A Comparison of CP-OFDM, PCC-OFDM and UFMC for 5G Uplink Communications

Polynomial-cancellation-coded orthogonal frequency division multiplexing (PCC-OFDM) is a form of OFDM that has waveforms which are very well localized in both the time and frequency domains and so it is ideally suited for use in the 5G network. This paper analyzes the performance of PCC-OFDM in the uplink of a multiuser system using orthogonal frequency division multiple access (OFDMA) and compares it with conventional cyclic prefix OFDM (CP-OFDM), and universal filtered multicarrier (UFMC). PCC-OFDM is shown to be much less sensitive than either CP-OFDM or UFMC to time and frequency offsets. For a given constellation size, PCC-OFDM in additive white Gaussian noise (AWGN) requires 3dB lower signal-to-noise ratio (SNR) for a given bit-error-rate, and the SNR advantage of PCC-OFDM increases rapidly when there are timing and/or frequency offsets. For PCC-OFDM no frequency guard band is required between different OFDMA users. PCC-OFDM is completely compatible with CP-OFDM and adds negligible complexity and latency, as it uses a simple mapping of data onto pairs of subcarriers at the transmitter, and a simple weighting-and-adding of pairs of subcarriers at the receiver. The weighting and adding step, which has been omitted in some of the literature, is shown to contribute substantially to the SNR advantage of PCC-OFDM. A disadvantage of PCC-OFDM (without overlapping) is the potential reduction in spectral efficiency because subcarriers are modulated in pairs, but this reduction is more than regained because no guard band or cyclic prefix is required and because, for a given channel, larger constellations can be used

A survey of digital television broadcast transmission techniques

This paper is a survey of the transmission techniques used in digital television (TV) standards worldwide. With the increase in the demand for High-Definition (HD) TV, video-on-demand and mobile TV services, there was a real need for more bandwidth-efficient, flawless and crisp video quality, which motivated the migration from analogue to digital broadcasting. In this paper we present a brief history of the development of TV and then we survey the transmission technology used in different digital terrestrial, satellite, cable and mobile TV standards in different parts of the world. First, we present the Digital Video Broadcasting standards developed in Europe for terrestrial (DVB-T/T2), for satellite (DVB-S/S2), for cable (DVB-C) and for hand-held transmission (DVB-H). We then describe the Advanced Television System Committee standards developed in the USA both for terrestrial (ATSC) and for hand-held transmission (ATSC-M/H). We continue by describing the Integrated Services Digital Broadcasting standards developed in Japan for Terrestrial (ISDB-T) and Satellite (ISDB-S) transmission and then present the International System for Digital Television (ISDTV), which was developed in Brazil by adopteding the ISDB-T physical layer architecture. Following the ISDTV, we describe the Digital Terrestrial television Multimedia Broadcast (DTMB) standard developed in China. Finally, as a design example, we highlight the physical layer implementation of the DVB-T2 standar

Optimization of 5G Second Phase Heterogeneous Radio Access Networks with Small Cells

Due to the exponential increase in high data-demanding applications and their services per coverage area, it is becoming challenging for the existing cellular network to handle the massive sum of users with their demands. It is conceded to network operators that the current wireless network may not be capable to shelter future traffic demands. To overcome the challenges the operators are taking interest in efficiently deploying the heterogeneous network. Currently, 5G is in the commercialization phase. Network evolution with addition of small cells will develop the existing wireless network with its enriched capabilities and innovative features. Presently, the 5G global standardization has introduced the 5G New Radio (NR) under the 3rd Generation Partnership Project (3GPP). It can support a wide range of frequency bands (<6 GHz to 100 GHz). For different trends and verticals, 5G NR encounters, functional splitting and its cost evaluation are well-thought-out. The aspects of network slicing to the assessment of the business opportunities and allied standardization endeavours are illustrated. The study explores the carrier aggregation (Pico cellular) technique for 4G to bring high spectral efficiency with the support of small cell massification while benefiting from statistical multiplexing gain. One has been able to obtain values for the goodput considering CA in LTE-Sim (4G), of 40 Mbps for a cell radius of 500 m and of 29 Mbps for a cell radius of 50 m, which is 3 times higher than without CA scenario (2.6 GHz plus 3.5 GHz frequency bands). Heterogeneous networks have been under investigation for many years. Heterogeneous network can improve users service quality and resource utilization compared to homogeneous networks. Quality of service can be enhanced by putting the small cells (Femtocells or Picocells) inside the Microcells or Macrocells coverage area. Deploying indoor Femtocells for 5G inside the Macro cellular network can reduce the network cost. Some service providers have started their solutions for indoor users but there are still many challenges to be addressed. The 5G air-simulator is updated to deploy indoor Femto-cell with proposed assumptions with uniform distribution. For all the possible combinations of apartments side length and transmitter power, the maximum number of supported numbers surpassed the number of users by more than two times compared to papers mentioned in the literature. Within outdoor environments, this study also proposed small cells optimization by putting the Pico cells within a Macro cell to obtain low latency and high data rate with the statistical multiplexing gain of the associated users. Results are presented 5G NR functional split six and split seven, for three frequency bands (2.6 GHz, 3.5GHz and 5.62 GHz). Based on the analysis for shorter radius values, the best is to select the 2.6 GHz to achieve lower PLR and to support a higher number of users, with better goodput, and higher profit (for cell radius u to 400 m). In 4G, with CA, from the analysis of the economic trade-off with Picocell, the Enhanced multi-band scheduler EMBS provide higher revenue, compared to those without CA. It is clearly shown that the profit of CA is more than 4 times than in the without CA scenario. This means that the slight increase in the cost of CA gives back more than 4-time profit relatively to the ”without” CA scenario.Devido ao aumento exponencial de aplicações/serviços de elevado débito por unidade de área, torna-se bastante exigente, para a rede celular existente, lidar com a enormes quantidades de utilizadores e seus requisitos. É reconhecido que as redes móveis e sem fios atuais podem não conseguir suportar a procura de tráfego junto dos operadores. Para responder a estes desafios, os operadores estão-se a interessar pelo desenvolvimento de redes heterogéneas eficientes. Atualmente, a 5G está na fase de comercialização. A evolução destas redes concretizar-se-á com a introdução de pequenas células com aptidões melhoradas e características inovadoras. No presente, os organismos de normalização da 5G globais introduziram os Novos Rádios (NR) 5G no contexto do 3rd Generation Partnership Project (3GPP). A 5G pode suportar uma gama alargada de bandas de frequência (<6 a 100 GHz). Abordam-se as divisões funcionais e avaliam-se os seus custos para as diferentes tendências e verticais dos NR 5G. Ilustram-se desde os aspetos de particionamento funcional da rede à avaliação das oportunidades de negócio, aliadas aos esforços de normalização. Exploram-se as técnicas de agregação de espetro (do inglês, CA) para pico células, em 4G, a disponibilização de eficiência espetral, com o suporte da massificação de pequenas células, e o ganho de multiplexagem estatística associado. Obtiveram-se valores do débito binário útil, considerando CA no LTE-Sim (4G), de 40 e 29 Mb/s para células de raios 500 e 50 m, respetivamente, três vezes superiores em relação ao caso sem CA (bandas de 2.6 mais 3.5 GHz). Nas redes heterogéneas, alvo de investigação há vários anos, a qualidade de serviço e a utilização de recursos podem ser melhoradas colocando pequenas células (femto- ou pico-células) dentro da área de cobertura de micro- ou macro-células). O desenvolvimento de pequenas células 5G dentro da rede com macro-células pode reduzir os custos da rede. Alguns prestadores de serviços iniciaram as suas soluções para ambientes de interior, mas ainda existem muitos desafios a ser ultrapassados. Atualizou-se o 5G air simulator para representar a implantação de femto-células de interior com os pressupostos propostos e distribuição espacial uniforme. Para todas as combinações possíveis do comprimento lado do apartamento, o número máximo de utilizadores suportado ultrapassou o número de utilizadores suportado (na literatura) em mais de duas vezes. Em ambientes de exterior, propuseram-se pico-células no interior de macro-células, de forma a obter atraso extremo-a-extremo reduzido e taxa de transmissão dados elevada, resultante do ganho de multiplexagem estatística associado. Apresentam-se resultados para as divisões funcionais seis e sete dos NR 5G, para 2.6 GHz, 3.5GHz e 5.62 GHz. Para raios das células curtos, a melhor solução será selecionar a banda dos 2.6 GHz para alcançar PLR (do inglês, PLR) reduzido e suportar um maior número de utilizadores, com débito binário útil e lucro mais elevados (para raios das células até 400 m). Em 4G, com CA, da análise do equilíbrio custos-proveitos com pico-células, o escalonamento multi-banda EMBS (do inglês, Enhanced Multi-band Scheduler) disponibiliza proveitos superiores em comparação com o caso sem CA. Mostra-se claramente que lucro com CA é mais de quatro vezes superior do que no cenário sem CA, o que significa que um aumento ligeiro no custo com CA resulta num aumento de 4-vezes no lucro relativamente ao cenário sem CA

Resource management with adaptive capacity in C-RAN

This work was supported in part by the Spanish ministry of science through the projectRTI2018-099880-B-C32, with ERFD funds, and the Grant FPI-UPC provided by theUPC. It has been done under COST CA15104 IRACON EU project.Efficient computational resource management in 5G Cloud Radio Access Network (CRAN) environments is a challenging problem because it has to account simultaneously for throughput, latency, power efficiency, and optimization tradeoffs. This work proposes the use of a modified and improved version of the realistic Vienna Scenario that was defined in COST action IC1004, to test two different scale C-RAN deployments. First, a large-scale analysis with 628 Macro-cells (Mcells) and 221 Small-cells (Scells) is used to test different algorithms oriented to optimize the network deployment by minimizing delays, balancing the load among the Base Band Unit (BBU) pools, or clustering the Remote Radio Heads (RRH) efficiently to maximize the multiplexing gain. After planning, real-time resource allocation strategies with Quality of Service (QoS) constraints should be optimized as well. To do so, a realistic small-scale scenario for the metropolitan area is defined by modeling the individual time-variant traffic patterns of 7000 users (UEs) connected to different services. The distribution of resources among UEs and BBUs is optimized by algorithms, based on a realistic calculation of the UEs Signal to Interference and Noise Ratios (SINRs), that account for the required computational capacity per cell, the QoS constraints and the service priorities. However, the assumption of a fixed computational capacity at the BBU pools may result in underutilized or oversubscribed resources, thus affecting the overall QoS. As resources are virtualized at the BBU pools, they could be dynamically instantiated according to the required computational capacity (RCC). For this reason, a new strategy for Dynamic Resource Management with Adaptive Computational capacity (DRM-AC) using machine learning (ML) techniques is proposed. Three ML algorithms have been tested to select the best predicting approach: support vector machine (SVM), time-delay neural network (TDNN), and long short-term memory (LSTM). DRM-AC reduces the average of unused resources by 96 %, but there is still QoS degradation when RCC is higher than the predicted computational capacity (PCC). For this reason, two new strategies are proposed and tested: DRM-AC with pre-filtering (DRM-AC-PF) and DRM-AC with error shifting (DRM-AC-ES), reducing the average of unsatisfied resources by 99.9 % and 98 % compared to the DRM-AC, respectively

Towards versatile and robust spectrum sensing in cognitive radio

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A Survey of Blind Modulation Classification Techniques for OFDM Signals

Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communications to improve spectral efficiency and power efficiency, and reduce latency. It will become a integral part of intelligent software-defined radios (SDR) for future communication. In this paper, we provide various MC techniques for orthogonal frequency division multiplexing (OFDM) signals in a systematic way. We focus on the most widely used statistical and machine learning (ML) models and emphasize their advantages and limitations. The statistical-based blind MC includes likelihood-based (LB), maximum a posteriori (MAP) and feature-based methods (FB). The ML-based automated MC includes k-nearest neighbors (KNN), support vector machine (SVM), decision trees (DTs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) based MC methods. This survey will help the reader to understand the main characteristics of each technique, their advantages and disadvantages. We have also simulated some primary methods, i.e., statistical- and ML-based algorithms, under various constraints, which allows a fair comparison among different methodologies. The overall system performance in terms bit error rate (BER) in the presence of MC is also provided. We also provide a survey of some practical experiment works carried out through National Instrument hardware over an indoor propagation environment. In the end, open problems and possible directions for blind MC research are briefly discussed

機械学習を用いたコグニティブ無線における変調方式識別に関する研究

The current spectrum allocation cannot satisfy the demand for future wireless communications, which prompts extensive studies in search of feasible solutions for the spectrum scarcity. The burden in terms of the spectral efficiency on the radio frequency terminal is intended to be small by cognitive radio (CR) systems that prefer low power transmission, changeable carrier frequencies, and diverse modulation schemes. However, the recent surge in the application of the CR has been accompanied by an indispensable component: the spectrum sensing, to avoid interference towards the primary user. This requirement leads to a complex strategy for sensing and transmission and an increased demand for signal processing at the secondary user. However, the performance of the spectrum sensing can be extended by a robust modulation classification (MC) scheme to distinguish between a primary user and a secondary user along with the interference identification. For instance, the underlying paradigm that enables a concurrent transmission of the primary and secondary links may need a precise measure of the interference that the secondary users cause to the primary users. An adjustment to the transmission power should be made, if there is a change in the modulation of the primary users, implying a noise oor excess at the primary user location; else, the primary user will be subject to interference and a collision may occur.Alternatively, the interweave paradigm that progresses the spectrum efficiency by reusing the allocated spectrum over a temporary space, requires a classification of the intercepted signal into primary and secondary systems. Moreover, a distinction between noise and interference can be accomplished by modulation classification, if spectrum sensing is impossible. Therefore, modulation classification has been a fruitful area of study for over three decades.In this thesis, the modulation classification algorithms using machine learning are investigated while new methods are proposed. Firstly, a supervised machine learning based modulation classification algorithm is proposed. The higher-order cumulants are selected as features, due to its robustness to noise. Stacked denoising autoencoders,which is an extended edition of the neural network, is chosen as the classifier. On one hand stacked pre-train overcomes the shortcoming of local optimization, on the other, denoising function further enhances the anti-noise performance. The performance of this method is compared with the conventional methods in terms of the classification accuracy and execution speed. Secondly, an unsupervised machine learning based modulation classification algorithm is proposed.The features from time-frequency distribution are extracted. Density-based spatial clustering of applications with noise (DBSCAN) is used as the classifier because it is impossible to decide the number of clusters in advance. The simulation reveals that this method has higher classification accuracy than the conventional methods. Moreover, the training phase is unnecessary for this method. Therefore, it has higher workability then supervised method. Finally, the advantages and dis-advantages of them are summarized.For the future work, algorithm optimization is still a challenging task, because the computation capability of hardware is limited. On one hand, for the supervised machine learning, GPU computation is a potential solution for supervised machine learning, to reduce the execution cost. Altering the modulation pool, the network structure has to be redesigned as well. On the other hand, for the unsupervised machine learning, that shifting the symbols to carrier frequency consumes extra computing resources.電気通信大学201

Control-data separation architecture for cellular radio access networks: a survey and outlook

Conventional cellular systems are designed to ensure ubiquitous coverage with an always present wireless channel irrespective of the spatial and temporal demand of service. This approach raises several problems due to the tight coupling between network and data access points, as well as the paradigm shift towards data-oriented services, heterogeneous deployments and network densification. A logical separation between control and data planes is seen as a promising solution that could overcome these issues, by providing data services under the umbrella of a coverage layer. This article presents a holistic survey of existing literature on the control-data separation architecture (CDSA) for cellular radio access networks. As a starting point, we discuss the fundamentals, concepts, and general structure of the CDSA. Then, we point out limitations of the conventional architecture in futuristic deployment scenarios. In addition, we present and critically discuss the work that has been done to investigate potential benefits of the CDSA, as well as its technical challenges and enabling technologies. Finally, an overview of standardisation proposals related to this research vision is provided

Interference mitigation in cognitive femtocell networks

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy”.Femtocells have been introduced as a solution to poor indoor coverage in cellular communication which has hugely attracted network operators and stakeholders. However, femtocells are designed to co-exist alongside macrocells providing improved spatial frequency reuse and higher spectrum efficiency to name a few. Therefore, when deployed in the two-tier architecture with macrocells, it is necessary to mitigate the inherent co-tier and cross-tier interference. The integration of cognitive radio (CR) in femtocells introduces the ability of femtocells to dynamically adapt to varying network conditions through learning and reasoning. This research work focuses on the exploitation of cognitive radio in femtocells to mitigate the mutual interference caused in the two-tier architecture. The research work presents original contributions in mitigating interference in femtocells by introducing practical approaches which comprises a power control scheme where femtocells adaptively controls its transmit power levels to reduce the interference it causes in a network. This is especially useful since femtocells are user deployed as this seeks to mitigate interference based on their blind placement in an indoor environment. Hybrid interference mitigation schemes which combine power control and resource/scheduling are also implemented. In a joint threshold power based admittance and contention free resource allocation scheme, the mutual interference between a Femtocell Access Point (FAP) and close-by User Equipments (UE) is mitigated based on admittance. Also, a hybrid scheme where FAPs opportunistically use Resource Blocks (RB) of Macrocell User Equipments (MUE) based on its traffic load use is also employed. Simulation analysis present improvements when these schemes are applied with emphasis in Long Term Evolution (LTE) networks especially in terms of Signal to Interference plus Noise Ratio (SINR)