Georgios Kardaras

Bio: Georgios Kardaras is an academic researcher from Technical University of Denmark. The author has contributed to research in topics: WiMAX & Wireless. The author has an hindex of 6, co-authored 13 publications receiving 1449 citations.

Cloud RAN for Mobile Networks—A Technology Overview

Abstract: Cloud Radio Access Network (C-RAN) is a novel mobile network architecture which can address a number of challenges the operators face while trying to support growing end-user's needs. The main idea behind C-RAN is to pool the Baseband Units (BBUs) from multiple base stations into centralized BBU Pool for statistical multiplexing gain, while shifting the burden to the high-speed wireline transmission of In-phase and Quadrature (IQ) data. C-RAN enables energy efficient network operation and possible cost savings on baseband resources. Furthermore, it improves network capacity by performing load balancing and cooperative processing of signals originating from several base stations. This paper surveys the state-of-the-art literature on C-RAN. It can serve as a starting point for anyone willing to understand C-RAN architecture and advance the research on C-RAN.

Remote radio heads and the evolution towards 4G networks

Abstract: Distributed base stations with remote radio head (RRH) capability greatly help mobile operators to resolve cost, performance, and efficiency challenges when deploying new base stations on the road to fully developed 4G networks. Multi-mode radios capable of operating according to GSM, HSPA, LTE, and WiMAX standards and advanced software configurability are key features in the deployment of more flexible and energy-efficient radio networks. This white paper describes the key market and technology requirements for RRHs and how Radiocomps state-of-the-art WiMAX/LTE RRH and intellectual property (IP) core solutions, combined with latest FPGA technology from Altera, helps design compact, green, and full-featured applications for mobile network solutions.

Advanced multimode radio for wireless & mobile broadband communication

Abstract: Distributed base station architectures represent the new trend that operators follow in order to resolve cost, performance and efficiency challenges when deploying 4G networks. Main components of such architectures are multimode radios capable of operating according to GSM, HSPA, WiMAX and LTE standards, known as remote radio heads (RRH). The key feature of remote radio heads is the extended software configurability which enables the deployment of more flexible and energy-efficient radio solutions. This paper describes a modern multi-mode radio system reference architecture and the major digital building blocks that when combined together enable multi-mode and more power efficient operation. It concentrates on blocks which can efficiently run multi-rate digital signal processing and blocks that increase radio power efficiency by linearizing the power amplifier output stage. The importance of a digital predistortion (DPD) block is emphasized and an adaptive polynomial approach based on cartesian to polar conversion is then proposed. Such radio architecture has successfully been implemented on a low-cost FPGA family meeting the WiMAX/LTE spectrum and Error Vector Magnitude (EVM) requirements.

Integrated service resource reservation using queueing networks theory

Abstract: This study analyses multi-server multi-service queueing networks with service protection. To guarantee each service a certain quality-of-service and at the same time ensure high utilisation of servers, a minimum capacity is reserved each service. In addition, all services share the remaining non-reserved capacity and all buffers in such a way that the system becomes reversible. This implies the model has product form between nodes and is insensitive to the packet size distribution. An analytical model and algorithm for performance evaluation are presented.

Reducing Electricity Demand Peaks by Scheduling Home Appliances Usage

Abstract: Nowadays there is a tendency to consume electricity during the same period of the day leading to demand peaks. Regular energy consumption habits lead to demand peaks at specific temporal intervals, because users consume power at the same time. In order to avoid demand peaks, users’ appliances should consume electricity in a more temporarily distributed way. A new methodology to schedule the usage of home appliances is proposed and analyzed in this paper. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power consumption limit, which is not allowed to be exceeded during peak hours. The scenario simulated describes a modern household, where the electrical devices are classified in low and high priority groups. The high priority devices are always granted power in order to operate without temporal restrictions. On the contrary, the low priority devices have to pause their operation, when the algorithm dictates it, and resume it in the future. This can become beneficial for both energy companies and users. The electricity suppliers companies will be capable of regulating power generation during demand peaks periods. Moreover, users can be granted lower electricity bill rates for accepting delaying the operation of some of their appliances. In order to analyze this scenario, teletraffic engineering theory, which is used in evaluating the performance of telecommunication networks, is used. A reversible fair scheduling (RFS) algorithm, which was originally developed for telecommunication networks, is applied. The purpose is to analyze how a power consumption limit and priorities for home appliances will affect the demand peak and the users’ everyday life. Verification of the effectiveness of the RFS algorithm is done by means of simulation and by using real data for power consumption and operation hours. The defined maximum power limit of 750 and 1000 Watt was not exceeded during peak demand hours. The trade‐off was an average delay of 36,1 and 12,36 minutes, respectively, for the aggregated low priority class.

Next Generation 5G Wireless Networks: A Comprehensive Survey

Abstract: The vision of next generation 5G wireless communications lies in providing very high data rates (typically of Gbps order), extremely low latency, manifold increase in base station capacity, and significant improvement in users’ perceived quality of service (QoS), compared to current 4G LTE networks. Ever increasing proliferation of smart devices, introduction of new emerging multimedia applications, together with an exponential rise in wireless data (multimedia) demand and usage is already creating a significant burden on existing cellular networks. 5G wireless systems, with improved data rates, capacity, latency, and QoS are expected to be the panacea of most of the current cellular networks’ problems. In this survey, we make an exhaustive review of wireless evolution toward 5G networks. We first discuss the new architectural changes associated with the radio access network (RAN) design, including air interfaces, smart antennas, cloud and heterogeneous RAN. Subsequently, we make an in-depth survey of underlying novel mm-wave physical layer technologies, encompassing new channel model estimation, directional antenna design, beamforming algorithms, and massive MIMO technologies. Next, the details of MAC layer protocols and multiplexing schemes needed to efficiently support this new physical layer are discussed. We also look into the killer applications, considered as the major driving force behind 5G. In order to understand the improved user experience, we provide highlights of new QoS, QoE, and SON features associated with the 5G evolution. For alleviating the increased network energy consumption and operating expenditure, we make a detail review on energy awareness and cost efficiency. As understanding the current status of 5G implementation is important for its eventual commercialization, we also discuss relevant field trials, drive tests, and simulation experiments. Finally, we point out major existing research issues and identify possible future research directions.

Non-orthogonal multiple access for 5G: solutions, challenges, opportunities, and future research trends

Abstract: The increasing demand of mobile Internet and the Internet of Things poses challenging requirements for 5G wireless communications, such as high spectral efficiency and massive connectivity. In this article, a promising technology, non-orthogonal multiple access (NOMA), is discussed, which can address some of these challenges for 5G. Different from conventional orthogonal multiple access technologies, NOMA can accommodate much more users via nonorthogonal resource allocation. We divide existing dominant NOMA schemes into two categories: power-domain multiplexing and code-domain multiplexing, and the corresponding schemes include power-domain NOMA, multiple access with low-density spreading, sparse code multiple access, multi-user shared access, pattern division multiple access, and so on. We discuss their principles, key features, and pros/cons, and then provide a comprehensive comparison of these solutions from the perspective of spectral efficiency, system performance, receiver complexity, and so on. In addition, challenges, opportunities, and future research trends for NOMA design are highlighted to provide some insight on the potential future work for researchers in this field. Finally, to leverage different multiple access schemes including both conventional OMA and new NOMA, we propose the concept of software defined multiple access (SoDeMA), which enables adaptive configuration of available multiple access schemes to support diverse services and applications in future 5G networks.

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

Abstract: Technological evolution of mobile user equipment (UEs), such as smartphones or laptops, goes hand-in-hand with evolution of new mobile applications. However, running computationally demanding applications at the UEs is constrained by limited battery capacity and energy consumption of the UEs. A suitable solution extending the battery life-time of the UEs is to offload the applications demanding huge processing to a conventional centralized cloud. Nevertheless, this option introduces significant execution delay consisting of delivery of the offloaded applications to the cloud and back plus time of the computation at the cloud. Such a delay is inconvenient and makes the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling it to run the highly demanding applications at the UE while meeting strict delay requirements. The MEC computing resources can be exploited also by operators and third parties for specific purposes. In this paper, we first describe major use cases and reference scenarios where the MEC is applicable. After that we survey existing concepts integrating MEC functionalities to the mobile networks and discuss current advancement in standardization of the MEC. The core of this survey is, then, focused on user-oriented use case in the MEC, i.e., computation offloading. In this regard, we divide the research on computation offloading to three key areas: 1) decision on computation offloading; 2) allocation of computing resource within the MEC; and 3) mobility management. Finally, we highlight lessons learned in area of the MEC and we discuss open research challenges yet to be addressed in order to fully enjoy potentials offered by the MEC.

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

Abstract: Technological evolution of mobile user equipments (UEs), such as smartphones or laptops, goes hand-in-hand with evolution of new mobile applications. However, running computationally demanding applications at the UEs is constrained by limited battery capacity and energy consumption of the UEs. Suitable solution extending the battery life-time of the UEs is to offload the applications demanding huge processing to a conventional centralized cloud (CC). Nevertheless, this option introduces significant execution delay consisting in delivery of the offloaded applications to the cloud and back plus time of the computation at the cloud. Such delay is inconvenient and make the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling to run the highly demanding applications at the UE while meeting strict delay requirements. The MEC computing resources can be exploited also by operators and third parties for specific purposes. In this paper, we first describe major use cases and reference scenarios where the MEC is applicable. After that we survey existing concepts integrating MEC functionalities to the mobile networks and discuss current advancement in standardization of the MEC. The core of this survey is, then, focused on user-oriented use case in the MEC, i.e., computation offloading. In this regard, we divide the research on computation offloading to three key areas: i) decision on computation offloading, ii) allocation of computing resource within the MEC, and iii) mobility management. Finally, we highlight lessons learned in area of the MEC and we discuss open research challenges yet to be addressed in order to fully enjoy potentials offered by the MEC.

Cloud RAN for Mobile Networks—A Technology Overview

Abstract: Cloud Radio Access Network (C-RAN) is a novel mobile network architecture which can address a number of challenges the operators face while trying to support growing end-user's needs. The main idea behind C-RAN is to pool the Baseband Units (BBUs) from multiple base stations into centralized BBU Pool for statistical multiplexing gain, while shifting the burden to the high-speed wireline transmission of In-phase and Quadrature (IQ) data. C-RAN enables energy efficient network operation and possible cost savings on baseband resources. Furthermore, it improves network capacity by performing load balancing and cooperative processing of signals originating from several base stations. This paper surveys the state-of-the-art literature on C-RAN. It can serve as a starting point for anyone willing to understand C-RAN architecture and advance the research on C-RAN.