Ubiquitous Cell-Free Massive MIMO Communications

Since the first cellular networks were trialled in the 1970s, we have witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic growth has been managed by a combination of wider bandwidths, refined radio interfaces, and network densification, namely increasing the number of antennas per site. Due its cost-efficiency, the latter has contributed the most. Massive MIMO (multiple-input multiple-output) is a key 5G technology that uses massive antenna arrays to provide a very high beamforming gain and spatially multiplexing of users, and hence, increases the spectral and energy efficiency. It constitutes a centralized solution to densify a network, and its performance is limited by the inter-cell interference inherent in its cell-centric design. Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive MIMO system implementing coherent user-centric transmission to overcome the inter-cell interference limitation in cellular networks and provide additional macro-diversity. These features, combined with the system scalability inherent in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO from prior coordinated distributed wireless systems. In this article, we investigate the enormous potential of this promising technology while addressing practical deployment issues to deal with the increased back/front-hauling overhead deriving from the signal co-processing.Comment: Published in EURASIP Journal on Wireless Communications and Networking on August 5, 201

Performance analysis of the interference adaptation dynamic channel allocation technique in wireless communication networks

Dynamic channel allocation (DCA) problem is one of the major research topics in the wireless networking area. The purpose of this technique is to relieve the contradiction between the increasing traffic load in wireless networks and the limited bandwidth resource across the air interface. The challenge of this problem comes from the following facts: a) even the basic DCA problem is shown to be NP-complete (none polynomial complete); b) the size of the state space of the problem is very large; and c) any practical DCA algorithm should run in real-time. Many heuristic DCA schemes have been proposed in the literature. It has been shown through simulation results that the interference adaptive dynamic channel allocation (IA-DCA) scheme is a promising strategy in Time Devision [sic] Multiple Accesss/Frequency Devision [sic] Multiple Accesss [sic] (TDMA/FDMA) based wireless communication systems. However, the analytical work on the IA-DCA strategy in the literature is nearly blank. The performance of a, DCA algorithm in TDMA/FDMA wireless systems is influenced by three factors: representation of the interference, traffic fluctuation, and the processing power of the algorithm. The major obstacle in analyzing IA-DCA is the computation of co-channel interference without the constraint of conventional channel reuse factors. To overcome this difficulty, one needs a representation pattern which can approximate the real interference distribution as accurately as desired, and is also computationally viable. For this purpose, a concept called channel reuse zone (CRZ) is introduced and the methodology of computing the area of a CRZ with an arbitrary, non-trivial channel reuse factor is defined. Based on this new concept, the computation of both downlink and uplink CO-channel interference is investigated with two different propagation models, namely a simplified deterministic model and a shadowing model. For the factor of the processing power, we proposed an idealized Interference Adaptation Maximum Packing (IAMP) scheme, which gives the upper bound of all IA-DCA schemes in terms of the system capacity. The effect of traffic dynamics is delt [sic] with in two steps. First, an asymptotic performance bound for the IA-DCA strategy is derived with the assumption of an arbitrarily large number of channels in the system. Then the performance bound for real wireless systems with the IA-DCA strategy is derived by alleviating this assumption. Our analytical result is compared with the performance bound drawn by Zander and Eriksson for reuse-partitioning DCA1 and some simulation results for IA-DCA in the literature. It turns out that the performance bound obtained in this work is much tighter than Zander and Eriksson\u27s bound and is in agreement with simulation results. 1only available for deterministic propagation model and downlink connection

Joint routing and resource allocation for wireless backhauling of small cell networks

The future communication networks are destined to support an increasingly large amount of data traffic, and for that reason, efficient mechanisms to manage them are necessary. Based on a backhaul network, and starting from specific scenarios, we develop methods to jointly optimize the routing parameters and resources of this network. We relate this optimization with the Software Defined Networks and network virtualization concepts, which allow us to have an overall vision of the network, and lead us to study its decomposition. To do this, we use convex optimization techniques, which have very efficient resolution mechanisms, and help us to obtain tools for interpreting the obtained results and perform analysis on the network parameters. The achieved results show a great improvement in relation to the non-optimized case in terms of carried traffic, which is an assessment we make in the final economic analysis.Las redes de comunicaciones del futuro están destinadas a soportar una cantidad de tráfico de datos cada vez más elevada, y por eso son necesarios mecanismos eficientes para gestionarlas. Basándonos en una red de backhaul y partiendo de escenarios concretos, desarrollamos métodos para optimizar conjuntamente los parámetros de enrutamiento y los recursos de esta red. Esta optimización la ligamos con los conceptos de Software Defined Networksk y de network virtualization, que nos permiten tener una visión general de la red, y nos conducen a estudiar su descomposición. Esto lo hacemos usando técnicas de optimización convexa, que tiene mecanismos de resolución muy eficientes, y nos ayuda a obtener herramientas para interpretar los resultados obtenidos y hacer análisis de los parámetros de la red. Los resultados conseguidos muestran una gran mejora con relación al caso no optimizado en términos de tráfico transportado, valoración que recogemos en un análisis económico final.Les xarxes de comunicacions del futur estan destinades a suportar una quantitat de trànsit de dades cada cop més elevada, i per això són necessaris mecanismes eficients per a gestionar-les. Basant-nos en una xarxa de backhaul i partint d?escenaris concrets, desenvolupem mètodes per a optimitzar conjuntament els paràmetres d?encaminament i els recursos d?aquesta xarxa. Aquesta optimització la lliguem amb els conceptes de Software Defined Network i de network virtualization, que ens permeten tenir una visió general de la xarxa, i ens condueixen a estudiar-ne la seva descomposició. Tot això ho fem utilitzant tècniques d?optimització convexa, que té mecanismes de resolució molt eficients, i ens ajuda a obtenir eines per a interpretar els resultats obtinguts i fer anàlisis dels punts forts i febles de la xarxa. Els resultats aconseguits mostren una gran millora respecte el cas no optimitzat en termes de trànsit transportat, valoració que recollim en una anàlisi econòmica final

Real-Time and Energy-Efficient Routing for Industrial Wireless Sensor-Actuator Networks

With the emergence of industrial standards such as WirelessHART, process industries are adopting Wireless Sensor-Actuator Networks (WSANs) that enable sensors and actuators to communicate through low-power wireless mesh networks. Industrial monitoring and control applications require real-time communication among sensors, controllers and actuators within end-to-end deadlines. Deadline misses may lead to production inefficiency, equipment destruction to irreparable financial and environmental impacts. Moreover, due to the large geographic area and harsh conditions of many industrial plants, it is labor-intensive or dan- gerous to change batteries of field devices. It is therefore important to achieve long network lifetime with battery-powered devices. This dissertation tackles these challenges and make a series of contributions. (1) We present a new end-to-end delay analysis for feedback control loops whose transmissions are scheduled based on the Earliest Deadline First policy. (2) We propose a new real-time routing algorithm that increases the real-time capacity of WSANs by exploiting the insights of the delay analysis. (3) We develop an energy-efficient routing algorithm to improve the network lifetime while maintaining path diversity for reliable communication. (4) Finally, we design a distributed game-theoretic algorithm to allocate sensing applications with near-optimal quality of sensing