Reconfigurable Intelligent Surfaces (RIS) appear as a promising solution to combat wireless channel fading and interferences. However, the elements of the RIS need to be properly oriented to boost the data transmission rate. In this work, we propose a new strategy to adaptively configure the RIS without Channel State Information (CSI). Our goal is to minimize the number of RIS configurations to be tested to find the optimal one. We formulate the problem as a stochastic shortest path problem, and use Q-Learning to solve it.

This paper proposes a new approach for Machine Learning (ML)-based beam alignment, for a single radio-frequency chain millimeter-wave (mmW) MIMO transmitter (Tx) and receiver (Rx), with massive antennas. Assuming (massive) codebooks of possible beams at Tx and Rx, we propose to sound a very small subset of beams from the Tx/Rx codebooks. We then use the SNR of the (subset of) sounded beams, to learn two ML models: Matrix Factorization (MF), and Nonnegative MF. Furthermore, we derive the update eqts for two optimization methods to solve the MF/Nonnegative MF optimization problems. While the first optimization method is shown to converge (and exhibits medium complexity), the second optimization method has negligible complexity (but lacks a convergence guarantee). Our extensive numerical results suggest that by sounding just 10% of the beams from the (large) Tx and Rx codebooks, MF and Nonnegative MF are able to predict the SNR of the remaining beams, with extremely high accuracy. This observation holds as the Tx/Rx codebook sizes vary from 64×64 to 1024 × 1024.

The growing number of Internet of Thing (IoT) and Ultra-Reliable Low Latency Communications (URLCC) use cases in next generation communication networks calls for the development of efficient Forward Error Correction (FEC) mechanisms. These use cases usually imply using short to mid-sized information blocks and requires low-complexity and/or fast decoding procedures. This paper investigates the joint learning of short to mid block-length coding schemes and associated Belief-Propagation (BP) like decoders using Machine Learning (ML) techniques. An interpretable auto-encoder (AE) architecture is proposed, ensuring scalability to block sizes currently challenging for ML-based linear block code design approaches. By optimizing a coding scheme w.r.t. the targeted decoder, the proposed system offers a good complexity/performance trade-off compared to various codes from literature with length up to 128 bits.

This paper investigates the uplink reception in the cloud radio access network (C-RAN) with finite-capacity fronthaul links. The latter is an emerging network that transfers the computing load from the radio heads (RHs) to the central processor (CP) unit. Due to the prohibitive complexity of computations, the most efficient uplink C-RAN schemes are challenging to be implemented in practical systems. Using deep neural networks (DNNs), we propose a new and low complex distributed processing for uplink C-RAN subject to some quantification rules. The objective of our architecture, called TDNet, is to optimize the processing jointly at the RHs and the CP side. Our goal is not to solve signal detection in multi-antenna systems. Instead, our work aims to find a helpful transformation scheme at the RH side before quantization. A correspondent decoding scheme at the CP side considers the quantization scheme. Inspired by the projected gradient descent algorithm, TDNet is designed as a distributed DNN with sparse connections. Numerical results are provided and show that our scheme outperforms linear receivers such as the zero-forcing (ZF). It also achieves near-optimal performance compared to the sphere decoder (SD) algorithm, especially for a low-to-moderate number of quantization bits.

This paper demonstrates the advantage of utilizing lattice codes in uplink sectored cellular networks employing Cloud radio access network (C-RAN). We give a novel decomposition of the cellular network into interfering but non-overlappping clusters. We employ compute-and-forward (CoF) and quantized-CoF (QCoF) for each cluster by allowing each sector to compute best equation and to treat out-of-cluster as noise. CoF may perform poorly due to rank deficiency of the integer coefficient matrix. This is solved using QCoF, which shows highly favorable performance in terms of average sum-rate. To reduce implementation complexity of the proposed scheme for QCoF, we investigate the effect of employing less number of nested lattices than number of users, i.e., some users apply the same lattice code, and hence, the rate of the lattice code is chosen as the minimum of rates of these users. Simulation results show that the sum rate degradation of QCoF due to using fewer nested lattices is not significant especially if the fronthaul capacity is limited. It is also shown that QCoF with reduced number of nested lattices outperforms CoF even if one lattice code is employed for all cluster users.

Communication using orbital angular momentum (OAM) modes has recently received a considerable interest in free space optical (FSO) communications. Propagating OAM modes through free space may be subject to atmospheric turbulence (AT) distortions that cause intermodal crosstalk and power disparities between OAM modes. In this paper, we are interested in multiple-input multiple-output (MIMO) coherent FSO communication systems using OAM multiplexing. We propose space-time (ST) coding at the transmitter to enhance the bit error rate (BER) performance against atmospheric turbulence. Through numerical simulations, we show performance improvement thanks to ST coded schemes for different MIMO dimensions. Furthermore, we derive an analytical expression for the error probability upper bound of the ST coded OAM FSO channel affected by atmospheric turbulence. The theoretical error probability is compared with Monte Carlo simulations and a good agreement is observed.

A modified sphere decoding (SD) scheme is proposed for multiple-input multiple-output (MIMO) communication systems in this paper. The contribution of the paper includes the introduction of a systematic approach to sphere radius design and control based on Deep Neural Networks (DNNs) as well as the complexity advantage yielded by the proposed scheme. The learning model is introduced to predict the number of lattice points inside the sphere with some radius. Since this number is cleverly learnt by a neural network (NNW), the SD updates the radius until expecting a small number of points and then starts the search hypersphere, which greatly reduces the computational complexity. We show through simulation that for high dimensional MIMO systems the number of lattice points highly reduces in the new SD algorithm, which leads to a complexity only 3 times of the MMSE decoder complexity.

This paper investigates the per user Degrees of Freedom (DoF) for uplink in sectored cellular networks which employ C-RAN architecture. The network consists of N base stations (BS) and K ≤ N base band unit (BBU) pools. The communication between BSs and BBU pools occurs by means of finite-capacity fronthaul links. In the network, the computing units (BBU pools) have limited processing capacity. We propose a lower bound and cut-set bound on the per user DoF, where both of them are functions of processing capacity, the BBU pool/BS ratio r and fronthaul capacity. The achievability scheme is based on dividing the network into clusters, where some of the mobile users are silenced to provide isolation between them. It is shown, by simulations, that cut-set bound are attained for several cases and the achievability gap is very small for fronthaul capacity prelog μF ≤ 2M, where M is the number of antennas at both transmitter and receiver.

In this paper, we analyze the performance of coded and uncoded spatial modulations over multi-mode fiber optic channels with the mode-dependent loss (MDL) under the maximum likelihood (ML) and zero-forcing (ZF) detection schemes. We focus on the multi-dimensional modulations that satisfy certain orthogonality criteria such as the Threaded Algebraic Space-Time (TAST) codes. In particular, we link the post-detection signal-to-noise ratio (SNR) to the orthogonality defect factor (ODF) of the equivalent channel matrix by deriving their closed-form expressions as well as characterizing their statistical properties. Using the post-detection SNR and ODF properties, we develop upper and ad-hoc tight bounds on the error probabilities, which illustrate how these “orthogonal” spatial modulations mitigate the MDL under both the ML and ZF detection schemes. The obtained properties also allow us to propose a modification to the detection algorithm such that it still achieves an essentially optimal performance but at a much smaller cost than exhaustive or tree search algorithms. The theoretical results are validated numerically and by simulations.

This paper derives upper and lower bounds on the secrecy capacity-memory tradeoff of a wiretap erasure broadcast channel (BC) with Kw weak receivers and Ks strong receivers, where weak receivers and strong receivers have the same erasure probabilities and cache sizes, respectively. The lower bounds are achieved by the schemes that meticulously combine joint cache-channel coding with wiretap coding and key-aided onetime pads. The presented upper bound holds more generally for arbitrary degraded BCs and arbitrary cache sizes. When only weak receivers have cache memories, upper and lower bounds coincide for small and large cache memories, thus providing the exact secrecy capacity-memory tradeoff for this setup. The derived bounds further allow us to conclude that the secrecy capacity is positive even when the eavesdropper is stronger than all the legitimate receivers with cache memories. Moreover, they show that the secrecy capacity-memory tradeoff can be significantly smaller than its non-secure counterpart, but it grows much faster when cache memories are small. This paper also presents a lower bound on the global secrecy capacity-memory tradeoff where one is allowed to optimize the cache assignment subject to a total cache budget. It is close to the best known lower bound without secrecy constraint. For small total cache budget, the global secrecy capacity-memory tradeoff is achieved by assigning all the available cache memory uniformly over all the receivers if the eavesdropper is stronger than all the legitimate receivers, and it is achieved by assigning the cache memory uniformly only over the weak receivers if the eavesdropper is weaker than the strong receivers.

Sphere Decoder (SD) is a widely used and studied decoder for MIMO systems. As the number of antenna grows, SD becomes computationally intensive. To overcome this disadvantage, this paper proposes an improvement of SD consisting in an efficient radius update strategy using dichotomy. With no performance loss, the resulting algorithm allows a considerable complexity saving compared to conventional SD, up to 90% in some scenarios. This gain is due to the decrease in the number of visited lattice points in the spherical region shown to be logarithmic as a function of the SNR. We provide simulation results and a theoretical proof of the expected complexity reduction.

Approaching the capacity limits of single-mode fiber based optical transmission systems, new fibers supporting the propagation of up to six orthogonal spatial modes, called few-mode fibers, stand as promising candidates for future high-capacity systems. Extensive research is being carried out to further increase the number of modes to multiplex more data. This technique is known as spatial division multiplexing (SDM). However, the co-existence of modes in the same space leads to inevitable modal crosstalk that may induce a loss of their orthogonality as well as power disparities. This phenomenon is called mode dependent loss (MDL) and mainly arises from optical components such as few-mode amplifiers. Although optical solutions were suggested to reduce MDL by inserting mode scramblers or using fibers with strong modal coupling, MDL was unfortunately not completely removed. In this work, we propose a DSP solution based on Space-Time (ST) coding along with OFDM, originally designed for multi-antenna channels, to mitigate MDL in SDM systems. We show that a combination of ST coding at the transmitter and an optimal distribution of mode scramblers in the optical link can completely absorb the penalties induced by important levels of MDL in 6-mode SDM systems. Later on, we address the complexity and scalability of the ST-coding solution and propose a sub-optimal decoding scheme that keeps the MDL-induced penalty low while considerably reducing the decoding complexity.

In this work, we propose a novel sequential decoder for MIMO systems termed the Zigzag Stack decoder. The algorithm combines the search strategy of the Stack decoder with the Schnorr-Euchner zigzagging method. We show that the Zigzag Stack provides ML performance with a reduced complexity compared to the original Stack decoder and a complexity reduction of 40% in average over the commonly used sphere decoder.

We address in this paper decoding aspects of the Compute-and-Forward (CF) physical-layer network coding strategy. Under the CF framework, encoders use a special class of nested lattice codes and decoders are based on suboptimal minimum distance decoding of unknown performance gap with respect to optimal decoders. In this work, we develop and assess the performance of novel decoding algorithms for CF operating in the multiple access channel. Starting with the Gaussian channel, we investigate the maximum a posteriori (MAP) decoder. We derive a novel MAP decoding metric and develop practical decoding algorithms shown numerically to outperform the original one. For the fading channel, we analyze the ML decoder for integer-valued lattices and develop a novel Diophantine approximation-based near-ML decoding algorithm shown numerically to outperform the original CF decoder in the 1-D case using Z lattices.

Coherent detection with Polarization Multiplexing (PolMux) is the most promising technique for future optical fiber transmission systems. However, the optical channel suffers from non-unitary impairments known as Polarization Dependent Loss (PDL). Space-Time coding, originally designed for wireless Rayleigh fading channels, was proven to be capable of mitigating PDL. Coding gains of ST codes were evaluated through simulations and experiments that showed differences in their performance on the optical channel and on the wireless channel. In this paper, we derive an upper bound of the pairwise error probability of an optical channel considering the PDL effect. This upper bound explains the performance of ST codes used to mitigate PDL and yields the design criterion that a code should satisfy in order to completely mitigate PDL.

Integer Forcing (IF) architecture has been recently proposed to design linear receivers in MIMO systems. Research works show the promise of this architecture from a capacity achieving perspective. However, it is not totally understood how to select IF coefficient matrix and if the promised theoretical gain of the resulting receivers is attainable in practical settings. We try in this work to fill the gap between theory and practice: we propose algorithms to select optimal IF receiver parameters that lead to the maximization of the total achievable rate. We propose an implementation of an IF-based MIMO system considering a practical scenario where lattice codes are used. Experimental studies are carried out to evaluate the error rate performance of the proposed algorithms and compare them to traditional linear receivers. Our proposed implementation shows that the theoretical potential of the IF receivers is achievable even with finite-length lattice codes.

In this paper, we propose a practical implementation of the Dynamic Decode and Forward (DDF) protocol based on rateless codes and HARQ. We define the macro diversity order of a transmission from several intermittent sources to a single destination. Considering finite symbol alphabet used by the different sources, upper bounds on the achievable macro diversity order are derived. We analyse the diversity behavior of several relaying schemes for the DDF protocol, and we propose the Patching technique to increase both the macro and the micro diversity orders. The coverage gain for the open-loop transmission case and the spectral efficiency gain for the closed loop transmission case are illustrated by simulation results.

In this paper, a full duplex relay using a Dynamic Decode and Forward (DDF) protocol is considered for improving the performance of multiple source-destination pairs interfering one on each other. A relay precoder is optimized as a function of the symbols correctly decoded by the relay in order to improve the channel capacity. Furthermore, a DDF-Patching technique allows for increasing the number of precoded symbols by the relay and providing highly improved performance in interference-limited scenarios.

Perfect space-time codes (STC) are optimal codes in their original construction for multiple-input multiple-output (MIMO) systems. Based on cyclic division algebras (CDA), they are full-rate, full-diversity codes, have non-vanishing determinants (NVD) and hence achieve diversity-multiplexing tradeoff (DMT). In addition, these codes have led to optimal distributed space-time codes when applied in cooperative networks under the assumption of perfect synchronization between relays. However, they lose their diversity when delays are introduced and thus are not delay-tolerant. In this paper, using the cyclic division algebras of perfect codes, we construct new codes that maintain the same properties as perfect codes in the synchronous case. Moreover, these codes preserve their full-diversity in asynchronous transmission.

When distributed cooperative nodes are communicating with a destination, the received signal can be asynchronous due to the propagation or processing delays. This can destroy the space time block code properties designed initially for synchronous case. In this paper, a new construction method of bounded delay tolerant codes is presented. These new codes preserve the full diversity with optimal rates if the relative delays are in a designed delay tolerance interval. The general design method is based on the concatenation and permutation of optimal synchronous space time block codes and works for an arbitrary number of transmitting and receiving antennas. Examples of bounded delay tolerant codes based on the Alamouti code, the Golden code and Threaded Algebraic Space-Time (TAST) codes are given. Theoretical proofs are used to show that the new codes respect the design criteria. Simulation results manifest better error rate performance of the new codes compared to other known delay tolerant codes.

In distributed antenna networks, the received signal from different transmitters can be asynchronous due to the processing or propagation delays. This destroys the space time code properties designed initially for synchronous case. We introduce, in this paper, a new design method to construct optimal-rate delay-tolerant codes from existing synchronous codes for a certain number of delay profiles that can exist in the network. Some construction examples based on optimal known codes are proposed and it is shown that they achieve full diversity for synchronous and some asynchronous cases. Their performance is compared to other delay tolerant codes.

Polarization effects may induce severe performances degradation in polarization multiplexed optical fiber transmissions. Those systems can be seen as 2×2 multi-antennas systems as the emitted polarizations can be considered as 2 input signals and the received polarizations as 2 output signals. Therefore, Space-Time code can be used to take benefit of this configuration and enhance the transmission performances but they have to be combined with optical OFDM to suppress the fiber dispersion and allow their decoding. In wireless 2×2 multi-antennas systems, the Golden and the Silver code are respectively the two best Space- Time codes so, we propose to use those two codes on polarization multiplexed systems. The performances of the Space-Time codes on the optical fiber channel are different than on the wireless channel. Simulations show than the Silver code outperforms the Golden code. Nevertheless, we also show that Space-Time coding can dramatically mitigate the polarization dependent loss (PDL) impairments.

In this paper, we consider a broadcast transmission from a source to multiple destinations with an OFDM-based system. In order to improve the broadcast services of a cellular system, we consider the use of relays with Dynamic Decode and Forward protocols allowing the source to ignore the existence of relays in the system. A new algorithm executed at the relay is proposed. It allows for maximizing the diversity order at the destinations side by selecting the best relaying protocol and modulation size as function of the relay correct decoding time. No feedback is assumed on any link between the source, relays and destinations.

In this paper, we propose Patched Distributed Space-Time Block Codes (DSTBC) for the Dynamic Decode and Forward (DDF) Relaying protocol, in which the relay transmits combination of information from the first and second phase of the DDF protocol, and the destination makes a linear combination of symbols received in the two phases. Thus, from the error correcting code point of view, the number of coded bits seeing a diversity-one channel reduces proportionnally as the number of symbols sent by the relay increases, which is not the case with known schemes. In other words, the length of the phase two of the DDF protocol needed to achieve full diversity can be reduced with respect to known schemes. Three examples of Patched DSTBC are presented, the Patched Alamouti, the Patched Golden Code and the Patched Silver Code whose outage analyses prove the diversity enhancement offered by the proposed scheme.

Lattice reduction algorithms, such as the LLL algorithm, have been proposed as preprocessing tools in order to enhance the performance of suboptimal receivers in MIMO communications. In this paper we introduce a new kind of lattice reduction-aided decoding technique, called augmented lattice reduction, which recovers the transmitted vector directly from the change of basis matrix, and therefore doesn't entail the computation of the pseudo-inverse of the channel matrix or its QR decomposition. We prove that augmented lattice reduction attains the maximum receive diversity order of the channel; simulation results evidence that it significantly outperforms LLL-SIC detection without entailing any additional complexity.

For distributed antennas based communications, the received signal from different sources can be asynchronous due to the propagation or processing delays. This can destroy the space time block code properties designed initially for synchronous case. In this paper, we introduce the delay-diversity tradeoff showing that it is possible to preserve the maximum diversity of a code without reducing its rate as long as the relative delays are in a designed delay tolerance interval. New delay tolerant block codes are proposed and it is shown that they achieve full diversity and optimal rates for both synchronous and asynchronous cases. Their performances are compared to other delay tolerant codes.

Perfect Space-Time Codes (STC) are full-rate, full-diversity codes originally proposed for Multiple Input Multiple Output (MIMO) systems. Based on Cyclic Division Algebras (CDA), they have non-vanishing determinants and hence achieve the Diversity-Multiplexing Tradeoff (DMT). In addition, these codes have led to optimal distributed Space-Time Codes when applied in cooperative networks under the assumption of perfect synchronization between relays. However, they lose their diversity when delays are introduced and thus are not delay-tolerant. In this paper, using the cyclic division algebras of perfect codes, we construct new codes that maintain the same properties as perfect codes in the synchronous case. Moreover, these codes preserve their full-diversity in asynchronous transmission.

In this paper, a low-complexity protocol for the K-parallel-path multihop channel is proposed. This protocol is based on a smart path selection combined with a small space-time code. It is proven to achieve full rate and full diversity, and to reach the optimum diversity-multiplexing gain tradeoff d*(r)=K(1-r)+. Some implementation issues such as the frame length or interferences between paths are further discussed.

Lattice reduction algorithms, such as the Lenstra-Lenstra-Lovasz (LLL) algorithm, have been proposed as preprocessing tools in order to enhance the performance of suboptimal receivers in multiple-input multiple-output (MIMO) communications. A different approach, introduced by Kim and Park, allows to combine right preprocessing and detection in a single step by performing lattice reduction on an v{augmented channel matrix}. In this paper we propose an improvement of the augmented matrix approach which guarantees a better performance. We prove that our method attains the maximum receive diversity order of the channel. Simulation results evidence that it significantly outperforms LLL reduction followed by successive interference cancellation (SIC) while requiring a moderate increase in complexity. A theoretical bound on the complexity is also derived.

In this paper we introduce a new right preprocessing method for the decoding of 2 times 2 algebraic space-time codes, called algebraic reduction, which exploits the multiplicative structure of the code. The principle of the new reduction is to absorb part of the channel into the code, by approximating the channel matrix with an element of the maximal order of the code algebra. We prove that algebraic reduction attains the receive diversity when followed by a simple zero-forcing (ZF) detection. Simulation results for the golden code show that using minimum mean squared error generalized decision feedback equalization (MMSE-GDFE left preprocessing), algebraic reduction with simple ZF detection has a loss of only 3 dB with respect to optimal decoding.

The Silver code has captured a lot of attention in the recent past, because of its nice structure and fast decodability. In their recent paper, Hollanti et al. show that the Silver code forms a subset of the natural order of a particular cyclic division algebra (CDA). In this paper, the algebraic structure of this subset is characterized. It is shown that the Silver code is not an ideal in the natural order but a right ideal generated by two elements in a particular order of this CDA. The exact minimum determinant of the normalized Silver code is computed using the ideal structure of the code. The construction of Silver code is then extended to CDAs over other number fields.

In this paper, we consider the Multiple-Access channel with a non uniform energy distribution among users. We point out that, while a space-time code is optimal for the MAC in a balanced scenario, it could become suboptimal in an unbalanced scenario. No CSI is available at the transmitters that are initially assumed to have different energies. We investigate the use of an adapted coding scheme characterized by an unbalanced energy distribution among the symbols that helps compensating the system's unbalance. Numerical results illustrating the outage probability of the channel as well as the error probability of the proposed coding scheme for different power distributions are provided. We show that this unbalanced code is more appropriate in an unbalanced scenario and that it outperforms the best known coding scheme for the MAC.

In existing MIMO systems, either optimal or sub-optimal decoders can be used according to the required performance. However, the optimal decoders give ML performance but have very high complexity and the sub-optimal decoders give low complexity but poor performance. Moreover for ML decoding, the variable decoding time at a fixed SNR for the different channel realizations and also the big gap in the complexity between low and high SNRs represent a critical point for practical implementation. We propose here an adaptive decoder that allows to switch between optimal and sub-optimal decoders according to the channel realization and the system specifications. This decoder offers an almost constant complexity while keeping good performance.

Classical ML decoders for multiple input multiple output (MIMO) systems like the sphere decoder, the Schnorr-Euchner algorithm, the Fano and the stack decoders suffer from high complexity for high number of antennas and large constellation sizes. In this paper, we propose the use of parallel processing for stack decoding, to decode signals transmitted on linear MIMO channels to reduce time consumption of hardware architecture. It will be shown that the parallel stack decoder allows a 50% less of run time compared to the classical stack decoder.

In this paper, block-coded modulation is used to design a 2 times 2 multiple-input multiple-output (MIMO) space-time code for slow fading channels. The golden code is chosen as the inner code; the scheme is based on a set partitioning of the golden code using two-sided ideals whose norm is a power of two. In this case, a lower bound for the minimum determinant is given by the minimum Hamming distance. The description of the ring structure of the quotients suggests further optimization in order to improve the overall distribution of determinants. Simulation results show that the proposed schemes achieve a significant gain over the un-coded golden code.

In a broadcast channel with random packet arrival and transmission queues, the stability of the system is achieved by maximizing a weighted sum rate capacity with suitable weights that depend on the queue size. The weighted sum rate capacity using Dirty Paper Coding (DPC) and Zero Forcing (ZF) is asymptotically equivalent to the weighted sum capacity over parallel single-channels. In this paper, we study the Diversity Multiplexing Tradeoff (DMT) of the fading broadcast channel under a fixed weighted sum rate capacity constraint. The DMT of both identical and different parallel weighted MISO channels is first derived. Finally, we deduce the DMT of a broadcast channel using DPC and ZF precoders.

We consider a block coded modulation scheme for a 2 times 2 MIMO system over slow fading channels, where the inner code is the Golden Code. The scheme is based on a set partitioning of the Golden Code using two-sided ideals. A lower bound for the minimum determinant is given by the minimum Hamming distance. Performance simulations show that our GCRS schemes achieve a significant gain over the uncoded Golden Code.

In this paper, the selective time division multiple access (S-TDMA) strategy is studied in the downlink channel. This strategy consists in transmitting data to the user with the largest capacity. The diversity and multiplexing gains that can be achieved by this sub-optimal strategy are evaluated and then compared to the optimal gains over the broadcast channel. Codes construction is then proposed to achieve the diversity multiplexing tradeoff (DMT) of the S-TDMA. These codes are extended to the scenario of cooperating asynchronous broadcasting base stations where new codes that are suitable for this scenario are proposed and analyzed.

In this paper, we consider the isotropic fading broadcast channel. This channel refers to the case when no directional information is available at the transmitter side, and was studied by Jafar et al in. It was shown that the isotropic vector broadcast channel (BC-V) can be reduced to an equivalent scalar broadcast channel (BC-S). It is well known from [2]http://www.pimrc2008.org/ that BC-S is degraded in the same order as the channel magnitude. This implies that the optimal strategy that maximizes the sum capacity for BC-S and BCV consists on allocating the whole power to the strongest user. Based on these results, we derive in this paper the diversity multiplexing tradeoff (DMT) of the isotropic fading BC-S and BC-V, and we propose optimal schemes that achieve these DMT.

In this work, we explore the introduction of distributed space-time codes in decode-and-forward (DF) protocols. We propose a new Incomplete DF protocol, based on a partial decoding at the relays. This strategy allows the new protocol to bring both full diversity and full symbol rate. Outage probabilities and simulation results show that the Incomplete DF protocol has better performance than any existing DF protocol and than NAF protocols using the same space-time codes.

In this work, we are interested in the decoding of MIMO systems by using sequential decoders. These ones consist on tree search algorithms and were originally used to decode binary codes. They were rediscovered and adapted to MIMO systems by Murugan and al. We are interested here in the stack decoder. We propose a new sequential decoder that we call the spherical-bound stack decoder (SB-Stack) combining the stack decoder search strategy and the sphere decoder search region. We show that the SB-stack achieves the ML performance with a reduced complexity compared to the original stack and the sphere decoder. Furthermore by introducing the bias parameter the SB-stack offers a range of performances going from ML to ZF-DFE with proportional complexities.

In this work we propose a new amplify-and-forward (AF) protocol and a new decode-and-forward (DF) protocol based on the Alamouti space-time (ST) code, chosen because of its decoding simplicity. We also apply a new selection criterion for AF and DF protocols that improves their performance and solves the problem of bad performance at low SNR. Finally, we apply the Alamouti AF and DF protocols to a "non-line-of-sight" (NLOS) scheme to bring diversity. Outage probabilities and simulation results show that at low spectral efficiency, in spite of their rate of 1/2 symbol per channel use, these Alamouti AF and DF protocols have better performance than the non-orthogonal AF (NAF) protocol.

In this work, we propose an amplify-and- forward (AF) protocol based on a new selection criterion, a function of the instantaneous capacities of all possible transmission schemes (with or without cooperation). The outage probability and the simulation results show that the new Adaptive AF protocol has better performance than the best known AF protocol (NAF). Moreover, this protocol solves the problem of the bad performance of NAF at low SNR. We also make a relay-selection to obtain a better diversity-order and then better performance.

In this paper, linear precoding for non-orthogonal space time block codes (STBC) is investigated. A theoretical model of spatial correlation with a Laplacian distribution of AOA is first derived. The design of the precoder is based on the choice of the codeword error matrix according to a criterion. We propose here a new criterion based on the system outage probability to select the suitable codeword error matrix allowing to move rapidly from one diversity order to the next. Codeword selection points out the importance of the determinant and the eigenvalues of the error matrices. The proposed method is applied to the non-orthogonal optimal STBC : 2 times 2 golden code and 4 times 4 perfect code.

The problem of designing space-time codes on the MIMO quasi-static channel have received considerable attention these last years. We now know how to design perfect space-time block codes, that is linear information preserving codes achieving the diversity-multiplexing gain (D-M) tradeoff (F. Oggier et al., 2004) (P. Elia et al., 2005). Recent standards using multiple antennas terminals such as IEEE 802.11n or IEEE 802.16e, for example, are based on OFDM. By using interleaving, such OFDM systems can be seen as parallel MIMO quasi-static channels. We propose, here, new perfect space-time block codes for parallel MIMO channels

In this paper, we propose a new MIMO-HSDPA transmission scheme with two transmit and two receive antennas, using an optimal Space-Time block code: the golden code. This code has a full rate, a full diversity, achieves the Diversity- Multiplexing gain tradeoff and preserves the mutual information. The proposed scheme is compared to the RCMPD a scheme which has also a full rate and a full diversity. The major disadvantage of the later is the generation of the multiple access interference (MAI) even on a flat fading channel. Simulation results show that the proposed scheme has better performances specially for high spectral efficiency. The RCMPD performance are hardly affected by the MAI.

In this paper, we introduce the notion of perfect space-time block codes (STBCs). These codes have full-rate, full-diversity, nonvanishing constant minimum determinant for increasing spectral efficiency, uniform average transmitted energy per antenna and good shaping. We present algebraic constructions of perfect STBCs for 2, 3, 4, and 6 antennas

In this paper, the Golden code for a 2/spl times/2 multiple-input multiple-output (MIMO) system is presented. This is a full-rate 2/spl times/2 linear dispersion algebraic space-time code with unprecedented performance based on the Golden number 1+/spl radic/5/2.

In this paper we present the Golden code for a 2times2 MIMO system. This is a full-rate 2times2 linear dispersion algebraic space-time code with unprecedented performance based on the Golden number 1+radic5/2

We propose an algebraic framework for studying coherent space-time codes, based on arithmetic lattices on central simple algebras. For two transmit antennas, this algebra is called a quaternion algebra. For this reason, we call these lattices quaternionic lattices. The design criterion is the one described by V. Tarokh et al. (see IEEE Trans. Inf. Theory, vol.44, p.744-65, 1998).