-carrier. By applying the IS simulation technique, we have estimated a BER of the order of 10/sup -5/ with only 1000 simulations. The gain in simulation time is exceptional.

We propose a new multirate optical communication system using optical fast frequency hopping CDMA (OFFH-CDMA) for multimedia applications in which different quality of services (QoS) are required. In this system, each user needs only to transmit the minimum required power to achieve a desired signal to interference ratio (SIR). We assign different power levels to each rate through an average interference-based power control algorithm using variable optical attenuators. Such an approach minimizes interference and at the same time provides variable QoS constraints for different traffic types. The simulation shows a great improvement in the system capacity.

Support of multiple data services can be accomplished via code division multiple access (CDMA) with a constant chip rate, but variable data rates. We present exact equations for the cross-correlation of codes in a multiple-data rate system, and thus equations for the multiple access interference (MAI) and bit error rate (BER). Previous analysis has found the EER using the mean of the MAI assuming codes are truly random sequences. We show that Gold and Kasami sequences have a cross-correlation with a distribution closely approximated by a Gaussian one, and present confidence intervals to quantify the performance under the random code assumption.

Systematic design of pipelined recursive filters is presented. The procedure is based on a multiplication algorithm which generates the result with most significant digit first. Since the latency of such a multiplier is low, a reduced number of pipelining delays may be introduced in the reduction loop, resulting in a high sampling rate. The implementation obtained exhibits minimum hardware and ensures minimum latency. It is shown that its flexibility allows, on one hand, the ability to choose freely the number system radix and, on the other hand, the interleaving of two multiplier arrays into one. This is illustrated by the realization of a second-order all-pole filter, operating in a radix-4 representation and using only one array to perform two multiplications. In this way, long interconnections are avoided and denser and more regular layout is achieved. It turns out that the design procedure can also be applied successfully to various types of realization where multiplications are required.>

The authors derive a procedure to send r bits on M parallel channels. A decomposition of the best constellation in Z/sup M/+(1/2, . . ., 1/2) is given in terms of the cross-products of lower dimensional shells of points. The proposed scheme can be used with good known coset codes to provide an alternate method of coded modulation. The results indicate that one can get good shaping gains for low encoder complexity. The method is also generalized for channels with unequal gains. The authors also find a significant performance advantage at fixed shaping gain, in certain cases, with respect to the recent Voronoi constellations in terms of peak-to-average power and constellation expansion.>

A novel digital implementation of time-domain block LMS (least mean square) filtering is presented. The primitive operators are serial-parallel multipliers which produce the results digit by digit, most significant first. The use of a redundant notation is essential here. These operators are placed in a parallel and pipeline structure, resulting in a fast realization with O(log(L*N) mod /sub L/) time, where N and L are filter length and block length, respectively. This new realization is particularly suitable for VLSI implementation because of this modularity and the high integration capacity of the serial-parallel multipliers.>

A conjecture is proven on the number of points on shells for the shifted Z/sup 4 /and the shifted Z/sup 8/ lattices. Furthermore, the results are extended to any shifted Z/sup 4//sup n/ lattice (n=0, 1, . . .). These results provide an easy way to compute the number of points on shells for the type of lattices used in the design of multidimensional signal sets or in vector coding.>