Onel L. Alcaraz López, Hirley Alves, Richard Demo Souza, Samuel Montejo‐Sánchez · 6 authors
Recent advances on wireless energy transfer (WET) make it a promising\nsolution for powering future Internet of Things (IoT) devices enabled by the\nupcoming sixth generation (6G) era. The main architectures, challenges and\ntechniques for efficient and scalable wireless powering are overviewed in this\npaper. Candidates enablers such as energy beamforming (EB), distributed antenna\nsystems (DAS), advances on devices' hardware and programmable medium, new\nspectrum opportunities, resource scheduling and distributed ledger technology\nare outlined. Special emphasis is placed on discussing the suitability of\nchannel state information (CSI)-limited/free strategies when powering\nsimultaneously a massive number of devices. The benefits from combining DAS and\nEB, and from using average CSI whenever available, are numerically illustrated.\nThe pros and cons of the state-of-the-art CSI-free WET techniques in ultra-low\npower setups are thoroughly revised, and some possible future enhancements are\noutlined. Finally, key research directions towards realizing WET-enabled\nmassive IoT networks in the 6G era are identified and discussed in detail.\n
Mark A. Graham, Ayalvadi Ganesh, Robert J. Piechocki
The emergence of new connectivity services for automated transportation marks a paradigm shift for the operation of wireless networks. Furthermore, the advent of blockchain technology promises to enable a plethora of smart mobility services, which are not contingent on any central authorities. Concepts such as distributed ledger require efficient and reliable data dissemination between vehicles. Traditional techniques based on Automatic Repeat Request (ARQ) are well known to scale poorly in all-cast networks due to the feedback implosion problem. Fountain and network coding techniques are arguably the most promising alternative solutions. In this paper we derive new analytical bounds on transmit message lengths and quantify bandwidth delay trade-offs for fountain coding based data dissemination for CAVs.
The device-to-device (D2D) communication is one of the promising technologies of the future Internet of Things (IoT), but its security-related issues remain challenging. The block-chain is considered to be a secure and reliable distributed ledger, so we can treat the device user equipment (D-UE) request for the reusing resources of cellular user equipment (C-UE) as a transaction and put it into a transaction pool, then package the record into the block-chain. In this paper, we study the D2D communication resource allocation scheme based on sparse code multiple access (SCMA). Firstly, the system's interference model and block-chain-based transaction flow are analyzed. Then we propose the optimization problem so that C-UE can get the maximum revenue by sharing its resources to D-UE. This problem is NP-hard, so we propose a heuristic algorithm based on semi-definite relaxation (SDR) programming to solve it. Finally, the performance of the proposed algorithm is verified by simulation of different system parameters.
Despite growing adoption of cryptocurrencies, making fast payments at scale remains a challenge. Payment channel networks (PCNs) such as the Lightning Network have emerged as a viable scaling solution. However, completing payments on PCNs is challenging: payments must be routed on paths with sufficient funds. As payments flow over a single channel (link) in the same direction, the channel eventually becomes depleted and cannot support further payments in that direction; hence, naive routing schemes like shortest-path routing can deplete key payment channels and paralyze the system. Today's PCNs also route payments atomically, worsening the problem. In this paper, we present Spider, a routing solution that "packetizes" transactions and uses a multi-path transport protocol to achieve high-throughput routing in PCNs. Packetization allows Spider to complete even large transactions on low-capacity payment channels over time, while the multi-path congestion control protocol ensures balanced utilization of channels and fairness across flows. Extensive simulations comparing Spider with state-of-the-art approaches shows that Spider requires less than 25% of the funds to successfully route over 95% of transactions on balanced traffic demands, and offloads 4x more transactions onto the PCN on imbalanced demands.
This paper discusses novel joint (intracell and intercell) resource allocation algorithms for self-organized interference coordination in multicarrier multiple-input multiple-output (MIMO) small cell networks. The proposed algorithms enable interference coordination autonomously, over multiple degrees of freedom, such as base station transmit powers, transmit precoders, and user scheduling weights. A generic$\alpha$-fair utility maximization framework is considered to analyze performance-fairness tradeoff and to quantify the gains achievable in interference-limited networks. The proposed scheme involves limited inter-base station signaling in the form of two step (power and precoder) pricing. Based on this decentralized coordination, autonomous power and precoder update decision rules are considered, leading to algorithms with different characteristics in terms of user data rates, signaling load, and convergence speed. Simulation results in a practical setting show that the proposed pricing-based self-organization can achieve up to$100\%$improvement in cell-edge data rates when compared to baseline optimization strategies. Furthermore, the convergence of the proposed algorithms is also proved theoretically.
La próxima cuarta generación (4G) de redes de comunicaciones móviles celulares considera una interfaz radio basada en OFDMA (Orthogonal Frequency Division Multiple Access). Esta tecnología ofrece robustez a la propagación multicamino y diversidad en frecuencia gracias a la división del ancho de banda de operación en un conjunto de pequeños subcanales en frecuencia para así alcanzar un uso eficiente del espectro. Sin embargo, un importante desafío en una interfaz radio OFDMA es la manera en la que los subcanales en frecuencia se asignan a las distintas celdas. En primer lugar, la carga de tráfico podría variar a lo largo del tiempo y del espacio, de modo que los clásicos patrones fijos de asignación de espectro (es decir, los esquemas de planificación de frecuencias) pueden conducir a una carencia de recursos en ciertas celdas o a una falta de aprovechamiento de los mismos en otras. En segundo lugar, los futuros marcos reguladores del espectro cambiarán la mentalidad sobre su uso, planteando la coexistencia de usuarios primarios y secundarios del espectro en una misma área geográfica. Por lo tanto, una adecuada gestión del espectro primario podría facilitar la aparición de oportunidades del uso del espectro para usuarios secundarios a la vez que el operador podría obtener una nueva entrada de ingresos por ese uso. Finalmente, los futuros escenarios celulares tenderán a ser descentralizados, especialmente con la aparición de nuevos despliegues basados en femtoceldas (puntos de acceso de limitada cobertura desplegados por el propio usuario en la banda espectral en la que el operador tiene licencia), donde se requerirá un alto grado de independencia a la hora de decidir los canales que usa cada femtocelda, ya que, obviamente, las tareas centralizadas planificación de frecuencias tienen poco sentido práctico en estos escenarios. Esta tesis contribuye a la investigación sobre la asignación de espectro en redes móviles celulares 4G basadas en OFDMA proponiendo una solución para manejar dinámicamente la asignación de espectro por celda. Con este fin, se proponen estrategias dinámicas asignación de espectro (en inglés Dynamic Spectrum Assigment: DSA) y un marco práctico para ejecutarlas. Para reducir costes operacionales y la intervención humana en el proceso, el marco DSA propuesto se ha diseñado basándose en conceptos de autoorganización de modo que la red puede de forma autónoma (i) observar el funcionamiento de la asignación actual de espectro, (ii) analizar si una nueva asignación de espectro es necesaria, y (iii) decidir una nueva asignación de espectro que se adapte mejor a las condiciones de la red. Además, se propone una arquitectura funcional centralizada y descentralizada que permite que el marco DSA pueda aplicarse a varios escenarios, desde escenarios macrocelulares donde típicamente se emplea un control centralizado, a futuros escenarios con femtoceldas donde los nodos son prácticamente independientes y requieren de decisiones autónomas a nivel de celda para la asignación de espectro. La tarea de decisión del marco DSA reside en las estrategias DSA propuestas, donde una de ellas se basa en el aprendizaje máquina para explotar el conocimiento adquirido previamente en el pasado. Además, esta estrategia tiende a seleccionar una asignación de espectro óptima en el sentido de que maximiza una señal de recompensa definida apropiadamente en términos de métricas del funcionamiento de la red (e.g., eficiencia espectral, SINR, entre otras). Ciertamente, la autoorganización y el aprendizaje máquina en el contexto de la asignación de espectro en interfaces radio basadas en OFDMA se han explotado poco y constituyen así una novedad importante derivada del trabajo de esta tesis. Los resultados revelan importantes mejoras sobre estrategias del estado del arte en términos de eficiencia espectral (en bits/s/Hz), satisfacción de la calidad de servicio de los usuarios, fairness entre el throughput obtenido por los usuarios, y la capacidad para generar oportunidades para el uso secundario del espectro en grandes áreas geográficas. También, el marco DSA propuesto basado en autoorganización muestra atractivas capacidades desde la perspectiva del despliegue inicial, donde los nodos son capaces de autoconfigurarse después de su encendido introduciendo un impacto mínimo en sistema ya desplegado. Así el marco propuesto constituye una contribución práctica para solucionar el despliegue de millares de femtoceldas en un escenario macrocelular. Next fourth generation (4G) of cellular mobile networks envisage a radio interface based on OFDMA (Orthogonal Frequency Division Multiple Access). OFDMA offers frequency diversity and robustness against multipath channel propagation thanks to the division of a wide bandwidth into small OFDMA frequency resources, so that an efficient spectrum usage is attained. However, one important challenge in a 4G OFDMA-based radio interface of a cellular network is the way in which OFDMA frequency resources are assigned to cells. First, intercell interference must be mitigated to achieve the highest spectral efficiency. Second, traffic loads could vary along time and space, so typical fixed spectrum assignment patterns (i.e., frequency planning) could lead to lack of spectrum resources in some cells or underutilization of them in others. Third, future regulatory spectrum frameworks will change the mindset about the usage of the spectrum by planning the co-existence of primary (licensees) and secondary users of the spectrum in the same geographical area. Hence, an adequate primary management of the spectrum could ease the appearance of spectrum usage opportunities for secondary users at the same time that the primary operator could obtain a new revenue income for that usage. Finally, future cellular scenarios will tend to be decentralized, especially with the appearance of new femtocell deployments (short-range user-deployed access points in the operator's licensed spectrum band), where a high degree of independency when deciding the usage of OFDMA frequency resources will be needed, since, obviously, centralized frequency planning tasks has little practical sense in those scenarios. This thesis contributes to the research on the spectrum assignment in 4G OFDMA-based mobile cellular networks by proposing a solution to dynamically manage the cell-by-cell spectrum assignment. To this end, adequate Dynamic Spectrum Assignment (DSA) strategies and a practical framework to execute them are proposed. In order to reduce operational costs and to reduce human intervention, the DSA framework has been designed based on self-organization so that the network is able to autonomously (i) observe the performance of current spectrum assignment, (ii) analyze if a new spectrum assignment is needed, and (iii) decide a new spectrum assignment to better adapt to networks conditions. Furthermore, a centralized and decentralized functional architecture is proposed so that the framework can be applied to a vast number of scenarios, ranging from typical macrocell scenarios where centralized control is employed, to future femtocell scenarios where nodes are almost independent and require autonomous spectrum assignment decisions at the cell level. The decision task of the framework resides on proposed DSA strategies, where one of them is based on machine learning to exploit knowledge previously acquired in the past. Moreover, this machine learning strategy tends to select a spectrum assignment that is optimal in the sense that maximizes a given reward signal appropriately defined in terms of network performance metrics (e.g., spectral efficiency, SINR, among others). Certainly, self-organization and machine learning on the context of spectrum assignment in OFDMA based radio interfaces have been little exploited and thus constitutes a major novelty of the work of this thesis. Performance results reveal important improvements over state-of-the-art strategies in terms of spectral efficiency (i.e. in bits/s/Hz), users' QoS satisfaction, fairness between the throughput obtained by users, and capacity for generating opportunities for secondary spectrum usage in large geographical areas. Also, the proposed DSA framework, based on self-organization, demonstrates appealing capabilities from the perspective of initial deployment, where nodes are able to self-configure after switch-on introducing a minimal impact on the already deployed system, being then a practical contribution to solve the deployment of thousands of femtocells in macrocell environments.
We present an efficient simultaneous broadcast protocol ν-SimCast that allows n players to announce independently chosen values, even if up to t < n players are corrupt. Independence is guaranteed in the partially syn-2 chronous communication model, where communication is structured into rounds, while each round is asynchronous. The ν-SimCast protocol is more efficient than previous constructions. For repeated executions, we reduce the communication and computation complexity by a factor O(n). Combined with a deterministic extractor, ν-SimCast provides a particularly efficient solution for distributed coin-flipping. The protocol does not require any zero-knowledge proofs and is shown to be secure in the standard model under the Decisional Diffie Hellman assumption.