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Über dieses Buch

This book constitutes the thoroughly refereed conference proceedings of the 12th International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2017, held in Lisbon, Portugal, in September 2017.
The 28 revised full papers presented were carefully reviewed and selected from numerous submissions and cover the evolution of cognitive radio technology pertaining to 5G networks. The papers are clustered to topics on spectrum management; network management; trials, test beds, and tools; PHY and sensing; spectrum management.

Inhaltsverzeichnis

Frontmatter

Main Track

Frontmatter

Network Resource Trading: Locating the Contract Sweet Spot for the Case of Dynamic and Decentralized Non-broker Spectrum Sharing

Abstract
This paper aims to present a framework for analysing network resource trading between operators. We present the results for the case of orthogonal inter-operator spectrum sharing as a sub-case of the network resource trading between operators.
A two-operator, two-cell scenario has been considered. Operators share bandwidth orthogonally using standard LTE technology, detailed in the paper. An operator can post resources to a local market (neighbouring cells) for trading them with other operators. We were interested in identifying the duration of the resource trading contracts for trading, which would provide throughput gains. Simulations show up to 30% increase of user throughput and a more efficient use of spectrum if we do not consider any monetary cost or value in the model. In a separate idealised scenario, throughput gains of up to 80% are reported.
Robert Schmidt, Arash Toyser, Siddharth Naik, Janis Nötzel, Eduard A. Jorswieck

Meet an Fantastic Sibyl: A Powerful Model in Cognitive Radio Networks

Abstract
Dynamic spectrum access is challenging, since an individual secondary user usually just has limited sensing abilities. One key insight is that primary user emergence forecasting among secondary users can help to make the most of the inherent association structure in both time and space, it also enables users to obtain more informed spectrum opportunities. Therefore, primary user presence forecasting is vital to cognitive radio networks (CRNs). With this insight, an auto regressive enhanced primary user emergence reasoning (AR-PUER) model for the occurrence of primary user prediction is derived in this paper. The proposed method combines linear prediction and primary user emergence reasoning. Historical samples are selected to train the AR-PUER model in order to capture the current distinction pattern of primary user. The training samples of the primary user emergence reasoning (PUER) model are combined with the recent samples of auto regressive (AR) model tracking recent parallel. Our scheme does not require the knowledge of the signal or of the noise power. Furthermore, the proposed model in this paper is blind in the detection that it does not require information about the channel. To verify the performance of the proposed model, we apply it to the data during the past two months, and then compare it with other method. The simulation results demonstrate that the AR-PUER model is effective and generates the most accurate forecasting of primary user occasion in several cases. Besides, it also performs much better than the commonly used energy detector, which usually suffers from the noise uncertainty problem.
Wei Yang, Xiaojun Jing, Hai Huang

REM-Based Indoor Wireless Network Deployment - An Experimental Study

Abstract
In this paper we discuss the results of the conducted experiment, where dedicated databases have been used for management of deployment of indoor small-cells. As the transmission has been realized in the TV band, the ultimate goal of the study was initialize new data transmission in a spectrum sharing mode while protecting the DVB-T signal. Every time when the cognitive user wanted to initiate new transmission, it asked the database for permission and for a set of parameters defining transmit opportunities. The experiment has been carried out with two sets of USRP N210 devices.
Adrian Kliks, Łukasz Kułacz

Autonomous Spectrum Assignment of White Space Devices

Abstract
White-space spectrum has temporal and spatial variations, and fragmentation, making the spectrum assignment for devices in this space challenging. In this paper, we propose an autonomous agent model for spectrum assignment of white space devices at a given location. Each white space device (WSD) acts autonomously out of self-interest, choosing a strategy from its bag of strategies. It obtains a payoff based on its choice and choices made by all other WSDs. Based on the payoffs received by different strategies, WSDs evolve their strategic profile over time. This has the effect of demographic changes in the population which is published as demographic profile by the Master. WSDs are expected to choose a strategy with a probability distribution based on this, for optimising network utilisation. In evaluation runs, network utilisation levels in such an approach are found to be high, and approaching optimal values computed in a centralised fashion.
Chaitali Diwan, Srinath Srinivasa, Bala Murali Krishna

Machine Learning-Aided Radio Scenario Recognition for Cognitive Radio Networks in Millimeter-Wave Bands

Abstract
Radio scenario recognition is critically important to acquire comprehensive situation awareness for cognitive radio networks in the millimeter-wave bands, especially for dense small cell environment. In this paper, a generic framework of machine learning-aided radio scenario recognition scheme is proposed to acquire the environmental awareness. Particularly, an advanced back propagation neural network-based AdaBoost classification algorithm is developed to recognize various radio scenarios, in which different channel conditions such as line-of-sight (LOS), non-line-of-sight (NLOS), and obstructed line-of-sight (OLOS) are encountered by the desired signal or co-channel interference. Moreover, the advanced AdaBoost algorithm takes the offline training performance into account during the decision fusion. Simulation results show that machine learning can be exploited to recognize the complicated radio scenarios reliably and promptly.
Jingyun Wang, Youping Zhao, Xin Guo, Chen Sun

Dynamic Base Station Sleep Control via Submodular Optimization for Green mmWave Networks

Abstract
This paper proposes a dynamic millimeter-wave (mmWave) base station (BS) sleep control scheme for green mmWave networks. The typical coverage radius of mmWave BS is short due to high propagation and shadowing loss, thus large number of BSs are required to be deployed densely. A network consisting of many BSs consumes large energy. Sleep and activation control is a promising technique to reduce energy consumption. However, to select a set of BSs to sleep from large number of BSs to maximize total throughput under on condition that the total energy consumption of the network is limited is a NP-hard problem and it requires huge computation time. This paper formulates sleep control based on submodular optimization which can be solved quickly by using a greedy algorithm and the performance in the worst case is guaranteed to be \((1-\mathrm {e}^{-1})\)-approximation. We design a utility function defined as total expected rate for mmWave access networks in consideration of the characteristics of mmWave communication, and prove that it is submodular and monotone. The sleep and activation control of mmWave BSs is formulated as a combinatorial optimization problem to maximize a monotone submodular function under the constraint that the number of BSs to be activated is limited due to energy constraints. Simulation results confirmed that the proposed scheme obtains a BS set achieving higher throughput than random selection and the scheme is polynomial time algorithm.
Akihiro Egami, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto

Implementation of a Pseudonym-Based Signature Scheme with Bilinear Pairings on Android

Abstract
Privacy preservation is of paramount importance in the emerging smart city scenario, where numerous and diverse online services will be accessed by users through their mobile or wearable devices. In this scenario, service providers or eavesdroppers can track users’ activities, location, and interactions with other users, which may discourage citizens from accessing smart city services. Pseudonym-based systems have been proposed as an efficient solution to provide identity confidentiality, and more concretely pseudonym-based signature schemes have been suggested as an effective means to authenticate entities and messages privately. In this paper we describe our implementation of a pseudonym-based signature scheme, based on bilinear-pairings. Concretely, our implementation consists of an Android application that enables users to authenticate messages under self-generated pseudonyms, while still enabling anonymity revocation by a trusted third party in case of misbehavior. The paper presents a description of the implementation, performance results, and it also describes the use cases for which it was designed.
Leonardo Oliveira, Victor Sucasas, Georgios Mantas, Jonathan Rodriguez

Cognitive Radio Policy-Based Adaptive Blind Rendezvous Protocols for Disaster Response

Abstract
In disaster scenarios, with damaged network infrastructure, cognitive radio (CR) can be used to provide temporary network access in the first few hours. Since spectrum occupancy will be unknown, the radios must rely on spectrum sensing and opportunistic access. An initial goal is to establish rendezvous between CR nodes to set up the network. The unknown primary radio (PR) activity and CR node topology makes this a challenging task. Existing blind rendezvous strategies provide guarantees on time to rendezvous, but assume channels with no PR activity and no external interferers. To handle this problem of blind multi-node rendezvous in the presence of primary users, we propose an Extended Modular Clock Algorithm which abandons the guarantee on time to rendezvous, an information exchange mechanism for the multi-node problem, and various cognitive radio operating policies. We show that the adapted protocols can achieve up to 80% improvement in the expected time to rendezvous and reduce the harmful interference caused to the primary radio.
Saim Ghafoor, Cormac J. Sreenan, Kenneth N. Brown

Application of the CBRS Model for Wireless Systems Coexistence in 3.6–3.8 GHz Band

Abstract
In this paper we discuss the results of the experiment conducted in Poznan, Poland, where the performance of CBRS spectrum sharing model in 3.6–3.8 GHz band has been verified. Three-tier model has been tested, where the highest priority has been assigned to the fixed WiMAX users, whose transmit parameters cannot be modified. Second tier of users was constituted by the peer-to-peer microwave line, whereas the third tier of lowest priority covered the low-power cognitive small-cells. The whole system has been managed by the dedicated remote database located in Finland. Experiments have been carried out in the laboratory, where mainly the functionality of the management of the third tier user has been tested, while protecting the users assigned to two higher tiers.
Adrian Kliks, Paweł Kryszkiewicz, Łukasz Kułacz, Karol Kowalik, Michał Kołodziejski, Heikki Kokkinen, Jaakko Ojaniemi, Arto Kivinen

Spectrum Occupancy Classification Using SVM-Radial Basis Function

Abstract
With recent development in wireless communication, efficient spectrum utilization is major area of concern. Spectrum measurement studies conducted by wireless communication researchers reveals that the utilization of spectrum is relatively low. In this context, we analyzed big spectrum data for actual spectrum occupancy in spectrum band using different machine learning techniques. Both supervised [Naive Bayes classifier (NBC), K-NN, Decision Tree (DT), Support Vector Machine with Radial Basis Function (SVM-RBF)] and unsupervised algorithms [Neural Network] are applied to find the best classification algorithm for spectrum data. Obtained results shows that combination of SVM-RBF is the best classifier for spectrum database with highest classification accuracy appropriately for distinguishing the class vector in the busy and idle state. We made analysis-based on empirical SVM-RBF model to identify actual duty cycle on the particular band across four mid-size location at Ahmedabad Gujarat.
Mitul Panchal, D. K. Patel, Sanjay Chaudhary

Analysis of Blockchain Use Cases in the Citizens Broadband Radio Service Spectrum Sharing Concept

Abstract
The Blockchain (BC) technology has received religious attention in the financial and internet domains, and recently interest has spread to adjacent sectors like communications. This paper seeks to identify the impact of the BC technology in novel spectrum sharing concepts using the Citizens Broadband Radio Service (CBRS) concept as an example. The results indicate that the BC core characteristics can be utilized in several use cases addressing current CBRS implementation considerations. The CBRS concept could particularly benefit of BCs in building trust, consensus and lowering the transaction cost. In BC deployments, confidentiality should be taken into consideration through hybrid and private BC options. Furthermore, the cognitive radio spectrum sharing – BC combination paves the way for new business models and distributed services.
Seppo Yrjölä

Lessons Learned from Long-Term and Imperfect Sensing in 2.4 GHz Unlicensed Band

Abstract
Accuracy of spectrum sensing affects the decision making operation of cognitive radio. In order to achieve meaningful results, in related experimental and simulation work, realistic wireless environment representation is a necessity. Existing spectrum occupancy models range from simple additive white Gaussian noise to elaborate, based on large scale wireless spectrum measurements, but universal models are not available. Creating such a model for unlicensed bands would be particularly difficult, if not impossible, because of its unpredictability and inherent dynamics. On the other hand, our experience shows that using real-life, relatively low-resolution, data collected using inexpensive spectrum analyzer provides insight consistent with observations made with more sophisticated setups, preserves more nuances than simple models, and could be a viable alternative to spectrum occupancy modeling.
Jacek Dzikowski, Cynthia Hood

A Planning Tool for TV White Space Deployments

Abstract
There have been numerous studies conducted on the availability of TV white spaces in India, which show that white spaces are plentiful. If one needs to harness this spectrum, there is a need for techniques to compute suitable locations where secondary base stations can be placed for providing broadband access. To address this issue, we have come up with a planning tool which determines the best locations for placement of secondary antennas based on secondary base station’s coverage area, population of the region, throughput required and other such parameters. Our real-time model uses different propagation models to compute the path loss, and subsequently the throughput using Shannon’s theorem, to determine the optimal placement of secondary TV white space antennas. Experiments with our tool show that it can provide good placement of secondary base stations and provide high throughput to the covered users. We believe that a tool like ours can accelerate the pace of deployment of secondary networks in the TV white space spectrum.
Mahesh Iyer, Mythili Vutukuru

Impact of Mobility in Spectrum Sensing Capacity

Abstract
This work evaluates the secondary users’ (SUs) transmission capability considering that the primary users (PUs) can move to different positions. The transmission capability identifies the available opportunities for SU’s transmission. No opportunities are available when mobile PUs are active within the SU’s sensing region. We also consider the scenario when the PUs are undesirable detected active when they are not located within the SUs’ sensing region. Our analysis indicate that the transmission capability increases as the average mobility of the PUs decreases, which is confirmed by simulation.
Luis Irio, Rodolfo Oliveira

Multi-Armed Bandit Learning in IoT Networks: Learning Helps Even in Non-stationary Settings

Abstract
Setting up the future Internet of Things (IoT) networks will require to support more and more communicating devices. We prove that intelligent devices in unlicensed bands can use Multi-Armed Bandit (MAB) learning algorithms to improve resource exploitation. We evaluate the performance of two classical MAB learning algorithms, \(\mathrm {UCB}_1\) and Thomson Sampling, to handle the decentralized decision-making of Spectrum Access, applied to IoT networks; as well as learning performance with a growing number of intelligent end-devices. We show that using learning algorithms does help to fit more devices in such networks, even when all end-devices are intelligent and are dynamically changing channel. In the studied scenario, stochastic MAB learning provides a up to \(16\%\) gain in term of successful transmission probabilities, and has near optimal performance even in non-stationary and non-i.i.d. settings with a majority of intelligent devices.
Rémi Bonnefoi, Lilian Besson, Christophe Moy, Emilie Kaufmann, Jacques Palicot

Inter-operator Interference Coordination in the Spectrum-Sharing Overlapping Area

Abstract
With the widespread application of dynamic spectrum access technology, sharing spectrum with the same primary systems by multiple operators will become a common scenario. Serious co-channel interference (CCI) needs to be mitigated if there is no coordination among the operators. In this paper, a cluster-based interference management algorithm is proposed to reduce the inter-operator CCI in the spectrum-sharing overlapping area. The proposed algorithm consists of two major steps: (1) undirected weighted graph-based clustering and spectrum allocation; (2) signal to interference and noise ratio (SINR) margin-based power adjustment. A novel weight is defined and employed in the clustering procedure to take the SINR requirement of each secondary user (SU) into account. Simulation results show that the ratio of satisfied SUs (whose SINR exceeds their SINR thresholds) can be increased while the sum of co-channel interference is significantly reduced. Furthermore, by introducing a third-party agent, direct exchange of sensitive SU information between different operators can be avoided for better privacy protection.
Yiteng Wang, Youping Zhao, Xin Guo, Chen Sun

Blind Symbol Rate Estimation of Faster-than-Nyquist Signals Based on Higher-Order Statistics

Abstract
Both faster-than-Nyquist (FTN) and cognitive radio go towards an efficient use of spectrum in radio communications systems at the cost of an added computational complexity at the receiver side. To gain the maximum potential from these techniques, non-data-aided receivers are of interest. In this paper, we use fourth-order statistics to perform blind symbol rate estimation of FTN signals. The estimator shows good performance results for moderate system’s densities beyond the Nyquist rate and for a reasonable number of received samples.
Albert Abelló, Damien Roque, Jean-Marie Freixe

Impact of Uncertainty About a User to be Active on OFDM Transmission Strategies

Abstract
In this paper we investigate the impact that incomplete knowledge regarding user activity can have on the equilibrium transmission strategy for an OFDM-based communication system. The problem is formulated as a two user non-zero sum game for independent fading channel gains, where the equilibrium strategies are derived in closed form. This allows one to show that a decrease in uncertainty about the user activity could reduce the number of subcarriers jointly used by the users. For the boundary case (with complete information, which reflects a classical water-filling game) the equilibrium strategies are given explicitly. The necessary and sufficient conditions, when channels sharing strategies are optimal, is established as well as the set of shared subcarriers is identified. The stability of the upper bound of the size of this set with respect to power budgets is derived.
Andrey Garnaev, Wade Trappe, Ratnesh Kumbhkar, Narayan B. Mandayam

Invited Papers

Frontmatter

Reliable and Reproducible Radio Experiments in FIT/CorteXlab SDR Testbed: Initial Findings

Abstract
The FIT/CorteXlab platform is a wireless testbed situated in Lyon, France, where all radio nodes are confined to an electro- magnetically (EM) shielded environment and have flexible radio-frequency (RF) front-end for experimenting on software defined radio (SDR) and cognitive radio (CR). A unique feature of this testbed is that it offers roughly 40 SDR nodes that can be accessed from anywhere in the world in a reproducible manner: the electro-magnetic shield prevents from external interference and channel variability. In this paper we show why it is important to have such a reproducible radio experiment testbed and we highlight the reproducibility by the channel characteristics between the nodes of the platform. We back our claims with a large set of measurements done in the testbed, that also refines our knowledge on the propagation characteristics of the testbed.
Leonardo S. Cardoso, Othmane Oubejja, Guillaume Villemaud, Tanguy Risset, Jean Marie Gorce

Spectrum Broker Service for Micro-operator and CBRS Priority Access Licenses

Abstract
This paper discusses a spectrum broker service for micro-operator and Citizens Broadband Radio Service (CBRS) Priority Access Licenses (PAL). The spectrum broker service provides a marketplace for selling and leasing of spectrum resources. The micro-operator licenses are regional, and possibly temporal, mobile network spectrum licenses for a confined service area like for a factory, a campus, or a hospital. CBRS opens the 3.5 GHz band for Dynamic Spectrum Access (DSA) in the US. PAL is the middle priority level license in CBRS. The paper introduces a new service model for spectrum brokering. The required functionalities of the service are described, and a new automated spectrum pricing model is proposed for the broker service.
Topias Kokkinen, Heikki Kokkinen, Seppo Yrjölä

Designing a Testbed Infrastructure for Experimental Validation and Trialing of 5G Vertical Applications

Abstract
This paper describes the design of a testbed for experimental validation and trialing of 5G vertical applications. The paper introduces the challenges that 5G aims to solve with regard to the spectrum demand and the convergence of different wireless communication services. The European-level 5G research program 5G Public Private Partnership (5G-PPP) is a coordinated European approach to secure European leadership in 5G. The 5G-PPP has developed a 5G Pan-European Trials Roadmap, which includes a comprehensive strategy for coordinated international preliminary and pre-commercial trials. The objective in designing Turku University of Applied Sciences (TUAS) testbed infrastructure in Turku, Finland, has been in building a testbed that can be used to contribute to the development, standardization and trialing of wireless communications in a diverse selection of scenarios and vertical applications. In addition, the paper describes the spectrum monitoring capabilities at TUAS facilities.
Juha Kalliovaara, Reijo Ekman, Jarkko Paavola, Tero Jokela, Juhani Hallio, Jani Auranen, Pekka Talmola, Heikki Kokkinen

Interference Study of Micro Licensing for 5G Micro Operator Small Cell Deployments

Abstract
5G brings along very dense small cell deployments in specific locations such as hospitals, campuses, shopping malls, and factories. This will result in a novel 5G deployment scenario where different stakeholders, i.e., micro operators, are issued local spectrum access rights in the form of micro licenses, to deploy networks in the specific premises. This new form of sharing-based micro licensing guarantees that the local 5G networks remain free from harmful interference from each other and also protects potential incumbent spectrum users’ rights. It admits a larger number of stakeholders to gain access to the 5G spectrum to serve different vertical sectors’ needs beyond traditional mobile network operators (MNO) improving the competition landscape. We characterize the resulting interference scenarios between the different micro operators’ deployments and focus on the building-to-building scenario where two micro operators hold micro licenses in separate buildings in co-channel and adjacent channel cases. We analyze the resulting allowable transmit power levels of a base station from inside one building towards an end user mobile terminal inside another building as a function of the minimum separation distance between the two micro operator networks. Numerical results are provided for the example case of the 3.5 GHz band with different building entry losses characterizing the impact of propagation characteristics on the resulting interference levels. The results indicate that the building entry losses strongly influence the interference levels and resulting required minimum separation distances, which calls for flexibility in determining the micro license conditions for the building specific situation.
Marja Matinmikko, Antti Roivainen, Matti Latva-aho, Kimmo Hiltunen

Using Deep Neural Networks for Forecasting Cell Congestion on LTE Networks: A Simple Approach

Abstract
Predicting short-term cellular load in LTE networks is of great importance for mobile operators as it assists in the efficient managing of network resources. Based on predicted behaviours, the network can be intended as a proactive system that enables reconfiguration when needed. Basically, it is the concept of self-organizing networks that ensures the requirements and the quality of service. This paper uses a dataset, provided by a mobile network operator, of collected downlink throughput samples from one cell in an area where cell congestion usually occurs and a Deep Neural Network (DNN) approach to perform short-term cell load forecasting. The results obtained indicate that DNN performs better results when compared to traditional approaches.
Pedro Torres, Hugo Marques, Paulo Marques, Jonathan Rodriguez

Radio Hardware Virtualization for Coping with Dynamic Heterogeneous Wireless Environments

Abstract
Diverse wireless standards, designed for diverse traffic types, operate in the same wireless environment without coordination, often leading to interference and inefficient spectrum usage. Although C-RAN (Cloud/centralized RAN) is a promising architecture to achieve intra-operator network coordination, the architecture encounters challenge when low latency services and diverse access technologies are expected over non-fiber fronthaul. So, multi-standard multi-channel access point with low processing latency is preferred to be at the edge of network instead of central cloud. But, developing this kind of equipment is difficult as multiple radio chips and drivers have to be integrated and coordinated. In ORCA (Orchestration and Reconfiguration Control Architecture) project, a SDR architecture is developed on a single chip radio platform including hardware accelerators wrapped by unified software APIs, which offer the following capabilities: (1) concurrent data transmission over multiple virtual radios; (2) runtime composition and parametric control of radios; and (3) radio resource slicing, supporting independent operation of multiple standards in different bands, time slots or beams. Such an architecture offers a fast development cycle, as only software programming is required for creating and manipulating multiple radios. The architecture further achieves an efficient utilization of hardware resources, as accelerators can be shared by multiple virtual radios.
Xianjun Jiao, Ingrid Moerman, Wei Liu, Felipe Augusto Pereira de Figueiredo

TV White Spaces and Licensed Shared Access Applied to the Brazilian Context

Abstract
The spectrum “scarcity” problem can be tackled by promoting a more efficient use of this resource. Spectrum sharing techniques, e.g. TV White Spaces (TVWS) and Licensed Shared Access (LSA), are good solutions for this problem and there are already regulation and standardization efforts worldwide. The Brazilian regulatory scenario is not that advanced regarding spectrum sharing, but there are already some actions towards the adoption of this concept for the Brazilian reality. This paper gives an overview of the spectrum sharing concept and the Brazilian telecommunications regulatory scenario. Case studies regarding the employment of both TVWS and LSA in the Brazilian scenario are also presented as a way to bring more attention to the adoption of those concepts in the country.
Raphael B. Evangelista, Carlos F. M. e Silva, Francisco R. P. Cavalcanti, Yuri C. B. Silva

MAC Design for 5G Dense Networks Based on FBMC Modulation

Abstract
The fifth generation (5G) of wireless networks is currently under investigation in order to address the well-known challenges of the high capacity demands and traffic volume. The promising solutions to meet these targets can be achieved through ultra-densification, efficient use of spectrum and advanced filtered modulation techniques. In this paper, we present an enhanced MAC protocol for 5G small cells operating at 5 GHz and assuming an FBMC physical layer. The proposed MAC design consists of scheduled-based and contention-based access schemes and involves a listen before talk (LBT) procedure to comply with ETSI regulations. The performance of the proposed FBMC-MAC design is then evaluated in dense deployment scenarios under different PHY/MAC parameter settings. Moreover, we study the performance of FBMC-MAC systems in the context of coexistence with WiFi systems.
Rida El Chall, Benoit Miscopein, Dimitri Kténas

A Flexible Physical Layer for LPWA Applications

Abstract
In the context of Low Power Wide Area (LPWA) networks, terminals are expected to be low cost, to be able to communicate over a long distance, and to operate on battery power for many years. In order to support a wide range of LPWA applications, the next generation of LPWA technologies is expected to provide faster throughput, be more resilient, and guarantee lower levels of latency for a similar battery lifetime. These contradictory requirements, lead to consider the design of a flexible physical layer with the aim to be efficient for the identified operating modes from “low data rate, low power consumption, long range” to “high data rate”. Performance of waveform candidates is assessed in terms of PER, range and also power consumption in order to obtain the best compromise between operating modes. A new flexible waveform based on frequency domain processing is finally proposed to address the large scale of requirements of new LPWA applications.
Valérian Mannoni, Vincent Berg, François Dehmas, Dominique Noguet

Late Papers

Frontmatter

Knapsack Optimisation for Mobility Load Balancing in Dense Small Cell Deployments

Abstract
We present a new approach for mobility load balancing (MLB) and user association in dense small cell scenarios. This Self Organizing Network (SON) approach relies on Knapsack Optimisation (KO) to evenly distribute users across participating cells subject to constraints. It is shown that the new technique referred to as (MLB-KO) achieves substantial improvements (better than three times reduction) in blocking ratios for the studied use cases.
Karim M. Nasr, Seiamak Vahid, Klaus Moessner

Backmatter

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