Ultra-Reliable Low-Latency Communication is the Fifth Generation (5G) use case with the most stringent requirements for latency and reliability. In Beyond 5G and future 6G systems, there will be a need to support a large number of URLLC devices, giving rise to a new use case known as massive URLLC (mURLLC). Addressing these demands requires efficient resource sharing among multiple devices. Non-Orthogonal Multiple Access (NOMA) emerges as an efficient solution to enhance spectral efficiency by allowing simultaneous transmissions from multiple devices over shared resources. In this paper, we propose a novel joint sub-channel allocation and power control framework that integrates Irregular Repetition Slotted ALOHA (IRSA) with Grant-Free NOMA (GF-NOMA). The resource allocation problem is formulated as a multi-agent reinforcement learning task, where each device acts as a learning agent and the gNodeB (gNB) broadcasts global feedback to meet the stringent reliability and latency requirements. The framework introduces new Quality Scores (QS) that guide agents in selecting resources more efficiently. Extensive simulations demonstrate that the proposed framework significantly outperforms existing techniques in meeting the stringent mURLLC requirements.

This paper focuses on maximizing the sum secrecy rate in secure multi-user MISO communication systems that use stacked intelligent metasurfaces (SIM). SIM technology manipulates electromagnetic waves and improves secure communication by combining several metasurface layers with discrete phase-shifting capabilities. We propose a methodology for optimizing beamforming vectors at the base station and phase shifts across metasurface layers, with the goal of maximizing the sum secrecy rate while adhering to practical power constraints. The non-convex optimization problem, induced by discrete phase shifts and coupled design beamforming parameters, is dealt by using an alternating optimization (AO) method. This method employs successive convex approximation for beamforming and projected gradient ascent for phase shift adjustment, resulting in convergence to locally optimal solutions. The proposed approach is thoroughly assessed in simulated scenarios to discover how it performs under various system configurations. The findings reveal that increasing the number of metasurface layers and meta-atoms significantly increases the sum secrecy rate by improving spatial control, lowering interference, and effectively repelling eavesdropping threats. Furthermore, the AO algorithm demonstrates rapid convergence and computational efficiency, making it appropriate for practical use. The framework demonstrates strong flexibility to changes in transmit power, antenna design, and user densities while retaining stable and scalable performance. This research emphasizes the potential of SIM-assisted systems in improving security in wireless communications by enhancing spatial architecture and beamforming, which can complement existing security strategies.

Recently, cutting-edge techniques, such as Non-Orthogonal Multiple Access (NOMA), have been highlighted to enable wireless networks to handle massive access scenarios and further improve the spectral efficiency. Nevertheless, these advantages come at the price of privacy exposure since a received signal may contain information belonging to several users. Usual security mechanisms, such as upper-layer encryption and sophisticated authentications, are not well suited to low-capacity Internet of Things (IoT) devices. These technical challenges have spotlighted Physical Layer Security (PLS) as a key enabling technology since it takes advantage of the wireless communication characteristics to secure communications without adding complex encryption mechanisms at higher layers. In this paper, we propose a PLS approach based on a network coding technique in order to ensure secure NOMA-based downlink transmissions taking into account the Quality of Service (QoS) requirements of the users. By doing so, decoding successfully some of the transmitted packets by an eavesdropper does not reveal useful information about the data. In fact, we develop a sequence-based algorithm with the aim of ensuring the confidentiality by changing the users’ positions in the Successive Interference Cancellation (SIC) decoding process. Henceforth, using its corresponding sequence, the legitimate user becomes the only one able to decode the information sent by the Base Station (BS). We show that the eavesdropper decoding complexity increases exponentially with the sequence length making the task intractable for relatively long ones.

The evolution from 5G to the upcoming 6G has spotlighted the limitations of the available wireless spectrum, which has become more pronounced. Thereby, efficient spectrum allocation through the design of appropriate multiple access methods is a critical challenge in addressing the demands for massive connectivity, broadband services, and facilitating efficient sharing of communication resources among multiple users. To address this challenge, we propose, in this paper, a novel approach entitled the LoCoNOMA framework. This framework focuses on optimizing resource allocation in Grant-Free (GF) Non-Orthogonal Multiple Access (NOMA) systems, taking into account the limited capacity of IoT devices and enhancing the scalability of wireless communication. In our approach, IoT devices autonomously select sub-carrier and power-level for their transmissions. By adopting GF access, the complexity at the gNodeB (gNB) is significantly reduced, resulting in enhanced scalability. The gNB only broadcasts global feedback that coordinates and improves the overall performance of all devices. We assume that devices perform channel estimation, and no additional information about other devices or the gNB is required during the sub-carrier/power level selection process. The proposed framework exhibits impressive results shown through extensive simulations, highlighting its effectiveness.

Facing the exponential number of Internet of Things (IoT) devices and the scarcity of available resources, next-generation wireless networks have to meet very challenging performance targets in terms of providing massive access and ensuring higher spectral efficiency . In this vein, Non-Orthogonal Multiple Access (NOMA) has been widely recognized as one of the advantageous techniques to handle the proliferation of the IoT. Nevertheless, from a security standpoint, enabling a user to decode the signals of the other users, while using Successive Interference Cancellation (SIC), raises serious concerns regarding confidentiality and vulnerability to malicious attacks . Meanwhile, conventional security paradigms, such as upper-layer encryption and sophisticated authentication mechanisms , require high computational complexity and additional processing, which impose an overwhelming burden on energy-efficient IoT devices. Alternatively, Physical layer Security (PLS) has sparked a significant interest as a promising complement to cryptographic techniques . The key idea of PLS is to avail wireless communication properties to secure communications without adding complex encryption mechanisms at higher layers. In this paper, we propose a PLS approach based on a network coding technique to prevent eavesdroppers from decoding users’ information transmitted through a downlink-based NOMA system. This results in correlating the packets to be transmitted with each other, making the interception of a single packet useless. We demonstrate that the eavesdropper’s decoding complexity increases exponentially with the sequence length , making the task intractable for relatively long ones.

Massive machine-type communications (mMTC) represent a significant challenge in the fifth generation of wireless networks (5G) and become increasingly critical in the sixth generation (6G) due to the limited frequency spectrum. Addressing the demands of mMTC requires efficient resource sharing among multiple users. Integrating Grant-Free (GF) access with Non-Orthogonal Multiple Access (NOMA) is a promising strategy to improve spectral efficiency . However, it may cause additional interference and complexity at the gNodeB (gNB) side. To mitigate these issues, we propose a novel, low-complexity GF-NOMA framework for joint power and channel allocation, where devices autonomously select their sub-carriers and power levels in a fully distributed manner. Besides, the gNB’s role is limited to sending a global feedback for device coordination. The proposed technique has been validated analytically and through simulation, demonstrating superior performance compared to existing approaches, in particular for the massive access scenario.

Cell-free Massive multiple-input multiple-output (CF-mMIMO) is one of the most promising technologies. It is crucial to examine the performance of CF-mMIMO systems in real-world scenarios, particularly the hardware impairments caused by nonlinear power amplifiers (PAs). This paper’s main objective is to thoroughly examine CF-mMIMO under PA non-linearity at user equipment (UE), focusing on power allocation performance. We provide closed-form expressions for uplink achievable data rates while accounting for the nonlinear behavior of the PA. We extensively examine power control strategies. Initially, we explore full power transmission and Channel Inversion. Then, we address the non-convex problem of maximizing both the sum rate (MSR) and the minimum rate (MMR) of users using the single condensation method (SCM) and successive convex approximation (SCA) algorithm. We propose iterative algorithms to optimize the ultimate geometric programming (GP) problem and find the optimal power control coefficients. Results confirm that the proposed nonlinearity-aware power control yields substantial enhancements in net throughput compared to conventional algorithms. This underscores the superiority of integrating the nonlinearity of PAs into the power allocation strategy. The proposed MSR algorithm not only enhances the sum throughput but also increases the minimum net throughput and Jain’s fairness index of net throughput.

This paper focuses on the study of hybrid beamforming (HBF) design, which aims to reduce hardware complexity and energy consumption in massive multiple-input and multiple-output (MIMO) systems that operate in frequency-selective channels. The proposed HBF architecture utilizes fixed phase shifters (FPSs) and switches to perform analog beamforming coefficients in an orthogonal frequency division multiplexing (OFDM) multiuser multiple-input and single-output (MISO) system. Our design aims to maximize the downlink sum rate while satisfying power constraints for each sub carrier by jointly optimizing the digital and analog precoder coefficients. To address the underlying non-convex optimization problem, we employ the alternating optimization approach and fractional programming (FP) technique. Through numerical studies, we demonstrate the effectiveness of our proposed design compared to baselines under different network settings.

In this paper, we introduce a novel pilot-based channel estimation approach for Orthogonal Time Frequency Space (OTFS) modulation systems. Our proposed method, which involves inserting a row of pilot symbols in the zero padding region of the ZP-OTFS system, offers significant advantages such as reduced overhead and lower Peak-to-Average Power Ratio (PAPR). Notably, by spreading pilot symbols across the Doppler axis, our method provides robust and accurate channel estimation even in high mobility scenarios, a characteristic feature of environments like the TransPod system for 1000 km/h+ transportation. This is crucial, as the Doppler shifts in such scenarios could otherwise lead to substantial degradation in system performance. We investigate the channel transfer function of the TransPod guideway using the ray-tracing propagation model to illustrate this advantage. Through simulation results, we demonstrate that our proposed method outperforms the conventional pilot-based estimation method, highlighting its potential to significantly enhance OTFS system performance in practical, high-mobility scenarios. This research offers valuable insight into the potential improvements in OTFS channel estimation techniques and their real-world applications.

The hybrid beamforming (BF) technique has been put forward to reduce required radio frequency (RF) chains in massive Multiuser MISO systems. Nevertheless, it requires an analog network to implement the complex coefficients of the analog BF in the analog domain. Deploying fixed PSs with switch networks is a simple architecture in which the BF coefficients are selected from a feasible set. In this paper, the size of the feasible set is analytically analyzed for the practical PSs numbers. We show that, in contrast with the largely used practical systems, the selection of a power of two as the number of PS is a very bad choice. In fact, a prim number of phase shifters is the most efficient selection.

Abstract In cell‐free massive multiple‐input‐multiple‐output (CF‐MMIMO) systems, a massive number of access points, mastered by central processing units are distributed in a coverage area to serve much smaller number of user equipments (UEs) simultaneously over the same time/frequency resources. In opposition to the centralized MMIMO, CF‐MMIMO particularity is that its channel hardening degree is not sufficiently accentuated, thus, it will be judicious to include downlink (DL) pilots in order for the DL channel to be estimated. This paper considers the DL pilot assignment for the CF‐MMIMO systems by defining a metric, involving the inter‐user interference. This metric gives insights into DL pilot contamination. A threshold is then defined to optimize the number of DL pilots, which maximizes the minimum per‐user DL throughput. This approach gives a conflict graph, where each UE is regarded as a vertex of the graph. This is a combinatorial optimization problem that can be approximated using graph‐colouring algorithms. The simulation results reveal that the proposed method outperforms interestingly, in terms of per‐user DL throughput, the existing methods such as statistical channel state information, the orthogonal, and the random pilot assignment in the DL training.

Network coding (NC) is one of the promising high-performance techniques for wireless sensor networks (WSNs). However, few works have focused on the concerns of multi-source networks using error correcting codes. When an intermediate node fails errors may occur and since NC combines packets from different sources, several packets can be affected. In this paper, we propose a modified-low rank parity check (M-LRPC) decoding algorithm for a scenario with multiple source nodes. Furthermore, we investigate the performance of the proposed coding technique in terms of success decoding rate. Then, we derive an analytical expression for the decoding probability of the proposed M-LRPC. Simulation results are conducted in order to validate our analytical findings. These results show that the proposed scheme significantly improves the decoding probability compared to Gabidulin codes.

In wireless sensor networks (WSNs), data produced by sensors are usually routed through several intermediate nodes to reach the sink Base Station (BS). In fact, since a WSN is usually composed of low-cost and limited capability sensors, their transmission range prevents the establishment of a reliable communication with the sink. When an intermediate node fails, errors may occur and the message is not delivered to the sink. The reliability of the system can be increased by using Network Coding (NC) techniques. In this paper, we consider the problem of data gathering in WSNs and we propose a novel error correction mechanism using Low Rank Parity Check code (LRPC), which is known to be good at correcting burst errors, as an outer code and a convolutional code as an inner code to correct sparse errors. Furthermore, we investigate the performance of the proposed system in terms of the packet error probability and the decoding complexity. We also propose a theoretical approximation of the decoding probability for LRPC codes in the case of network coding for binary and non-binary fields. We show, through Matlab simulations, that the proposed concatenated code outperforms the proposed coding schemes in the literature for data gathering in terms of decoding rate and complexity.

In this paper, we investigate multihop cooperative data exchange (CDE) using instantly decodable network coding (IDNC) in decentralized wireless nodes. In such model, we focus on how these wireless nodes can cooperate in limited transmission ranges without increasing the IDNC delay nor their energy consumption. For that purpose, we model the problem using a two stage game theory framework. We first model the problem using non-cooperative game theory where users jointly choose their desired transmission power selfishly in order to reduce their energy consumption and their IDNC delay. The optimal solution of this game allows the players in the next step to cooperate with each other through limited transmission ranges using cooperative game theory in partition form framework. Thereafter, a distributed multihop merge-and-split algorithm is defined to form coalitions where players maximize their utilities in terms of decoding delays and energy consumption. Indeed, the solution of the proposed framework determines the stable feasible partition for the wireless nodes with reduced interference and reasonable complexity. We demonstrate through simulations that the cooperation between nodes in the multihop cooperative scheme achieves a significant minimization of the energy consumption with respect to the most stable cooperative scheme in maximum transmission range without hurting the IDNC delay.

In this paper, we consider a Wireless Sensor Network (WSN) with Wireless Energy Transfer (WET) capability, and we focus on the data gathering in a multi-hop scenario. In fact, we assume that any wireless sensor that needs the help of relays to deliver the packet may transfer energy as a kind of reward or payment. We assume that only few sensors have direct reliable channel to the sink Base Station (BS), i.e. sensors that are close the BS. Hence, other sensors should relay on them to transmit their packets to the BS. We assume that the nodes of the WSN are selfish and aim to maximize their utility function, which mainly accounts for their energy consumption. We propose a multi-level multi-leader-follower Stackelberg game framework to analyse the competition between users. Particularly, we characterise the Stackelberg equilibrium (SE) for the three-hop WSN, and we propose a distributed algorithm to achieve the SE. Moreover, we show that the network lifetime is enhanced compared to other multi-hop data transmission in WSN.

In this paper, we investigate the cooperative data exchange (CDE) using instantly decodable network coding (IDNC) across the wireless nodes. We model the problem using the cooperative game theory in partition form. Unlike most of existing works concerning IDNC, we focus not only on the decoding delay, but also the consumed energy in order to increase the network lifetime. A distributed merge-and-split algorithm is proposed to form coalitions that maximize their utilities in terms of energy consumption and delay experienced by all the receivers. Indeed, the proposed algorithm enables the wireless nodes to self-organize into independent disjoint coalitions and the resulting clustered network structure is characterized through stability notion. Simulation results show that the cooperation between nodes not only reduces the energy consumption, but also the IDNC completion time. Note also that the proposed solution reduces the complexity of the CDE which makes the network more scalable and more reliable.

Power Line Communication (PLC) channel is a fading channel whose their characteristics vary considerably over long distances and at high frequencies, therefore the major challenge, for the researchers, is how to supply robust and efficient communication in PLC systems. To overcome these constraints Cooperative Communication and Network Coding have been demonstrated to be effective techniques. Consequently in this paper, we consider a two-way relaying PLC system in which the Orthogonal Frequency Division Multiplexing (OFDM) is considered for the source 1-to-source 2, the source 1-to-relay and the relay-to-source 2 links where the relay node performs Amplify and Forward (AF) protocol. We propose a conventional bi-directional relaying schema (AF-PLC) which we compare to a schema including a Physical Network Coding (AF-PNC-PLC) for different number of time slots dedicated to exchange data messages between two source nodes S1and S2with the assistance of the relay node R. We also evaluate the data rate for OFDM-based two-way relaying AF-PLC and AF-PNC-PLC systems by applying the adaptive modulation technique.

As the size of Wireless Sensor Networks continues to grow, the amount of data for processing and transmitting becomes enormous. In many practical cases, the wireless sensors are distributed across a physical field to monitor physical phenomena with high space-time correlation. Compressive Sensing is a promising technique to exploit this correlation in order to limit the number of transmission and therefore increase the lifetime of the network. In this paper, we are interested in mesh network topology where the sink node is not in the range of sensors and routing schemes must be applied. We propose a joint Space-Time Compressive Sensing by exploiting jointly inter-sensor and intra-sensor data dependency. Since the routing and the number of retransmission affect significantly the total energy consumption, we introduce the routing in our cost function in order to optimize the selection of transmitting sensors. The simulations show that this method outperforms the existing ones and confirm the validity of our approach.

Powerline network is recognized as a favorable infrastructure for Smart Grid to transmit information in the network thanks to its broad coverage and low cost deployment. The existing works are trying to improve and adapt transmission techniques to reduce Powerline Communication (PLC) channel attenuation and exploit the limited bandwidth to support high data rate over long distances. Two-hop relaying BroadBand PLC (BB-PLC) system, in which Orthogonal Frequency Division Multiplexing (OFDM) is used, is considered in this paper. We derive and compare the PLC channel capacity and the end-to-end Average BER (ABER) for OFDM-based direct link (DL) BB-PLC system and for OFDM-based two-hop relaying BB-PLC system for Amplify and Forward (AF) and Decode and Forward (DF) protocols. We analyze the improvements when we consider the direct link in a cooperative communication when the relay node only transmits the correctly decoded signal. Maximum ratio combining is employed at the destination node to detect the transmitted signal. In addition, in this paper, we highlight the impact of the relay location on the channel capacity and ABER for AF and DF transmission protocols. Moreover, an efficient use of the direct link was also investigated in this paper.

Since PLC channel is a fading channel whose characteristics vary considerably over long distances and at high frequencies the major challenge for researchers in Smart Grid, is how to supply robust and efficient communication. To overcome these constraints Cooperative communication and Network coding have been demonstrated to be effective. Consequently in this paper, we consider a two-way relaying PLC system in which orthogonal frequency division multiplexing (OFDM) is employed for the source 1-to-source 2, the source 1-to-relay and the relay-to-source 2 links where the relay node performs Amplify and Forward (AF) protocol. We consider a conventional bi directional relaying schema (AF-PLC) and we compare it to a schema in which we include Physical Network Coding (AF-PNC-PLC) for different number of time slots dedicated to exchange data messages between two source nodes S1and S2with the assistance of the relay node R. We also derive the channel capacity and sum-average BER (SA-BER) expressions for OFDM-based two-way relaying AF-PLC and AF-PNC-PLC systems without and with cooperative diversity. Moreover, we provide a solution based on sub-carrier pairing technique to further improve the channel capacity and SA-BER performances.

A major challenge for researchers in Smart Grid, is how to supply robust and efficient communication since PLC channel is a fading channel whose characteristics vary considerably over long distances and at high frequencies. To overcome these constraints Cooperative communication and Network coding have been demonstrated to be effective. Consequently in this paper, we consider a two-way relaying network in which orthogonal frequency division multiplexing (OFDM) is employed for the source 1-to-source 2, the source 1-to-relay and the relay-to-source 2 links where the relay node performs Amplify and Forward (AF) protocol. We consider a conventional bi directional relaying schema (AF-PLC) and we compare it to a schema in which we include Physical Network Coding (AF-PNC-PLC) for different number of time slots dedicated to exchange data messages between two source nodes S1and S2with the assistance of the relay node R. We also evaluate the channel capacity for OFDM-based two-way relaying AF-PLC and AF-PNC-PLC systems without/with cooperative diversity. Moreover, we provide a solution based on sub-carrier pairing technique to further improve the channel capacity.

Power Line Communication (PLC) remains the most appropriate communication architectures and technology for Smart Grid (SG) deployment. A major challenge for researchers in SG, is how to supply robust and efficient communication since PLC channel is a fading channel whose characteristics vary considerably over long distances and at high frequencies. To reach this goal, cooperative communication has been proven to be effective. Thus in this paper, we derive the channel capacity for OFDM-based two-hop relaying PLC system where we use a relay node between the source and destination nodes. We analyze channel capacity for Amplify-and-Forward (AF), Decode-and-Forward (DF) relaying protocols and Fountain-code-and-Forward (FCF) protocol which joint cooperative relay and coding techniques. We highlight in this paper how the use of this new category of cooperation relaying protocol (FCF) increases channel capacity of an OFDM-based two-hop relaying PLC system.

A new distributed coding scheme is proposed to achieve diversity in a network comprising multiple sources, multiple relays, and a single destination. This scheme is based on a distributed implementation of linear block codes, where each relay is assigned to a subset of the source nodes using the channel state information (CSI) of the source-relay (SR) channels. The proposed scheme achieves diversity without using the CSI of the relay-destination (R-D) channels for relay assignment. On the other hand, in classical distributed coding schemes, it is usually assumed that each relay can fully decide if its received symbols are successfully decoded. This is achieved by using complicated coding schemes in S-R channels, which is also vulnerable to quasi-static fading. The proposed scheme achieves the intended diversity without using this extra coding/overhead. For the resulting relay assignment problem, we propose an algorithm based on the max-min criterion.

In this paper, we address the relay assignment in cooperative networks based on order statistics. We consider a network comprising a cluster of transmitting sources, a cluster of relay nodes and a single destination. This is motivated by the fact that the existing relay assignment schemes don't achieve diversity for the network configuration under consideration. We assume that the cooperation is in the amplify-and-forward (AF) mode, but proposed scheme is applicable to the decode-and-forward (DF) mode. In the relay assignment process, the source nodes that have weaker source-destination links, have higher priority in relay selection. We analyze the probability density function (PDF) and the average bit error rate (BER) for the proposed scheme where we invoke important results that we first derive for simple two-hop networks. Specifically, we calculate the exact expression for the PDF of the end-to-end signal-to-noise ratio (SNR). Compared to other relay assignment schemes (like maximizing sum of SNR values or maximizing the minimum selected SNR), the proposed scheme has the advantages of simplicity, higher diversity order and fairness.

This paper deals with relay assignment in cooperative networks based on the max-min criterion. A simple algorithm is proposed in order to find the optimum relay assignment permutation to avoid brute-force prohibitive search method. It is assumed that there are N source-destination pairs and M relays in the network. The problem is how to assign each relay to a source-destination pair in order to achieve the highest diversity order. The proposed algorithm achieves the maximum spatial diversity for all of the nodes and leads us to simplify the analysis and simulation of the optimal answer. It is shown that the Probability Density Function (PDF) of the end-to-end signal-to-noise ratio (SNR) after relay assignment can be expressed as a weighted sum of the order statistics of the PDF of individual end-to-end links. Since the analytical calculation of the weighting coefficients in the mentioned weighting sum becomes difficult, we propose an approximation in order to calculate the mentioned weighting coefficients. The validity of this fit is shown through some simulations.

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This paper offers the statistical analysis of relay assignment in cooperative Decode-and-Forward (DF) networks based on order statistics. By assuming a set of N independent Rayleigh fading channels, first the channel with r-th biggest SNR is analyzed. The diversity order and average error probability for this channel are calculated. Then it is assumed that there are two clusters of terminals and the terminals in each cluster are relatively close to each other, so they have equivalent average SNR to the destination. The cluster with better average SNR is assumed to be the relay cluster. The problem is to find best pairing of source-relays. By assuming the SNR of direct channels to be i.i.d. random variables, it's more reasonable to work with their order statistics, because order statistics reveal the relative SNR of the channels. This is the basic distinction of this paper from similar papers. Using this approach, two different scenarios are proposed to assign the best relay to each weak-channeled terminal based on the instantaneous SNR information. In the first scenario, only the SNR of direct links between the terminals and the destination are known; whereas in the second scenario we assume that the SNR of all channels are available. It's shown that in the second scenario, a much higher performance can be achieved through cooperation.

This paper addresses the problem of transmitting data to multiple mobile stations using a decode-and-forward strategy. Precoding vectors are used in relays to cancel out multiple access interference at the mobile stations. Statistical distribution of signal to noise ratio (SNR) is approximated by an expectation maximization algorithm. Based on this distribution, system performance is evaluated for low and high SNR. Simulation results confirm the analytic calculations and show that the maximum diversity advantage can be obtained, which is the product of the number of antennas at each relay by the number of relays minus the total number of system constraints.

We propose in this paper optimized designs for LDPC codes which are able to work close to the theoretical bounds for the half duplex relay channel using the decode and forward strategy originally proposed by Cover and El Gamal. The challenge is that we have to find two codes operating at different rates and at different SNR's: one for source-destination and the other for relay-destination transmission. We use density evolution together with Gaussian approximation for the design of the proposed irregular LDPC codes. Simulation results show that our proposed LDPC enable to work within less than 1.0 dB from the theoretical limit capacities under different channel conditions.

A unified method to derive Tanner graph related to tail-biting convolutional codes (CCs) is presented. The graphs obtained by this method have low complexity even for codes with a large number of states. It is shown that under certain conditions, a unique graph can be used for decoding of recursive and non-recursive CCs. Analog realization of such a graph employing MOS transistors is discussed and its circuit-level simulation results are given.

An iterative expectation-maximisation time–frequency synchronisation algorithm joint with channel estimation for multiple-input multiple-output–orthogonal frequency-division multiplexing (OFDM) systems in frequency-selective fading channels is addressed. The receiver iterates between detection and estimation stages. For each iteration, the expectation of ODFM symbols is calculated first by using a posteriori probabilities provided by maximum a posteriori (MAP) decoder, and second, a proposed metric is maximised to obtain both frequency offset and symbol timing. The channel can be identified by means of these estimates. This algorithm can work in transmission mode, and thus, can be used to estimate the residual errors or track the change of the parameters. The performance of the proposed synchronisation approach, in terms of bit-error rate and mean-square error, is shown.

The design of expectation–maximisation (EM)-based turbo receivers for low-density parity-check-coded multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems with the presence of carrier-frequency offset (CFO) is studied. First, starting from the maximum-likelihood principle, a novel EM-based CFO estimator for MIMO-OFDM systems is devised. This estimator iteratively provides the CFO estimate with the aid of pilot symbols. It is also capable of accommodating any space–time-coded-OFDM transmission. Then this CFO estimator is incorporated into the initialisation step of the turbo receiver. Simulation results show the effectiveness of the receiver design in combating CFO over unknown frequency-selective fading channels.

New sphere decoding algorithms are proposed in this paper. We put the emphasis on an iterative list branch and bound (BB) algorithm which is based on the basic BB algorithm.. When compared to other LSD algorithms, simulation results show that the proposed list BB algorithm can achieve near capacity performance with smaller candidate list size.

A mixed-signal programmable filter suitable for high- rate WLAN is addressed in this work. The proposed filter has analog input and analog-sampled outputs. The filter taps are stored in a digital memory and can be changed easily to meet any receiver requirements. The filter structure is based on a bank of digitally controlled transconductors realized by simple CMOS inverters and thus can be integrated efficiently with digital parts. A cosine rolloff filter is designed and investigated by simulation in frequency domains. Comparison with other recent works shows that the proposed structure has a good speed-complexity-consumption trade-off.

We propose in this paper a maximum likelihood (ML) estimator to jointly obtain time and frequency synchronization together with channel estimation in a MIMO OFDMA system. The proposed algorithm is planned to be implemented in a base station (BS) environment and so it is mainly devoted to uplink asynchronous transmission schemes. We propose a new EM based procedure which enables to convert a multidimensional maximization problem into a number of substantially smaller separate maximization problems. Simulation results are presented which clearly show the accuracy of our estimator and its ability to combat the near-far effect.

This paper addresses an iterative expectation-maximization (EM) time-frequency synchronization algorithm joint with channel estimation for MIMO-OFDM systems in frequency selective fading channels. The receivers iterates between detection and estimation. For each iteration, we calculate first the expectation of ODFM symbols by using a posteriori probabilities provided by MAP decoder and second we maximise a proposed metric to obtain both frequency offset and then symbol-timing. The channel can be identified by means of these estimates. This algorithm can work in transmission mode and thus can be used to estimate the residual errors or track the change of the parameters. The performance of the proposed synchronization approach, in terms bit error rate and mean square error of the estimated frequency offset, is shown.

In this paper, we propose a new scheme for joint maximum- likelihood (ML) estimation of carrier-frequency offset (CFO) and channel coefficients in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. To reduce the prohibitive computational complexity of joint ML estimation problems, the expectation- maximization (EM) algorithm is employed. Moreover, the Cramer-Rao bounds (CRB) for both CFO and channel estimators are developed to evaluate the performance of the proposed scheme. Computer simulations show that the proposed algorithm achieves almost ideal performance compared with the CRB for both channel and frequency offset estimations.

A mixed-signal programmable filter suitable for high-rate communication systems is addressed in this work. The proposed filter has analog input and analog-sampled outputs. The filter taps are stored in a digital memory and can be changed on the fly which is desirable in many practical applications such as adaptive filtering. The filter structure is based on a bank of digitally controlled transconductors along with small capacitors. The employed transconductors are based on simple CMOS transistors and thus can be integrated efficiently with the digital parts of systems. A cosine rolloff filter is designed and investigated by simulation in frequency domains. The results show that the proposed structure has a good speed-complexity-consumption trade-off.

Channel parameter estimation is an important task for coherent detection and constitutes a key challenge in MIMO systems. Turbo-Bell Labs Laboratory Architecture Systems (T-BLAST) with orthogonal frequency division multiplexing (OFDM) can be used to improve communication quality and capacity. This paper proposed a modified expectation maximization (EM) algorithm for T-BLAST systems in frequency selective channels. It is based on a combination of data and pilot based channel estimate with approximated coefficients. These coefficients are obtained by resolving an optimization problem using the Lagrangian multipliers. The algorithm we present takes advantage of the exchange message between the two soft input soft output (SISO) modules of the turbo receiver to attain the best estimation performance. The effectiveness of this technique is demonstrated through the simulation of an OFDM T-BLAST system with two-transmit and three-receive antennas.

This paper introduces new studies on the codes named Super Orthogonal Space Time Trellis Codes (SOSTTC). Using set partitioning rules combined with a set of orthogonal designs, SOSTTC's are able to combine the coding gain of STTC's together with diversity advantage of orthogonal STBC's. We propose new application fields of these codes in the particular context of three transmit antenna systems. We introduce new STTC's built on STBC designs that outperform some STTC's schemes based on the determinant and rank criteria. Further- more, we demonstrate by simulation that the use of these codes in a turbo parallel concatenated scheme permits working very close to the channel outage probability.

We propose in this paper a maximum likelihood (ML) estimator to jointly obtain time and frequency synchronization together with channel estimation in a MIMO OFDMA system. The proposed algorithm is planned to be implemented in a base station (BS) environment and so it is mainly devoted to uplink asynchronous transmission schemes. Due to the number of unknown quantities, frequency offset estimation together with time synchronization and channel estimation for each user constitute a very complex problem. We propose an EM based procedure which enables to convert a multidimensional maximization problem into smaller separate maximization problems. Simulation results are presented which clearly show the accuracy of our estimator and its ability to combat the near-far effect.

We present a new architecture of layered space-time codes as a combination of BLAST architecture and of special STTC codes which are variations about the codes first introduced by Jafarkhani et al. and named super orthogonal space-time trellis codes (SOSTTC). Using powerful set partitioning, these codes are able to combine the coding advantage of STTC's together with the advantage diversity of orthogonal space-time block codes (STBC). The system we propose is named super quasi orthogonal horizontal layered space time trellis code (SQOHLSTTC). It consists in a powerful STBC based STTC originally derived for a three transmit antenna system, together with an original block based decoding algorithm which enables to use a higher number of transmit antennas. The decoding of SQOHLSTTC combines group interference suppression and group interference cancellation techniques. To implement the system, we propose a low complexity hard decision iterative decoding method. System performances are illustrated and confirm the great interest of the proposed transmission scheme

This paper addresses maximum-likelihood (ME) time-frequency synchronization algorithm joint with channel estimation for MIMO-OFDM systems in frequency selective fading channels. In proposed algorithm, we use two steps to maximize a proposed metric to obtain first frequency offset and then timing. Using these two estimates, the channel is identified. An iterative algorithm is proposed to improve frequency offset estimation. The performance of the proposed synchronization approach, in terms of timing failure probability and mean square error of the estimated frequency offset, was compared with literature. Based on simulation results, the Cramer-Rao lower bound is obtained with a few iterations

In this paper, we propose a multi-user detector for space-time uplink transmission in multi-carrier CDMA systems using a new combination of STBC, OFDM and CDMA spreading. To achieve high rate, CDMA spreading codes are shared between a few users and we use linear STBC decoding to further separate users. The OFDM codewords are built from chips issued from different symbols. The STBC encoder and decoder are placed at the last stage of our multi-user transmitter and receiver respectively. We show that the system is particularly easy to implement when exploiting the space diversity after CDMA detection. Besides, the performance is comparable to the case of a single user STBC system. The proposed system allows for a very high rate multi-user system compared to the conventional CDMA system or combined array-processing technique previously proposed.

In this paper we propose the new decoding rules for STBC (space-time block codes) using the maximum likelihood (ML) principles. Using algebraic tools we are able to derive a simple matrix model which is very easy to implement in the simulation. After giving our particular detection rules, we determine a new accurate upperbound for the BER performances of STBC transmitting schemes. Simulation results are given which show the accuracy of the derived upperbound.

We consider turbo-trellis-coded transmission over fading MIMO channels with transmit diversity using space-time bloc codes. We consider the concatenation of turbo-TCM with a space-time block code and show that. in addition to the transmit diversity, substantial benefits can be obtained by turbo iteration. In addition an improved CSI PSAM (pilot Symbol-Assisted Modulation Technique) scheme is proposed to obtain an iterative channel state estimate procedure.