Demo: Non-classic Interference Alignment for Downlink Cellular Networks

Our demo aims at proving the concept of a recent proposed interference management scheme that reduces the inter-cell interference in downlink without complex coordination, known as non-classic interference alignment (IA) scheme. We assume a case where one main Base Station (BS) needs to serve three users equipments (UE) while another BS is causing interference. The primary goal is to construct the alignment scheme ; i.e. each UE estimates the main and interfered channel coefficients, calculates the optimal interference free directions dropped by the interfering BS and feeds them back to the main BS which in turn applies a scheduling to select the best free inter-cell interference directions. Once the scheme is build, we are able to measure the total capacity of the downlink interference channel. We run the scheme in CorteXlab ; a controlled hardware facility located in Lyon, France with remotely programmable radios and multi-node processing capabilities, and we illustrate the achievable capacity gain for different channel realizations.Comment: Joint NEWCOM/COST Workshop on Wireless Communications JNCW 2015, Oct 2015, Barcelone, Spain. 201

Réduction d'interférence dans les systèmes de transmission sans fil

Wireless communications have known an exponential growth and a fast progress over the past few decades. Nowadays, wireless mobile communications have evolved over time starting with the first generation primarily developed for voice communications, and reaching the fourth generation referred to as long term evolution (LTE) that offers an increasing capacity and speed using a different radio interface together with core network improvements. Overall throughput and transmission reliability are among the essential measures of service quality in a wireless system. Such measures are mainly subjected to interference management constraint in a multi-user network. The interference management is at the heart of wireless regulation and is essential for maintaining a desirable throughput while avoiding the detrimental impact of interference at the undesired receivers. Our work is incorporated within the framework of interference network where each user is equipped with single or multiple antennas. The goal is to resolve the challenges that the communications face taking into account the achievable rate and the complexity cost. We propose several solutions for the precoding and decoding designs when transmitters have limited cooperation based on a technique called Interference Alignment. We also address the detection scheme in the absence of any precoding design and we introduce a low complexity detection scheme based on the sparse decomposition.Les communications mobiles sans fil ont connu un formidable essor au cours des dernières décennies. Tout a commencé avec les services vocaux offerts par les systèmes de la première génération en 1980, jusqu¿aux systèmes de la quatrième génération aujourd¿hui avec des services internet haut débit et un accroissement du nombre d¿utilisateurs. En effet, les caractéristiques essentielles qui définissent les services et la qualité de ces services dans les systèmes de communication sans fil sont: le débit, la fiabilité de transmission et le nombre d¿utilisateurs. Ces caractéristiques sont fortement liées entre elles et sont dépendantes de la gestion des interférences entre les différents utilisateurs. Les interférences entre-utilisateurs se produisent lorsque plusieurs émetteurs, dans une même zone, transmettent simultanément en utilisant la même bande de fréquence. Dans cette thèse, nous nous intéressons à la gestion d¿interférence entre utilisateurs par le biais de l¿approche d¿alignement d¿interférences où la coopération entre utilisateurs est réduite. Aussi, nous nous sommes intéressés au design d¿un récepteur où l¿alignement d¿interférences n¿est pas utilisé et où la gestion des interférences est réalisée par des techniques de décodage basées sur les décompositions parcimonieuses des signaux de communications. Ces approches ont conduit à des méthodes performantes et peu couteuses, exploitables dans les liens montant ou descendant

Interference alignment for a multi-user SISO interference channel

International audienceOur work addresses the single-input single-output interference channel. The goal is to show that although interference alignment is suboptimal in the finite power region, it is able to achieve a significant overall throughput. We investigate the interference alignment scheme proposed by Choi et al. (IEEE Commun. Lett. 13(11): 847-849, 2009), which achieves a higher multiplexing gain at any given signal dimension than the scheme proposed by Cadambe and Jafar (IEEE Trans. Inform. Theory 54(8), 2008). Then, we try to modify the IA design in order to achieve enhanced sum-rate performance in the practical signal-to-noise ratio (SNR) region. Firstly, we introduce a way to optimize the precoding subspaces at all transmitters, exploiting the fact that channel matrices in the interference model of a single-input single-output channel are diagonal. Secondly, we propose to optimize jointly the set of precoder bases within their associated precoding subspaces. To this end, we combine each precoder with a new combination precoder, and this latter seeks the optimal basis that maximizes the network sum rate. We also introduce an improved closed-form interference alignment scheme that performs close to the other proposed schemes

Low-complexity detector for very large and massive MIMO transmission

International audienceMaximum-Likelihood (ML) joint detection has been proposed as an optimal strategy that detects simultaneously the transmitted signals. In very large multiple-input-multiple output (MIMO) systems, the ML detector becomes intractable due the computational cost that increases exponentially with the antenna dimensions. In this paper, we propose a relaxed ML detector based on an iterative decoding strategy that reduces the computational cost. We exploit the fact that the transmit constellation is discrete, and remodel the channel as a MIMO channel with sparse input belonging to the binary set {0, 1}. The sparsity property allows us to relax the ML problem as a quadratic minimization under linear and l1-norm constraint. We then prove the equivalence of the relaxed problem to a convex optimization problem solvable in polynomial time. Simulation results illustrate the efficiency of the low-complexity proposed detector compared to other existing ones in very large and massive MIMO context

Interference alignment: improved design via precoding vectors

International audienceThe degree of freedom of the Single Input Single Output (SISO) fading interference channel is asymptotically upperbounded by K/2. This upperbound can be achieved using the Interference Alignment approach (IA), proposed by Cadambe et al.. In this work, a new optimized design of the IA scheme is presented. It involves introducing, for each user, a combination matrix so as to maximize the sum rate of the network. The optimal design is obtained via an iterative algorithm proposed in the K-user IA network, and a convergence to a local optimum is achieved. Numerical results enable us to evaluate the performance of the new algorithm and to compare it with other designs

Formation de voie pour la maximisation du débit dans les schémas d’alignement d’interférence

National audienceDans ce papier, nous traitons le problème de la maximisation du débit d'un système multi-utilisateurs, utilisant un schéma d'alignement d'interférence sur un canal à interférence, pour des valeurs de rapport signal à bruit finies. Nous définissons des matrices de changement de base des précodeurs élémentaires qui préservent l'alignement d'interférence et maximisent le débit global en fonction du récepteur utilisé. Ensuite, nous proposons une méthode itérative de résolution du problème d'optimisation. Les résultats de simulation montrent un gain de débit global par rapport aux schéma de référence

Sparsity-based Recovery of Finite Alphabet Solutions to Underdetermined Linear Systems

International audienceWe consider the problem of estimating a deterministic finite alphabet vector f from underdetermined measurements y = A f, where A is a given (random) n x M matrix. Two new convex optimization methods are introduced for the recovery of finite alphabet signals via l1-norm minimization. The first method is based on regularization. In the second approach, the problem is formulated as the recovery of sparse signals after a suitable sparse transform. The regularization-based method is less complex than the transform-based one. When the alphabet size $p$ equals 2 and (n,N) grows proportionally, the conditions under which the signal will be recovered with high probability are the same for the two methods. When p > 2, the behavior of the transform-based method is established. Experimental results support this theoretical result and show that the transform method outperforms the regularization-based one

Precoding and Decoding in the MIMO Interference Channel for Discrete Constellation

International audienceThis paper addresses the problem of decoding and precoding in the K-user MIMO interference channels. At the receiver side, a joint decoding of the interference and the desired signal is able to improve the receive diversity order. At the transmitter side, we introduce a joint linear precoding design that maximizes the joint cut-off rate, known as a tight lower bound on the joint mutual information for high signal-to-noise ratio (SNR). We also derive a closed-form solution of the precoding matrices that maximizes the mutual information when the SNR is close to zero. This solution is characterized by its low computational complexity, and only requires a local channel state information knowledge at the transmitters. Our simulation results show that decoding interference jointly with the desired signal results in a significant improvement of the receive diversity order. Also a substantial bit error rate and sum-rate improvements are illustrated using the proposed precoding designs

New decoding strategy for underdetermined mimo transmission sparse decomposition

International audienceIn this paper we address the problem of large dimension decoding in MIMO systems. The complexity of the optimal maximum likelihood detection makes it unfeasible in practice when the number of antennas, the channel impulse response length or the source constellation size become too high. We consider a MIMO system with finite constellation and model it as a system with sparse signal sources. We formulate the decoding problem as an underdetermined sparse source recovering problem and apply the L1-minimization to solve it. The resulting decoding scheme is applied to large MIMO systems and to frequency selective channel . We also review the computational cost of some L1-minimization algorithms. Simulation results show significant improvement compared to other existing receivers

Fundamental Limits of a Dense IoT Cell in the Uplink

International audienceThe envisioned Internet of Things (IoT) will involve a massive deployment of objects connected through wireless cells. While commercial solutions are already available, the fundamental limits of such networks in terms of node density, achievable rates or reliability are not known. To address this question, this paper uses a large scale Multiple Access Channel (MAC) to model IoT nodes randomly distributed over the coverage area of a unique base station. The traffic is represented by an information rate spatial density ρ(x). This model, referred to as the Spatial Continuum Multiple Access Channel, is defined as the asymptotic limit of a sequence of discrete MACs. The access capacity region of this channel is defined as the set of achievable information rate spatial densities achievable with vanishing transmission errors and under a sum-power constraint. Simulation results validate the model and show that this fundamental limit theoretically achievable when all nodes transmit simultaneously over an infinite time, may be reached even with a relatively small number of simultaneous transmitters (typically around 20 nodes) which gives credibility to the model. The results also highlight the potential interest of non-orthogonal transmissions for IoT uplink transmissions when compared to an ideal time sharing strategy