With the increasing requirement of spectral efficiency in 6G mobile networks, the Citizens Broadband Radio Service (CBRS) proposed by the Federal Communications Commission (FCC) is considered as the potential dynamic spectrum sharing solution. Traditional CBRS suffers high administrative expense and privacy risk. In addition, conventional consensus methods in blockchain consume excessive computing power or lack well-founded consensus standard. In this paper, we propose a distributed CBRS-Blockchain model with a specialized consensus method, which is able to reduce administrative expense of dynamic access system. Based on the ring signature techniques, a privacy protection method is proposed. Furthermore, we design a new consensus method named as proof-of-strategy, which combines with the process of spectrum allocation. The proposed method not only provides well-founded consensus mechanism, but also prevents spectrum allocation system from the event of single point failure. Simulation results show the divergent privacy protection for legal users and malicious users, as well as the system utility under the proposed consensus method.
Emanuele Di Pascale, Hamed Ahmadi, Linda Doyle, Irene Macaluso
Neutral Host Small Cell Providers (SCP) represent a key element of the 5G\nvision of ultra-dense mobile networks. However, current business models mostly\nfocus on multi-year agreements for large venues, such as stadiums and hotel\nchains. These business agreements are regulated through binding Service Level\nAgreements (SLAs), which tend to be too cumbersome and costly for smaller scale\nSCPs. As a result, the neutral host model does not scale up to its full\npotential. In this paper, we propose a framework to enable the participation of\nsmall- to medium-sized players in the cellular market as providers offering\nnetwork resources to Mobile Network Operators (MNOs). To this purpose, we\nreview the current and emerging spectrum and technology opportunities that SCPs\ncan use for neutral host deployments. We also propose the use of\nblockchain-enabled smart contracts as a simple and cost-efficient alternative\nto traditional SLAs for small-scale SCPs. To demonstrate this, we describe a\nproof of concept implementation of an Ethereum-based smart contract platform\nfor best-effort service between an SCP and an MNO. Our simulations on potential\nsmart contract-based deployments in city centre Dublin show that the received\nsignal strength in the considered area will increase by an average of $10$\npercent.\n
Mengting Liu, Yinglei Teng, F. Richard Yu, Victor C. M. Leung · 5 authors
The boom of video streaming industry has resulted in the increasing demands for transcoding services from heterogeneous users. Recent advances of blockchain technology allow some startups to realize decentralized collaborative transcoding through device-to-device (D2D) networks, where a group of transcoders are selected to perform transcoding cooperatively. For the blockchain-enabled D2D transcoding systems, it's imperative to jointly design transcoder selection, task scheduling and resource allocation schemes in order to provide efficient and trustworthy transcoding services. In this paper, viewing the involved multi-dimensional complex factors and channel fluctuation, we propose a novel deep reinforcement learning (DRL) based transcoder selection framework for blockchain enabled D2D transcoding systems where both the platform dynamics and channel statistics are captured. To reduce the action space size, we adopt a two-stage decision approach to first select the transcoders through a normal DRL based framework and then obtain the optimal task scheduling, power control, and resource allocation scheme by solving a stochastic optimization problem with the constrained stochastic successive convex approximation (CSSCA) approach. Simulation results show that our proposed framework can achieve high transcoding revenue while meeting the quality of service (QoS) requirements, and it can well handle dynamic cases.
Asuquo A. Okon, Ibrahim Elgendi, Olusegun Samuel Sholiyi, Jaafar M. H. Elmirghani · 6 authors
Whereas 4G LTE networks have brought about an increase in data rates of mobile networks, they are unable to meet the capacity demands of future networks. Specifically, the centralized nature of the evolved packet core (EPC) makes the network non-scalable to match the exponential increase in number of wireless devices in addition to the complexities of diverse service requirements. The SDN concept has recently attracted a lot of research interest as a viable proposition for bringing about programmability and ease of network management while also offering flexibility for innovative network designs. However, current SDN implementations are not adapted to support business agreements that foster interoperability among mobile network operators (MNOs). This paper is an extended version of our earlier work and we intend to present a unified SDN and blockchain architecture with enhanced spectrum management features for enabling seamless user roaming capabilities between MNOs. Our simulation results show that users can experience no disruption in service with very minimal delay as they traverse between operators.
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
Zhixin Liu, Lu Gao, Yang Liu, Xinping Guan · 6 authors
Blockchain-based femtocell networks aim to build decentralized frameworks which enable easy deployment and low power consumption, thus they have been seen promising technologies to make up the coverage of cellular networks in the next generation communication system. This article aims to employ power control to support quality-of-service provisioning, especially the guarantee for the transmission rate of a macrocell user (MUE) and the time delay of femtocell users (FUEs) in two-tier femtocell networks, where the MUE and FUEs share the same communication channel. We formulate the interactions among the macrocell base station and FUEs as a Stackelberg game to maximize the utilities of MUE and FUEs by obtaining the optimal power allocation and pricing strategy. Considering the uncertainty of channel gain which is expressed as a function of transmission distance, we propose a worst-case method to transform the uncertain optimization problem into a deterministic one. We then design two algorithms by considering the dynamics of FUEs, i.e., FUEs may join and leave femtocells. Numerical results verify the convergence and superior performance of our proposed algorithms.
The demand for frequency is continuously increasing owing to the growth of wireless communication devices and the development of network technology. To share frequency effectively in a limited frequency resource environment, studies to develop spectrum-sharing technology should be conducted. In this study, a blockchain-based spectrum- sharing system, in which various types of users can efficiently share spectrum in dense networks, is proposed. Furthermore, a method to apply game theory to obtain cooperation from users who do not participate in the spectrum-sharing system is studied. When the simulation was conducted based on game theory, the proposed blockchain-based spectrum-sharing technique was simulated by using the tit-for-tat (TFT) strategy, in which the system cooperates with the users if the users collaborate and the system does not cooperate with the users if the users do not collaborate. Simulations show that there are more than a certain percentage of users who use the TFT strategy, and if users are encouraged to change their sharing strategy on a regular basis, they can provide more efficient spectrum sharing than traditional centralized methods. It was confirmed that this technique can improve spectrum sharing by 55.1% or more through optimization.
A key challenge in 4G and emerging 5G systems is that of reliably detecting the uplink transmissions of users close to the edge between cells. These users are subject to significant signal attenuation due to path loss, and frequent hand-off from one cell to the other, making channel estimation very challenging. Even multiuser detection using base station cooperation often fails to detect such users, due to channel estimation errors and the sensitivity of multiuser detection to near-far power imbalance. Is it even possible to reliably decode the cell-edge users' signals under these circumstances? This paper shows, perhaps surprisingly, that with a suitable base station `interferometry' strategy, the cell-edge users' signals can be reliably decoded at low SNR under mild conditions. Exploiting the fact that cell-edge users' signals are weak but common to both base stations, while users close to a base station are unique to that base station, reliable detection is enabled by Canonical Correlation Analysis (CCA) - a machine learning technique that reliably estimates a common subspace, even in the presence of strong individual interference. Free from cell-center interference, the resulting mixture of cell-edge signals can then be unraveled using well-known algebraic signal processing techniques. Simulations demonstrate that the proposed detector achieves order of magnitude BER improvement compared to an `oracle' zero-forcing with successive interference cancellation that assumes perfect knowledge of all channels. The paper also includes proof of common subspace identifiability for the assumed generative model, which was curiously missing from the machine learning / CCA literature.
Taras Maksymyuk, Juraj Gazda, Longzhe Han, Minho Jo
The concept of spectrum and infrastructure sharing appeared to solve the problem by allowing operators to cooperate between each other. However, the current architecture of mobile network, which is mostly based on the centralized management entities is not suitable for the spectrum and infrastructure sharing due to the complexity of billing procedure. Moreover, the operator oriented mobile network is slowing the overall technological development, because operators must balance between capital expenditures and profit margins. Such situation negatively affects users, because they are either experience lower quality of service or forced to pay higher price. In this paper, we propose a new intelligent network architecture, which leverage the blockchain technology to handle relationship between operators and users based on smart contracts. The new unlicensed spectrum sharing algorithm between operators using the virtual cryptocurrency has been developed based on game theory. Simulation results show that proposed algorithm achieves Nash equilibrium between operators within few seconds.
The concept of blockchain radio access network (B-RAN) was proposed to integrate cross-network resources including spectra and infrastructures to meet the explosive growth of diverse connectivity needs. In this work, we consider the prototype design of B-RAN and address the issues arising in its implementation. To reduce the access delay, we develop a fast smart contract deployment (FSCD) for B-RAN. Also, we propose the concept of digitized spectrum assets (DSA) in B-RAN for efficient spectrum sharing and management. We further summarize and demonstrate the B-RAN prototype enhanced by the newly introduced FSCD and DSA, along with the overall workflow. We apply comprehensive simulations based on an inhouse experimental platform to illustrate the effectiveness of the proposed B-RAN prototype.
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.
Although a massive amount of bandwidth is available at mm-waves, physics dictates the use of legacy frequencies in the sub 6-GHz range. This necessitates dynamic spectrum access in the face of exponentially growing spectral demands. However, disorganized spectrum sharing causes interference, leads to a chaotic situation, and loss of capacity. Moreover, it is difficult to ensure that the primary users are compensated for sharing their licensed bands. We propose a Blockchain-based platform to address these limitations. A digital token, called spectral token, is introduced to validate and track the use of a licensed frequency band while enforcing sequential access to spectrum by secondary users to avoid interference. The proposed platform enables both advertising and sensing based spectrum sharing under different leasing policies. Such sharing and leasing policies are coded into smart contracts, which digitally enforce the contractual clauses of the leasing agreement. When a deal is made, the smart contract automatically transfers the spectral token between primary and secondary users within the agreed time frame while paying the primary user in cryptocurrency. We developed a proof of concept solution using the Ethereum Blockchain to demonstrate the utility of the proposed platform and its throughput and latency characteristics.
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.
In this article, we propose a blockchain verification protocol as a method for enabling and securing spectrum sharing in moving cognitive radio (CR) networks. The spectrum-sharing mechanism is used as a medium-access protocol for accessing wireless bandwidth among competing CRs. We introduce a virtual currency, called Specoins, for payment to access the spectrum. An auction mechanism based on a first-come-first-served queue is used, with the price for the spectrum advertised by each primary user in a decentralized fashion. The blockchain protocol facilitates the transactions between primary and secondary users and is used to validate and save each user's virtual wallet. Also important for mobile networks, the blockchain serves as a distributed database that is visible by all participating parties, and any node can volunteer to update the blockchain. The volunteer nodes are called miners, and they are awarded with Specoins. We propose diverse methods to exchange the Specoins to make leasing possible even by CRs that are not miners. We show the improvement of the proposed algorithm compared with the conventional Aloha medium-access protocol in terms of spectrum usage. This difference is investigated using small-scale fading variation in the wireless channel to compare the performance of our secure method with the conventional medium access used in vehicular communications. The secure blockchain verification protocol is not only secure but also outperforms the conventional system in moderate cases of small-scale fading. In the case of severe small-scale fading, the blockchain protocol will outperform the conventional system if multipath diversity is not used.
Cloud radio access network (C-RAN) interconnects thousands of terminal devices to support the services of Internet of Things (IoT) in 5G area. However, centralized access authentication of each terminal has been performed in mobile core network which causes an extremely high operating and capital expenditure of network. Traditional C-RAN cannot provide an authentic mechanism to guarantee the security of services and creditability of device and resource accessing with low network cost. We first propose a blockchain-based trusted authentication (BTA) architecture for 5G with blockchain-based anonymous access (BAA) scheme in cloud radio over fiber network. The feasibility and efficiency are verified on enhanced SDN testbed to enable blockchain as a service.
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.
Cognitive radio plays an important role in improving spectrum utilization in wireless services. In the cognitive radio paradigm, secondary users (SUs) are allowed to utilize licensed spectrum opportunistically without interfering with primary users (PUs). To motivate PU to share licensed spectrum with SU, it is reasonable for SU to pay PU a fee whenever the former is utilizing the latter's licensed spectrum. SU's detailed usage information, such as when and how long the licensed spectrum is utilized, is needed for PU to calculate payment. Providing usage information to PU, however, may compromise SU's privacy. To solve this dilemma, we are the first to propose a novel privacy-preserving mechanism for cognitive radio transactions through commitment scheme and zero-knowledge proof. This mechanism, on one hand, only allows PU to know the total payment to SU for a billing period, plus a little portion of SU's usage information. On the other hand, it guarantees PU that the payment is correctly calculated. We have implemented our mechanism and evaluated its performance.
I Wayan Mustika, Koji Yamamoto, Hidekazu Murata, Susumu Yoshida
This paper proposes a game-theoretic approach for self-organized resource allocation in OFDMA femtocells with closed access configuration. The objective of the proposed scheme is to overcome the interference problem caused by co-channel operation of femtocells in an existing macrocell network using a self-organization capability of femto users. Inspired by the emerging cognitive radio technology, each femto user acts as an autonomous entity and attempts to select the most appropriate subset of resource blocks in a decentralized manner in order to mitigate the cross- and co-tier interference. Such a self-organized resource allocation scheme can be modeled as a potential game, which guarantees the convergence to a Nash equilibrium as long as distributed sequential play based on the best response strategy is adopted. Simulation results show that the proposed scheme improves the capacity of the femtocell network, while minimizing the performance degradation of the macrocell network.
Francisco Bernardo, R. Agustı́, J. Pérez-Romero, O. Sallent
This paper presents a decentralized framework for dynamic spectrum assignment in multicell orthogonal frequency division multiple access (OFDMA) networks. The proposed framework allows each cell to autonomously decide the frequency resources it should use through a procedure that incorporates concepts from self-organization and machine learning in multiagent systems (MASs). Simulation results have been obtained for several scenarios, including both macrocells (MCs) and femtocells (FCs), revealing important improvements in terms of spectral efficiency and intercell interference mitigation over reference approaches, and close performance with the one obtained by a centralized strategy. Results also suggest that the framework would be practical for future FC cellular deployments where a high degree of independence of the network nodes is expected to reduce operational costs.
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.
In this correspondence, we show that the exact number of spatial degrees of freedom (DOF) for a two user nondegenerate (full rank channel matrices) multiple-input-multiple-output (MIMO) Gaussian interference channel with M1, M2 antennas at transmitters 1, 2 and N1, N2 antennas at the corresponding receivers, and perfect channel knowledge at all transmitters and receivers, is min{M1 + M2, N1 + M2, max(M1, N2), max(M2, N1)}. A constructive achievability proof shows that zero forcing is sufficient to achieve all the available DOF on the two user MIMO interference channel. We also show through an example of a share-and-transmit scheme how the gains of transmitter cooperation may be entirely offset by the cost of enabling that cooperation so that the available DOF are not increased.