DMT of weighted Parallel Channels: Application to Broadcast Channel

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.Comment: Proceedings of the 2008 IEEE International Symposium on Information Theory, Toronto, ON, Canada, July 6 - 11, 200

Multi-Agent Q-Learning Algorithm for Dynamic Power and Rate Allocation in LoRa Networks

International audienceIn this paper, we consider a Low Power Wide Area Network (LPWAN) operating in a licensed-exempt band. The LoRa network provides long-range, wide-area communications for a large amount of objects with limited power consumption. In terms of link budget, nodes that are far from the collector suffer collisions caused by nodes that are close to the collector during the data transmissions. Chirp Spread Spectrum (CSS) modulation is adopted by assigning different Spreading Factors (SF) to active sensors to help reduce destructive collisions in LoRa network. In order to improve the energy efficiency and communication reliability, we propose an application of multi-agent Q-learning algorithm in the dynamic allocation of power and SF to the active nodes for uplink communications in LoRa. The main objective of this paper is to reduce power consumption of the uplink transmissions and to improve the network reliability

Packet Recovery Latency of a Rate-less Polar Code in Low Power Wide Area Networks

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Codage spatio-temporel et gain de multiplexage multi-utilisateurs pour les canaux sélectifs

Les nouvelles générations de réseaux sans fils tels que IEEE 802.11n, IEEE 802.16m, LTE advanced, etc sont basées sur des techniques de transmission multi-antennes et multi-utilisateurs. Dans les systèmes de communications point à point, l'utilisation de plusieurs antennes l'émission et à la réception permet non seulement d'augmenter le débit transmis, mais aussi de garantir une meilleure qualité du signal reçu. Dans cette thèse, on propose une nouvelle famille des codes spatio-temporels pour les canaux sélectifs et nous montrons comment les codes dérivés de l'algèbre de division cyclique peuvent être appliqués dans un système réel, et nous nous focalisons sur leur optimalité et les limites pratiques qui peuvent être rencontrées en industrie. Dans le contexte multi-utilisateurs, l'exploitation du gain de multiplexage multi-utilisateurs permet d'augmenter considérablement le débit global du réseau. Dans le cadre de cette thèse, deux systèmes multiutilisateurs ont été étudiés dans le cas où les canaux entre la source et la destination possèdent une mémoire en temps et en fréquence. Pour le canal sélectif à interférence, on montre que le gain de multiplexage maximal peut être atteint en utilisant un système à alignement d'interférence sous certaines conditions de propagation de canal. Pour le canal sélectif à diffusion, on prouve que le gain multiutilsateur de multiplexage peut être conservé en utilisant une connaissance partielle du canal et un nombre de bits réduits qu'on calcule.The next generation of wireless systems such as IEEE 802.11n, IEEE 802.16m, LTE advanced, etc features Multiple-Input Multiple-Output(MIMO) transmission and multiuser communications. In a point-to-point communication, the use of multiple transmitter and receiver antennas enables an increased data throughput through spatial multiplexing and an increased range by exploiting the spatial diversity. In this dissertation, we propose a new family of split NVD parallel codes to achieve the optimal diversity multiplexing tradeoff and we show how the codes designed from cyclic division algebra can be applied in a real world system, and we focus on their optimality and the practical limits that can be encountered in industry. In the multiuser context, exploiting the multiuser multiplexing gains in the network allows to increase considerably the overall throughput in the network. The multiuser context has been extensively studied in the literature for the case where channels between nodes are flat fading. For the selective fading interference channel, we show that the maximal multiplexing gain of can be achieved using an interference alignment scheme under certain channel spread requirements. For the selective fading MIMO broadcast channels, we show how the correlation between time frequency channels can be used in a selective MIMO broadcast channel to minimize the number of bits to be fed back to the transmitter side while conserving the maximal multiplexing gain.PARIS-Télécom ParisTech (751132302) / SudocSudocFranceF

PAPR-Aware Artificial Noise for Secure Massive MIMO Downlink

International audienceThis paper introduces a new approach to providing secure physical-layer massive multiple-input multiple-output (MIMO) based communications that can improve the energy efficiency of the system. This is achieved by synthesizing orthogonal artificial noise (AN) that has to be constrained to lie in the null space of the legitimate users’ channels while it should lie in the range space of the eavesdropper’s channel. In addition, this AN reduces the peak-to-average power ratio (PAPR) of the transmit signal. Indeed, low PAPR signals are preferable and more efficient for low-cost hardware, thus improving the energy consumption of massive MIMO systems. In this paper, we propose a new PAPR-aware precoding scheme based on the use of AN to enhance the secrecy performance of massive MIMO while reducing the PAPR of the transmit signal and guaranteeing excellent transmission quality for legitimate users. The scheme is formulated as a convex optimization problem that can be resolved via steepest gradient descent (GD). Accordingly, we developed a new iterative algorithm, referred to as PAPR-Aware-Secure-mMIMO, that makes use of instantaneous information to solve the optimization problem. Simulation results show the efficiency of our proposed algorithm in terms of PAPR reduction and secrecy, which is also studied with respect to power distribution between useful signal and AN, PAPR targets and the number of BS antennas