International audience

This paper examines radio resource allocation in a full-duplex (FD) reconfigurable intelligent surface (RIS)-assisted wireless-powered (WP) industrial internet-of-Things (IIoT) communication network. The system model includes an FD access point (FD-AP) that communicates with FD energy harvesting (EH) mobile users (MUs), referred to as an FD-FD RIS-assisted WP-IIoT network. The FD-AP is equipped with two sets of multiple antennas: one set for downlink (DL) energy beamforming and another for uplink (UL) information signal reception. The FD-MUs have one antenna for DL energy signal reception and another for UL information transmission. This paper addresses the UL sum-rate maximization problem for the FD-FD RIS-assisted WP-IIoT system by jointly optimizing the RIS phase shift and power resources. Additionally, this paper presents two benchmarks as specific cases of the FD-FD RIS-assisted WP-IIoT system model, namely, (i) FD-HD RIS-assisted WP-IIoT network: FD AP and half-duplex (HD) two MUs groups, and (ii) HD-HD RIS-assisted WP-IIoT network: HD AP and HD MUs. The numerical results demonstrate that the FD-FD system outperforms both benchmarks in the low transmit power regime. Also, compared to the baseline non-RIS-assisted WP-IIoT network, the RIS-assisted WP-IIoT network achieved a significant UL sum-rate gain.

This paper investigates the sum spectral efficiency (SE) and total energy efficiency (EE) of the active reconfigurable intelligent surface (aRIS)-assisted cell-free (CF) massive multiple-input multiple-output (mMIMO) over temporal and spatially correlated channels. Multiple aRISs are deployed between numerous access points (APs) and mobile users to enhance the signals. The active reflective elements (REs) amplify and vary the signal phase. The continuously evolving channel creates a situation, where the channel differs during training and data transmission. We characterize the joint impact of multi-user interference (MUI), pilot contamination (PC), channel aging (CA), and active RIS noise amplification (RNA). The desired signal is enhanced as the reflected signal amplitude and REs per aRIS increase. However, the PC, MUI, CA, and RNA also grow– constraining the SE. Also, the network power consumption increases. An alternating optimization framework based on the weighted minimum mean square error and fractional programming is proposed to optimize the transmit power and reflection coefficients (RCs) with the objective of maximizing the sum SE. It is demonstrated that the number of APs and REs can be reduced by deploying aRISs. The proposed power and RC optimization algorithms considerably improves the sum SE. The trade-off analysis between the total EE and sum SE shows that the envelope of the operating region of the CF mMIMO is expanded by deploying multiple aRISs.

Backscatter communication has evolved, but the research interest has predominantly focused on a single carrier radio frequency source. In this paper, we propose a joint Repetition Coding (RC) and Multi-Source Temporal Combining (TC) framework to enhance the reliability and throughput of backscatter communication. Unlike conventional approaches that rely on a single carrier source or uniform repetition coding, our method dynamically assigns position-aware repetition codes while leveraging multiple ambient RF sources to exploit temporal diversity. We developed an analytical model to evaluate the bit error rate (BER) performance under different coding strategies and source distributions. Furthermore, we derive a closed-form optimization framework for adaptive weight allocation in TC, ensuring that the contribution of each RF source is weighted based on SNR, coherence time, and estimated BER.

To highlight the potential of RSMA and multicarrier (MC) techniques in vehicle-to-everything (V2X)communication, we propose and present a two-way communication MCRSMA V2X communication system that supports a large number of equipments (UEs) and promotes the dual function of sidelink and cellular communication. We employ$\mathbf{k}$-mean clustering for vehicle grouping and a suboptimal sub-carrier allocation with naive equal time and optimal precoder design for data transfer. To confirm the efficacy of the proposed system model, we compare the MC-RSMA solution against an MC-SDMA benchmark, using sum-rate as the performance metric. From the simulation results, the proposed system demonstrates significant improvements over the two multi-access technique benchmarks.

This paper investigates a full-duplex (FD) reconfigurable intelligent surface (RIS)-assisted wireless powered communication network (WPCN) in which FD multi-user (FD-MUs) industrial internet-of-things (IIoT) sensor devices with energy harvesting (EH) capabilities communicate with an FD hybrid-access point (FD-AP). The FD-AP with dual-set of multiple antennas use a set of antennas to beamform energy in downlink (DL) transmission and the other set of antennas to receive information signals in uplink (UL) transmission from the dual-set of single antenna FD-MUs. The FD-MUs use one single antenna to receive energy signals, while the other single antenna is used to transmit information. For comparison, two special cases of the FD-FD RIS-assisted WPCN IIoT network are considered. The first scenario considers an FD-HD (half-duplex) RIS-assisted WPCN IIoT network made up of a FD-AP and HD-MUs while the second comprises an HD-HD RIS-assisted WPCN IIoT network consisting of HD-AP and HD-MUs. We investigate the sum-rate performance of the FD-FD system with random IRS phase shifts and compare it to FD-HD and HD-HD system models. It is shown from simulation results that the FD-FD system outperforms the two special cases in the low transmit power regime.

This paper presents a three-tier (3T) symbiotic radio device-to-device (D2D) routing Internet-of-Things network. The primary network (PN) consists of a base station routing data through multiple single antenna decode-and-forward sensor node(s) (DSNs) and to the destination sensor node. The secondary network (SN) consists of single-antenna active sensor tag nodes (ASN) transmitting sensed data to a multi-antenna reader using the backscatter (BC) technique. The tertiary network (TN) consists of single antenna semi-passive energy harvesting sensor tags (SSN) that transmit sensed data using BC to the same multi-antenna reader. The symbiotic nature exists where the ASNs and SSNs utilize the DSNs' radio frequency for data transfer. At the same time, the PN benefits from ASNs and SSNs assistive data transfer in terms of spatial diversity. In this work, we focus on maximizing the EE for the proposed 3T SRN D2D-routing by optimizing the DSN and ASN power allocation and the SSN reflection co-efficient. Based on the optimization problem, a minimum distance-based and a maximum channel gain-based D2D-routing algorithms are proposed. The proposed channel-gain-based 3T SRN D2D-routing algorithm is shown to be superior to the distance-based algorithm.

This paper analyzes the spectral efficiency (SE) of an active reconfigurable intelligent surface (RIS)-aided cell-free (CF) massive multiple-input multiple-out (mMIMO). The aggregated channel estimate is derived and the achievable SE is obtained in closed-form by assuming imperfect channel state information. It is shown that the sum SE increases with the number of access points (APs) and reflecting elements (REs). The noise amplification due to active REs escalates the pilot contamination and impairs the sum SE. The active RIS offers higher sum SE than the passive RIS in the extreme scenarios of completely blocked and completely unblocked direct AP-user links.

In this paper, we develop an optimization framework for the symbiotic operation of a primary multi-vehicle-to-everything (MV2X) communication network employing downlink communication and a secondary backscatter (BC) communication (BackCom) network of wireless-powered sensor equipped reflecting configurable surfaces (RISs), sharing the same spectrum. The secondary semi-passive RISs provide the multiple primary receivers with a spatial diversity gain and enable transmitting their own data to a designated IoT central system equipped with a BC reader. We develop an alternating optimization algorithm for resource allocation to maximize the sum-rate for mutually beneficial symbiotic radio operation. The presented simulation results demonstrate the superiority of the proposed optimization algorithm over conventional beamforming designs and fixed RIS reflection coefficient benchmarks.

Symbiotic radio networks (SRN) have gained traction for efficient spectrum usage in wireless communication Internet-of- Things networks (IoTNs) applications. Furthermore, the efficient use of energy resources under energy-efficient communication is rising in IoTNs to satisfy and attain the United Nations' sustainable development goals on sustainable and renewable energy usage. Hence, this work focuses on energy and spectrum efficient usage through renewable radio frequency (RF) energy harvesting (EH) backscatter (BC) communication (BackCom) and SRN between a secondary network sensor-equipped EH intelligent reflective surface BC and a primary network base station to multiple user equipment using multiple access communication. This work focuses on resource allocation optimization to maximize the system energy-efficiency quality-of-service for the SRN. The superiority of the proposed scheme over existing benchmark schemes is also presented in this work.

Segmentations of ocean SAR images (Sentinel-1 A and B) into 10 classes of metoceanic phenomena are for the first time presented, with a 400 m resolution. Ocean SAR images segmentation differs from classic deep learning problems with a high variety of shapes and a particular importance of high-frequency patterns. To this end, an assessment of deep learning frameworks is performed, with a focus on the comparison between weakly supervised and supervised methods. Metrics based on the Wassertein distance indicate best performances by the supervised segmentation (U-Net) given operational constraints, thus highlighting the significance of properly annotated data sets. While available training data sets are made of small$20 \times 20 \text{km}$imagettes, the extension of the inference from imagettes to wide swath images, with a wider variety of incidence angles, presents promising results and opens the way to more extensive oceanographic applications in SAR imagery.

Next-generation wireless networks are expected to be highly heterogeneous, multilayered, with embedded intelligence at both the core and edge of the network. In such a context, system-level performance evaluation will be very important to formulate relevant insights into tradeoffs that govern such a complex system. Over the past decade, SG has emerged as a powerful analytical tool to evaluate the system-level performance of wireless networks and capture their tendency toward heterogeneity. However, with the imminent onset of this crucial new decade, where global commercialization of fifth generation (5G) is expected to emerge and essential research questions related to beyond 5G (B5G) are intended to be identified, we are wondering about the role that a powerful tool, such as SG, should play. In this article, we first aim to track and summarize the novel SG models and techniques developed during the last decade in the evaluation of wireless networks. Next, we will outline how SG has been used to capture the properties of emerging RANs for 5G/B5G and quantify the benefits of key enabling technologies. Finally, we will discuss new horizons that will breathe new life into the use of SG in the foreseeable future, for instance, using SG to evaluate performance metrics in the visionary paradigm of molecular communications. Also, we will review how SG is envisioned to cooperate with machine learning that is seen as a crucial component in the race toward ubiquitous wireless intelligence. Another important insight is Grothendieck's toposes, which is considered as a powerful mathematical concept that can help to solve long-standing problems formulated in SG.

In this paper, we characterize, based on stochastic geometry, the uplink coverage probability with a unified power control scheme built upon realistic path loss models and user equipment (UE) constrained transmit power. To improve their uplink connectivity, active UEs are next assumed to move in a random direction without prior knowledge of their nearest base station location, namely the blind cell search (BCS) movement. A tractable expression of the uplink handoff rate is then derived and the induced uplink coverage probability following the BCS movement is evaluated. The results show different echoes of the uplink coverage probability depending on the serving UE profile (stationary or mobile) and the considered path loss model, which suggests new insights into the design of uplink system parameters.

In a cost-effective implementation, we address the problem of cross-interference in cognitive multiple-input multiple-output (MIMO) spectrum sharing where mutual cochannel interference (CCI) between the primary and secondary systems is of major concern. First, we propose an optimal transmit-antenna selection (TAS) strategy that rather maximizes the received signal-to-interference-plus-noise ratio (SINR) after maximum-ratio combining (MRC). We statistically analyze the combined SINR structure and derive new expressions of its cumulative and probability distribution functions. Interestingly, we accurately show the substantial gains offered by the proposed TAS strategy in terms of the secondary system outage performance compared to the existent state-of-the-art TAS strategies. Finally, our analytical results are validated by simulations and some important insights are also underlined.

We consider a 3D cellular network in which generalized shadowing and radio network planning and optimisation (RNPO) parameters (e.g., antenna height, antenna tilt/azimuth, power biaising...) are incorporated into the cell-selection model. Using tools from stochastic geometry (SG), we derive an equivalent 2D network in which no shadowing and RNPO parameters are considered. Next, we derive coverage probability for a tractable case-study network, and the regimes where coverage probability is maximized in addition to the interference-limited one are investigated. An intermediary result is a closed-form expression generator encompassing the Q -function based-expression in [1]. Numerical results confirm the accuracy of our approximations.

Kernel techniques for efficient error probability estimation have demonstrated good performance in Bit Error Probability (BEP) estimation under a diversity of simulation frameworks. However, the transmission schemes of contemporary and emerging communication systems are more and more complex so that it is questionable if the Symbol Error Probability (SEP) estimate can be anyway derived from the BEP estimate. In this paper, we investigate for a direct way to efficiently estimate the SEP based on the kernel technique. We focus on the ubiquitous Quadrature Amplitude Modulation (QAM) systems and design a Gaussian kernel-based estimator. Simulation results, involving 4-QAM and 16-QAM symbols transmissions over the additive white Gaussian noise channel and over a frequency-selective channel, show that the proposed estimator can perform efficient, reliable and accurate SEP estimations.

In a spectrum-sharing underlay environment, we carry out a comprehensive outage probability analysis for a secondary (unlicensed) system operating with a limited feedback from the primary (licensed) system. We focus on single-user single- input multiple-output (SIMO) secondary communications where the direct link is being assisted by a set of single-antenna decode-and- forward (DF) relay nodes acting in a halfduplex selective-and-incremental relaying mode. For practicality reasons, we consider that the secondary system transmitting nodes are only capable of acquiring a limited interference channel state information (I-CSI) of the underlying cognitive radio interference channels. Accordingly, the cumulative distribution functions (CDF) of the received signal-to-noise ratio (SNR) at the secondary receiving nodes are devised in recursive and tractable closed-form expressions. These statistics are then used to derive the exact end-to-end secondary system outage probability. Also, we investigate the asymptotic outage analysis of the secondary network, and derive the achievable diversity-and-multiplexing tradeoff (DMT). Finally, the analytical and simulation results are compared and interestingly shown to perfectly match while revealing that limited I-CSI acquisition by the secondary system is more favored than its spectrum-consuming counterpart.

Higher order quadrature amplitude modulation (HOQAM) is one of the key technologies used in advanced mobile communication systems to achieve high data rates. However, in such systems, performance evaluation can be very complicated and time consuming due to the increase of constellation size. As a solution, a QAM scheme is seen as a combination of two pulse amplitude modulations (PAM). Nevertheless, the system remains complex especially with very high constellation sizes. Therefore, Monte-Carlo simulation method is impractical to obtain the expected system performance. In this paper, we propose a semi-analytical performance evaluation methodology for a PAM modulation. Our approach is based on the probability density estimation using kernel technique in joint application with cross-validation (CV) criterion. We derive both semi-analytical symbol error probability (SEP) and semi-analytical bit error probability (BEP) for several modulation schemes. Simulation results show that, in terms of SEP and BEP metrics, our technique is accurate compared with theoretical error probabilities.

In this paper, we carry out an exact outage analysis for a secondary (unlicensed) system operating under a strict primary (licensed) system outage constraint. We focus on single-user single-input multiple-output (SIMO) secondary communications where the direct link is being assisted by a cluster of single-antenna decode-and-forward (DF) relay nodes acting in a half-duplex selective-and-incremental relaying mode. Firstly, we derive a transmit power model for the secondary system where the source and relays adapt their transmit power based on: 1) a perfect acquisition of the underlying interference channel state information (I-CSI), and 2) an interference constraint that is either fixed or proportional to the primary system outage probability. Secondly, the cumulative distribution functions (CDF)s of the received signal-to-noise ratio (SNR) at the secondary receiving nodes are devised in a recursive and tractable closed-form expressions. These statistics are used to derive the exact end-to-end secondary system outage probability. The analytical and simulation results are then compared and interestingly shown to perfectly match, while revealing that with a moderate number of primary and secondary receive antennas, the secondary system spectral efficiency is amply enhanced as opposed to being severely degraded in the single receive antenna case.

In this paper, we address the issue of throughput-efficient half-duplex constrained relaying schemes for broadband uplink transmissions over multiple-input multiple-output (MIMO) channels. We introduce a low complexity signal-level cooperative spatial multiplexing (CM) architecture that allows for the shortening of the relaying phase without resorting to any symbol detection or re-mapping at the relay side. Half-duplex latency is thereby reduced, resulting in a significant throughput gain compared to amplify-and-forward (AF) relaying scheme. Surprisingly, we show that CM strategy becomes more powerful in boosting uplink throughput as the source approaches cell edge.

In this paper, we investigate practical turbo receiver design for throughput-efficient relay ARQ transmissions over broadband cooperative MIMO channels. Our setup is comprised of three multi-antenna nodes: a source, a destination, and a relay node operating under the amplify-and-forward half-duplex relaying mode. To attain higher system average throughput, we adopt a two-slot transmission strategy where the ARQ mechanism is activated on top of the amplify-and-forward protocol. We derive a soft sub-packet combiner allowing the destination node to jointly perform sub-packet combining (over both time-slots and multiple ARQ rounds) and frequency domain (FD) MMSE filtering. Its computational load is then smoothly relaxed via a recursive implementation alleviating the memory requirements when the number of ARQ rounds increases. Simulation results show that the proposed transmission strategy along with turbo sub-packet combining at the destination side achieves significant average throughput performance gain compared with conventional ARQ-based cooperative relaying, especially in situations where the relay node is close to the source node.

This paper addresses the problem of unsupervised Bit Error Rate (BER) estimation for communication systems where no prior information about transmitted bits is available at the receiver. We introduce a new technique using kernel probability density function (pdf) estimation together with Maximum Likelihood-based smoothing parameter computation. Performance is evaluated in the case of CDMA, Turbo and LDPC codes. Compared to Monte Carlo method, we show that the new technique provides good BER estimates even in the region of high SNR while it requires a few number of observations.

In a spectrum sharing underlay context, we investigate the exact derivation of the outage probability for relay-aided cognitive radio communications. To give more degrees of freedom to the secondary system in acquiring a targeted quality-of-service (QoS) under the primary system interference constraint, the secondary link is assisted by a set of relays acting in a two-hop decode-and-forward selective relaying mode. By means of the cumulative distribution functions of the received signal-to-noise ratio (SNR) at the secondary receiver, we derive the end-to-end outage probability of the secondary system in its closed form. The analytical and simulation results are then compared and interestingly shown to perfectly match over the entire interference threshold region.

In this article ad-hoc communications underlying cellular networks is studied. Two branches of usage cases, which lead to two modes of operation, are analyzed. We propose a coordinated in-band scheme where the ad-hoc communication uses the same licensed band operating the cellular networks and is under the control of cellular network operators. We show that the interference resulting from in-band ad-hoc transmission can be effectively managed by proper scheduling. The spectral efficiency gain is substantially increased using the proposed scheme.

This paper addresses the problem of unsupervised soft bit error rate (BER) estimation for any communications system, where no prior knowledge either about transmitted information bits, or the transceiver scheme is available. We show that the problem of BER estimation is equivalent to estimating the conditional probability density functions (pdf)s of soft receiver outputs. Assuming that the receiver has no analytical model of soft observations, we propose a non parametric Kernel-based pdf estimation technique, with Maximum Likelihood based smoothing parameter computation. We then introduce an iterative Stochastic Expectation Maximization algorithm for the estimation of both a priori and a posteriori probabilities of transmitted information bits, and the classification of soft observations according to transmitted bit values. These inputs serve in the iterative Kernel-based estimation procedure of conditional pdfs. We analyze the performance of the proposed unsupervised BER estimator in the framework of a multiuser code division multiple access (CDMA) system with single user detection, and show that attractive performance are achieved compared with conventional Monte Carlo-aided techniques.

Multichannel systems can benefit from multiuser diversity by assigning channels to users with best channel conditions in different time instants. In this paper, a two-dimension opportunistic scheme for OFDMA-based in-home PLC systems with random access is presented in order to exploit multiuser diversity over different subchannels and time diversity across different time slots. The proposed scheme adjusts the backoff time for each user based on the knowledge of instantaneous channel information in both frequency and time domains, and thus assigns users with better channel quality higher priority to channel accessing. Moreover, users are scheduled to transmit over their favorable subchannels in order to further improve the system throughput. The analysis shows that the collision probability of the proposed scheme is extremely small. Additionally, simulation results demonstrate that the saturated throughput is significantly augmented even in the case that the number of users is highly exceeds that of subchannels.

This paper addresses the problem of unsupervised soft BER estimation for digital communications systems, where no prior knowledge about transmitted information bits is available. We show that the problem of BER estimation is equivalent to estimating the conditional probability density functions (pdf)s of soft channel/receiver outputs. We also propose a non parametric Gaussian Kernel-based pdf estimation technique. Then, we introduce an iterative stochastic expectation maximization (EM) algorithm for the estimation of both a priori and a posteriori probabilities of transmitted information bits, and the classification of soft observations according to transmitted bit values. These inputs serve in the iterative procedure used for the estimation of conditional pdfs. We analyze the performance of the proposed BER estimator and show that is asymptotically unbiased and point-wise consistent. We also provide numerical results in the case of CDMA systems and show that attractive performance is achieved compared with conventional Monte Carlo (MC)-aided techniques.

In this contribution, we present a new class of project-and-forward (PF) relays operating with broadband MIMO hybrid ARQ-aided cooperative systems. Their architecture enables to jointly perform the orthogonal projection over multiple ARQ transmissions, increasing thereby the relay diversity order and achieving an interesting power gain over amplify-and-forward (AF)-based relaying schemes.

This paper proposes a signal-level turbo packet combining strategy for multi-antenna multi-rate relay-assisted systems operating over broadband channel. We derive a fixed rate equivalent multi-antenna system communication model where the multi-rate multi-node received signals can be viewed as direct retransmissions from a virtual node with a fixed transmission rate. Using virtual antenna concept, we introduce a frequency domain turbo packet combiner inspired by minimum mean square (MMSE) criterion. Block error rate (BLER) performance are provided to demonstrate the gains offered by the proposed combining scheme over the conventional soft information-based combining.

This paper investigates Orthogonal Frequency Division Multiplexing (OFDM) resource allocation schemes in a multiuser home Power Line Communication (PLC) network. The proposed cross-layer maximum weighted throughput scheme consists of two phases: subcarrier allocation at the Physical (PHY) layer and scheduling scheme at the Medium Access Control (MAC) layer, which dynamically integrates the channel conditions and queue characteristics to ensure leveled quality-of-service (QoS) requirements. In particular, the more bursty the various traffics are, the more advantageous the proposed cross-layer scheme is in the overall system performance, i.e., transmission rate and latency limit requirements in this work. Simulation results indicate that the proposed scheme improves the system throughput by as much as 100-130% compared with the typical maximum user required data rate scheme, meanwhile remains the latency in a tolerable limit in diverse applications supported by home PLC networks.

This paper focuses on turbo packet combining techniques for multi-relay-assisted systems operating over multiple-input multiple-output (MIMO) broadband channel. Two packet combining techniques are studied, signal-level packet combining and soft information-based combining. In this paper, a comparative study, in term of implementation cost and performance evaluation, is presented. Using complexity analysis and throughput simulations, we demonstrate that the choice of the best combining technique depends on the system configuration.

In this paper, we propose a new interference canceller (SIC-HARQ) for the WCDMA enhanced uplink system which is the combination of the hybrid ARQ technique (HARQ) with an improved successive interference canceller (SIC). The proposed SIC detector is an iterative receiver which consists of a multiple stages. It is capable of eliminating multiple user interferences (MUI) by generating and subtracting the user's contribution from the received signal. At the last stage, when there are users which have transmission errors, the erroneous packets are saved at the receiver buffer and negative acknowledgements (NACK) are sent to the transmitters which in response retransmit the packets. The retransmitted packets are maximum ratio combined (MRC) with the previously saved ones. In this manner, the obtained packet after combining is more reliable than the individually transmitted packet. This increases the probability of correct decoding and increases the performance of the improved SIC detector. We have shown that the proposed SIC-HARQ receiver improves the block error rate (BLER) results of the data physical channels. This enhancement achieves, for the modulation and coding scheme 1 (MCS1), almost 5dB at the BLER equal to 10-2.

This paper investigates throughput-efficient relay ARQ protocols for single carrier MIMO systems with amplify-and-forward relaying. We focus on reducing the multiplexing loss due to the half-duplex operation at the relay. We introduce two new relaying protocols where both ARQ and relaying are jointly targeted. Compared to the conventional relaying techniques, the proposed mechanisms require only one time slot duration for transmitting the entire data packet at each ARQ round. We also focus on performance evaluation, and show that the new techniques provide significant improvement in average throughput while maintaining good outage probability performance.

This paper focuses on turbo packet combining strategies for multi-relay-assisted systems operating over multiple-input-multiple-output (MIMO) broadband channel. We propose a frequency domain minimum mean square error (MMSE)-based turbo packet combining scheme where all slots received signals and their corresponding channel frequency responses (CFR)s are used to decode the data packet. We also provide an efficient recursive implementation way for the proposed scheme, and show that both its computational complexity and memory requirements are quite insensitive to the number of relays in the system. For the special case of cooperative automatic repeat request (ARQ) systems, we introduce an adaptive packet combining algorithm that enable to reduce the receiver implementation cost. Block error rate (BLER) performance are provided to demonstrate the gains offered by the proposed combining scheme over the conventional soft information-based combining.

In this paper, efficient turbo packet combining for single carrier (SC) broadband multiple-input-multiple-output (MIMO) hybrid-automatic repeat request (ARQ) transmission with unknown co-channel interference (CCI) is studied. We propose a new frequency domain soft minimum mean square error (MMSE)-based signal level combining technique where received signals and channel frequency responses (CFR)s corresponding to all retransmissions are used to decode the data packet. We provide a recursive implementation algorithm for the introduced scheme, and show that both its computational complexity and memory requirements are quite insensitive to the ARQ delay, i.e., maximum number of ARQ rounds. Furthermore, we analyze the asymptotic performance, and show that under a sum-rank condition on the CCI MIMO ARQ channel, the proposed packet combining scheme is not interference-limited. Simulation results are provided to demonstrate the gains offered by the proposed technique.

We address the issue of efficient iterative (turbo) packet combining for broadband space-time coded transmission with hybrid-automatic repeat request (ARQ) over co-channel interference (CCI)-limited multiple-input-multiple-output (MIMO) channel. We introduce a new frequency domain turbo combining scheme where multiple transmissions are combined at the signal level using soft minimum mean square error (MMSE) processing. The proposed technique allows to recursively combine received signal packets in the frequency domain, and does not require to explicitly store signals and channel frequency responses (CFR)s corresponding to multiple ARQ rounds. We analyze both the computational complexity and memory requirements of the proposed scheme and show that are quite insensitive to the ARQ delay, i.e., the maximum number of ARQ rounds. Block error rate (BLER) performance is investigated to examine the gains offered by the new technique.

In this paper, we address the problem of the presence of spatial correlated noise in upstream coordinated DSL systems. The performance of a minimum mean-squared-error (MMSE) iterative receiver structure without whitening the noise is evaluated. A simplified MMSE receiver based on the approximation of matrix inversion in the iterative process is presented. The convergence of the iterative scheme in this scenario is predicted using EXIT charts under realistic transmission conditions.

We propose a single carrier joint frequency domain equalization and interference cancellation (FDE-IC) with diversity combining for different relaying schemes. We consider amplify-and-forward (AF) and ACK/NACK-aided decode-and-forward (DF) modes over multiple-input multiple-output (MIMO) frequency selective relay channels. During the first time slot, the source transmits to both the relay and destination. In the second slot, the relay transmits the signal packet to the destination in the case of AF mode, while in DF the data block is transmitted either by the relay or the source depending on the ACK/NACK feedback. By deriving an equivalent source-relay-destination (S → R → D) channel for the AF mode, we propose an integrated iterative minimum mean square error (MMSE)-FDE-IC-aided transmission combining scheme where reception over multiple slots is viewed as virtual antennas. We also derive the joint combining scheme in the case of ACK/NACK-aided DF. Block error rate (BLER) performance is evaluated for different system settings.

High Speed Uplink Packet Access (HSUPA) is designed to increase the uplink data rate. To reach this goal, a new uplink transport channel, called enhanced dedicated channel (E-DCH), is introduced to the UMTS physical layer. This channel is used in a multicodes transmission principle with very low spreading factors. Furthermore, it supports Hybrid Automatic Repeat reQuest (HARQ), and a shorter 2 ms transmission time interval (TTI) optionally with 10 ms TTI. For determining the expected performance of HSUPA in a multipath channel, the sophisticated signal processing techniques supported by E-DCH channel must be simulated. Especially, the turbo decoding process makes the simulation very prohibitive and CPU-time consuming. In this paper, we propose a simplified simulation methodology which gives an abstraction of the system performance. Computer simulations show that the required CPU-time is significantly reduced.

Hybrid automatic repeat request (HARQ) is one of the main technologies used in HSUPA system to increase the uplink data throughput. Chase combining (CC) and incremental redundancy (IR) are the most known HARQ algorithms. The first provides a time diversity, while the second offers a coding gain. In this paper, we propose a method to increase the chase combining efficiency. In this method, all HARQ transmissions are considered as additional receive antennas, and combined at the chip-level using a linear minimum mean square error (LMMSE). It is shown that with our approach, the Chase combining diversity gain is considerably increased especially in the case of high order modulation.

This paper addresses the issue of efficient turbo packet combining techniques for coded transmission with a Chase-type automatic repeat request (ARQ) protocol operating over a multiple-input multiple-output (MIMO) channel with intersymbol interference (ISI). First of all, we investigate the outage probability and the outage-based power loss of the MIMO-ISI ARQ channel when optimal maximum a posteriori (MAP) turbo packet combining is used at the receiver. We show that the ARQ delay (i.e., the maximum number of ARQ rounds) does not completely translate into a diversity gain. We then introduce two efficient turbo packet combining algorithms that are inspired by minimum mean square error (MMSE)-based turbo equalization techniques. Both schemes can be viewed as low-complexity versions of the optimal MAP turbo combiner. The first scheme is called signal-level turbo combining and performs packet combining and multiple transmission ISI cancellation jointly at the signal-level. The second scheme, called symbol-level turbo combining, allows ARQ rounds to be separately turbo equalized, while combining is performed at the filter output. We conduct a complexity analysis where we demonstrate that both algorithms have almost the same computational cost as the conventional log-likelihood ratio (LLR)-level combiner. Simulation results show that both proposed techniques outperform LLR-level combining, while for some representative MIMO configurations, signal-level combining has better ISI cancellation capability and achievable diversity order than that of symbol-level combining.

This work focuses on signal-level packet combining techniques for coded transmission over co-channel interference (CCI)-limited multiple input multiple output (MIMO) channels with intersymbol interference (ISI). A turbo packet combining algorithm that jointly equalizes multiple transmissions using the concept of virtual antennas is proposed. Block error rate (BLER) performance is investigated to show the great potential of the introduced technique for many scenarios.

In this paper, we introduce two packet combining schemes with low complexity minimum mean square error (MMSE) turbo equalization for single user multi-code CDMA transmission over a broadband multiple input multiple output (MIMO) channel. The first scheme considers each transmission as an additional set of virtual receive antennas and combines multiple transmissions using a frequency domain chip level turbo equalizer. The second scheme performs frequency domain turbo equalization separately for each transmission then combines filter outputs. A comparative study in terms of performance and complexity is conducted to show the great potential of packet combining with integrated turbo equalization.

This paper extends the geometrical one-ring multi- input multi output (MIMO) channel model for a frequency flat fading process in a land mobile radio system with respect to frequency-selectivity. Our approach enables the design of efficient simulation models for space-time MIMO channels under isotropic scattering conditions for any numbers of transmit and receive antennas. A simulation study is performed into the space- time cross correlation to gain understanding of the modification of some relevant parameters. A conventional four transmit four receive 4 x 4 MIMO radio channel is analyzed.

This paper focuses on the problem of efficient packet combining techniques for coded systems with hybrid automatic repeat request (ARQ) protocols operating over the frequency selective fading multiple input multiple output (MIMO) channel. We introduce a receiver scheme where space-time soft equalization is integrated into the packet combiner. This allows to create at each transmission an additional set of virtual receive antennas, thereby increasing the diversity order of the system. We also propose a second packet combining scheme where equalization is performed separately for each transmission. Iterative channel estimation is also investigated, and a training scheme where the pilot symbols are not retransmitted is introduced. Block error rate (BLER) performance is investigated via computer simulations for both perfect and imprecise channel state information (CSI) at the receiver side for demonstrating the potential of integrated soft equalization-based packet combining for transmission over multipath MIMO channels.

This paper focuses on the problem of detecting multiuser coded space-time signals transmitted over multi-antenna multipath channel, with imprecise channel knowledge in reception. Computationally efficient methods combining soft multiuser interference (MUI) cancellation and minimum mean square error (MMSE) processing are developed for both channel estimation and space-time soft equalization.

High speed downlink packet access (HSDPA) is the major evolution of UMTS downlink. It provides peak data rates up to 10.8 Mbps. This is reached by radio link adaptivity, which includes fast scheduling, adaptive modulation and coding (AMC), and hybrid automatic repeat request (HARQ). The performance of AMC suffers from multipath interference introduced by the channel especially when using 16-QAM modulation. This is because of the variation in bit reliabilities caused by the bit-mapping onto the signal constellation. In this paper, we present a soft iterative multipath interference canceller (MPIC) for suppressing the multipath interference. We also propose to use HARQ Chase combining with the constellation rearrangement technique in joint application with MPIC. This can equalize the variation of bit reliabilities by using different mapping rules over HARQ transmissions. It is proven that the performance of adaptive modulation and coding is significantly improved after only two HARQ transmissions.

This paper presents a new space-time iterative technique for equalizing multiple input multiple output (MIMO) channels with unknown co-channel interference (UCCI). The proposed method is based on a successive interference cancellation (SIC) technique derived under a minimum mean square error (MMSE) formalism. Computer simulations show that attractive performance can be achieved even with simple coding schemes

This paper addresses the problem of soft equalization and detection of coded MIMO symbols transmitted over a frequency selective fading channel. We develop a low-complexity MMSE-based approach where both interference cancellation and computation of the soft information are performed in a successive fashion. Monte-Carlo simulations demonstrate attractive performance even under the presence of imprecise channel state information (CSI) at the receiver.

In this paper we propose an image coding scheme based on Block Turbo Codes (BTC) for protecting SPIHT coded images transmitted over wireless channels. An Unequal Error Protection (UEP) scheme using different product codes is also presented. The optimization of the UEP scheme under a transmission budget constraint is investigated. Performance of the proposed system are first evaluated over Gilbert-Elliott (GE) channels. They are then compared to the well-known system of Sherwood and Zeger, through numerical simulations over a single path Rayleigh fading channel. Then, we present an optimized mobile image transmission framework involving a multiuser asynchronous DS-CDMA transmission system over Rayleigh multipath channels. Simulation results for the 512x512 Lena image, transmitted over the ITU Vehicular A channel, show that a significant gain in PSNR is obtained by using the SIC/RAKE multiuser detector in comparison with a conventional detection by the RAKE receiver. Furthermore, performance are also improved when introducing the UEP scheme.

A new method for coding generic audio signals at 64 kbit/s in the 20-15000 Hz bandwidth with a low delay is presented. It combines subband coding, low delay CELP algorithm and cascaded filterbanks. Our earlier works (1996) show that, when using an equal bit rate on each subband, the resulting audio quality was not appropriate. We propose a new technique based on lattice quantization to avoid the search complexity of the statistical vector quantization. It allows an adaptive bit rate allocation in each subband. Experimental results assessing the validity of the proposed method are also presented.

International audience

The code excited linear prediction coder (CELP) makes it possible to synthesize good quality speech at low bit rates. In such a case, speech quality mainly depends on spectral envelope design accuracy. Different kinds of parameters belonging to the parametrical domain (linear prediction coefficients.

Presents the development of the RGSKA/spl epsi/, a new algorithm for designing vector quantizers. The main features of this algorithm are the following: due to its stochastic nature it avoids being trapped in poor local minima; initial codebook is not needed; the codevectors move away from the gravity centre of the training vectors towards their final position; source coding and channel coding are jointly optimized to obtain a codebook robust against different levels of the transmission noise; The resulted codebook always performs as well or even better than existing codebooks designed for noisy or noiseless channels; the computational complexity is only slightly higher than that of the most widely used K-means algorithm; the bootstrap sampling technique can be successfully applied in case of a large training set; the method is suitable for parallel implementation.

International audience

International audience

International audience

International audience

International audience

International audience