319 research outputs found

    Architectures and Key Technical Challenges for 5G Systems Incorporating Satellites

    Get PDF
    Satellite Communication systems are a promising solution to extend and complement terrestrial networks in unserved or under-served areas. This aspect is reflected by recent commercial and standardisation endeavours. In particular, 3GPP recently initiated a Study Item for New Radio-based, i.e., 5G, Non-Terrestrial Networks aimed at deploying satellite systems either as a stand-alone solution or as an integration to terrestrial networks in mobile broadband and machine-type communication scenarios. However, typical satellite channel impairments, as large path losses, delays, and Doppler shifts, pose severe challenges to the realisation of a satellite-based NR network. In this paper, based on the architecture options currently being discussed in the standardisation fora, we discuss and assess the impact of the satellite channel characteristics on the physical and Medium Access Control layers, both in terms of transmitted waveforms and procedures for enhanced Mobile BroadBand (eMBB) and NarrowBand-Internet of Things (NB-IoT) applications. The proposed analysis shows that the main technical challenges are related to the PHY/MAC procedures, in particular Random Access (RA), Timing Advance (TA), and Hybrid Automatic Repeat reQuest (HARQ) and, depending on the considered service and architecture, different solutions are proposed.Comment: Submitted to Transactions on Vehicular Technologies, April 201

    A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead

    Get PDF
    Physical layer security which safeguards data confidentiality based on the information-theoretic approaches has received significant research interest recently. The key idea behind physical layer security is to utilize the intrinsic randomness of the transmission channel to guarantee the security in physical layer. The evolution towards 5G wireless communications poses new challenges for physical layer security research. This paper provides a latest survey of the physical layer security research on various promising 5G technologies, including physical layer security coding, massive multiple-input multiple-output, millimeter wave communications, heterogeneous networks, non-orthogonal multiple access, full duplex technology, etc. Technical challenges which remain unresolved at the time of writing are summarized and the future trends of physical layer security in 5G and beyond are discussed.Comment: To appear in IEEE Journal on Selected Areas in Communication

    D6.3 Intermediate system evaluation results

    Full text link
    The overall purpose of METIS is to develop a 5G system concept that fulfil s the requirements of the beyond-2020 connected information society and to extend todayโ€™s wireless communication systems for new usage cases. First, in this deliverable an updated view on the overall METIS 5G system concept is presented. Thereafter, simulation results for the most promising technology components supporting the METIS 5G system concept are reported. Finally, s imulation results are presented for one relevant aspect of each Horizontal Topic: Direct Device - to - Device Communication, Massive Machine Communication, Moving Networks, Ultra - Dense Networks, and Ultra - Reliable Communication.Popovski, P.; Mange, G.; Fertl, P.; Gozรกlvez - Serrano, D.; Droste, H.; Bayer, N.; Roos, A.... (2014). D6.3 Intermediate system evaluation results. http://hdl.handle.net/10251/7676

    ์…€๋ฃฐ๋Ÿฌ ์‚ฌ์ด๋“œ๋งํฌ ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ์œ„ํ•œ ์ƒ์œ„๊ณ„์ธต ๊ธฐ๋ฒ•

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2020. 8. ๋ฐ•์„ธ์›….In typical cellular communications, User Equipments (UEs) have always had to go through a Base Station (BS) to communicate with each other, e.g., a UE transmits a packet to a BS via uplink and then the BS transmits the packet to another UE via downlink. Although the communication method can serve UEs efficiently, the communication method can cause latency problems and overload problems in BS. Thus, sidelink has been proposed to overcome these problems in 3GPP release 12. Through sidelink, UEs can communicate directly with each other. There are two representative communications using sidelink, i.e., Device-to-Device (D2D) communication and Vehicle-to-Vehicle (V2V) communication. In this dissertation, we consider three strategies to enhance the performances of D2D and V2V communications: (i) efficient feedback mechanism for D2D communications, (ii) context-aware congestion control scheme for V2V communication, and (iii) In-Device Coexistence (IDC)-aware LTE and NR sidelink resource allocation scheme. Firstly, in the related standard, there is no feedback mechanism for D2D communication because D2D communications only support broadcast-type communications. A feedback mechanism is presented for D2D communications. Through our proposed mechanism, UEs can use the feedback mechanism without the help of BS and UEs do not need additional signals to allocate feedback resources. We also propose a rate adaptation algorithm, which consider in-band emission problem, on top of the proposed feedback mechanism. We find that our rate adaptation achieves higher and stable throughput compared with the legacy scheme that complies to the standard. Secondly, we propose a context-aware congestion control scheme for LTE-V2V communication. Through LTE-V2V communication, UEs transmit Cooperative Awareness Message (CAM), which is a periodic message, and Decentralized Environmental Notification Message (DENM), which is a event-driven message and allows one-hop relay. The above two messages have different characteristics and generation rule. Thus, it is difficult and inefficient to apply the same congestion control scheme to two messages. We propose a congestion control schemes for each message. Through the proposed congestion control schemes, UEs decide whether to transmit according to their situation. Through simulation results, we show that our proposed schemes outperform comparison schemes as well as the legacy scheme. Finally, we propose a NR sidelink resource allocation scheme based on multi-agent reinforcement learning, which awares a IDC problem between LTE and NR in Intelligent Transport System (ITS) band. First, we model a realistic IDC interference based on spectrum emission mask specified at the standard. Then, we formulate the resource allocation as a multi-agent reinforcement learning with fingerprint method. Each UE achieves its local observation and rewards, and learns its policy to increase its rewards through updating Q-network. Through simulation results, we observe that the proposed resource allocation scheme further improves Packet Delivery Ratio (PDR) performances compared to the legacy scheme.์ „ํ˜•์ ์ธ ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹ ์—์„œ๋Š”, ๋‹จ๋ง๋“ค์€ ์„œ๋กœ ํ†ต์‹ ํ•˜๊ธฐ ์œ„ํ•ด ํ•ญ์ƒ ๊ธฐ์ง€๊ตญ์„ ๊ฑฐ์ณ์•ผ ํ•œ๋‹ค. ์˜ˆ๋ฅผ ๋“ค๋ฉด, ๋‹จ๋ง์ด uplink๋ฅผ ํ†ตํ•ด ๊ธฐ์ง€๊ตญ์—๊ฒŒ ํŒจํ‚ท์„ ์ „์†กํ•œ ๋‹ค์Œ ๊ธฐ์ง€๊ตญ์€ downlink๋ฅผ ํ†ตํ•ด ํ•ด๋‹น ํŒจํ‚ท์„ ์ „์†กํ•ด์ค€๋‹ค. ์ด๋Ÿฌํ•œ ํ†ต์‹ ๋ฐฉ์‹์€ ๋‹จ๋ง๋“ค์—๊ฒŒ ํšจ์œจ์ ์œผ๋กœ ์„œ๋น„์Šค๋ฅผ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ์ƒํ™ฉ์— ๋”ฐ๋ผ์„œ๋Š” ์ง€์—ฐ๋ฌธ์ œ์™€ ๊ธฐ์ง€๊ตญ์˜ ๊ณผ๋ถ€ํ•˜ ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐํ•  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ 3GPP release12์—์„œ ์ด๋Ÿฌํ•œ ๋ฌธ์ œ์ ๋“ค์„ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด sidelink๊ฐ€ ์ œ์•ˆ๋˜์—ˆ๋‹ค. ๋•๋ถ„์— ๋‹จ๋ง๋“ค์€ sidelink๋ฅผ ํ†ตํ•ด์„œ ์„œ๋กœ ์ง์ ‘ ํ†ต์‹ ์„ ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋˜์—ˆ๋‹ค. Sidelink๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๋‘ ๊ฐ€์ง€ ๋Œ€ํ‘œ์ ์ธ ํ†ต์‹ ์€ D2D(Device-to-Device) ํ†ต์‹ ๊ณผ V2V(Vehicle-to-Vehicle) ํ†ต์‹ ์ด๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” D2D ์™€ V2V ํ†ต์‹  ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ์„ธ๊ฐ€์ง€ ์ „๋žต์„ ๊ณ ๋ คํ•œ๋‹ค. (i) D2D ํ†ต์‹ ์„ ์œ„ํ•œ ํšจ์œจ์ ์ธ ํ”ผ๋“œ๋ฐฑ ๋ฉ”์ปค๋‹ˆ์ฆ˜, (ii) V2V ํ†ต์‹ ์„ ์œ„ํ•œ ์ƒํ™ฉ์ธ์‹๊ธฐ๋ฐ˜ ํ˜ผ์žก์ œ์–ด ๊ธฐ๋ฒ•, ๊ทธ๋ฆฌ๊ณ  (iii) IDC(In-Device Coexistence) ์ธ์ง€ ๊ธฐ๋ฐ˜ sidelink ์ž์› ํ• ๋‹น ๋ฐฉ์‹. ์ฒซ์งธ, ๊ด€๋ จ ํ‘œ์ค€์—๋Š” D2D ํ†ต์‹ ์ด ๋ธŒ๋กœ๋“œ์บ์ŠคํŠธ ์œ ํ˜•์˜ ํ†ต์‹ ๋งŒ์„ ์ง€์›ํ•˜๊ธฐ ๋•Œ๋ฌธ์— D2D ํ†ต์‹ ์— ๋Œ€ํ•œ ํ”ผ๋“œ๋ฐฑ ๋ฉ”์ปค๋‹ˆ์ฆ˜์ด ์—†๋‹ค. ์šฐ๋ฆฌ๋Š” ์ด๋Ÿฌํ•œ ํ•œ๊ณ„์ ์„ ๊ทน๋ณตํ•˜๊ณ ์ž D2D ํ†ต์‹ ์„ ์œ„ํ•œ ํ”ผ๋“œ๋ฐฑ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ํ†ตํ•ด, ๋‹จ๋ง์€ ๊ธฐ์ง€๊ตญ์˜ ๋„์›€์—†์ด ํ”ผ๋“œ๋ฐฑ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ ํ”ผ๋“œ๋ฐฑ ์ž์›์„ ํ• ๋‹นํ•˜๊ธฐ ์œ„ํ•œ ์ถ”๊ฐ€ ์‹ ํ˜ธ๋ฅผ ํ•„์š”๋กœ ํ•˜์ง€ ์•Š๋Š”๋‹ค. ์šฐ๋ฆฌ๋Š” ๋˜ํ•œ ์ œ์•ˆ๋œ ํ”ผ๋“œ๋ฐฑ ๋ฉ”์ปค๋‹ˆ์ฆ˜์œ„์—์„œ ๋™์ž‘ํ•  ์ˆ˜ ์žˆ๋Š” data rate ์กฐ์ ˆ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ์šฐ๋ฆฌ๋Š” ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•˜์—ฌ, ์ œ์•ˆํ•œ data rate ์กฐ์ ˆ ๊ธฐ๋ฒ•์ด ๊ธฐ์กด ๋ฐฉ์‹๋ณด๋‹ค ๋” ๋†’๊ณ  ์•ˆ์ •์ ์ธ ์ˆ˜์œจ์„ ์ œ๊ณตํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋‘˜์งธ, LTE-V2V ํ†ต์‹ ์„ ์œ„ํ•œ ์ƒํ™ฉ ์ธ์ง€ ๊ธฐ๋ฐ˜ ํ˜ผ์žก ์ œ์–ด ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. LTE-V2V ํ†ต์‹ ์—์„œ ๋‹จ๋ง๋“ค์€ ์ฃผ๊ธฐ์ ์ธ ๋ฉ”์‹œ์ง€์ธ CAM(Cooperative Awareness Message) ๋ฐ ๋น„์ฃผ๊ธฐ์  ๋ฉ”์‹œ์ง€์ด๋ฉฐ one-hop๋ฆด๋ ˆ์ด๋ฅผ ํ—ˆ์šฉํ•˜๋Š” DENM(Decentralized Environmental Notification Message)๋ฅผ ์ „์†กํ•œ๋‹ค. ์œ„์˜ ๋‘ ๋ฉ”์‹œ์ง€๋Š” ํŠน์„ฑ๊ณผ ์ƒ์„ฑ ๊ทœ์น™์ด ๋‹ค๋ฅด๊ธฐ ๋•Œ๋ฌธ์— ๋™์ผํ•œ ํ˜ผ์žก ์ œ์–ด ๊ธฐ๋ฒ•์„ ์ ์šฉํ•˜๋Š” ๊ฒƒ์€ ๋น„ํšจ์œจ์ ์ด๋‹ค. ๋”ฐ๋ผ์„œ ์šฐ๋ฆฌ๋Š” ๊ฐ ๋ฉ”์‹œ์ง€์— ์ ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ํ˜ผ์žก ์ œ์–ด ๊ธฐ๋ฒ•๋“ค์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•๋“ค์„ ํ†ตํ•ด์„œ ๋‹จ๋ง๋“ค์€ ๊ทธ๋“ค์˜ ์ƒํ™ฉ์— ๋”ฐ๋ผ์„œ ์ „์†ก ์—ฌ๋ถ€๋ฅผ ๊ฒฐ์ •ํ•˜๊ฒŒ ๋œ๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์ด ๊ธฐ์กด ํ‘œ์ค€ ๋ฐฉ์‹ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ตœ์‹ ์˜ ๋น„๊ต ๊ธฐ๋ฒ•๋“ค๋ณด๋‹ค ์šฐ์ˆ˜ํ•œ ์„ฑ๋Šฅ์„ ์–ป๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ITS(Intelligent Transport System)๋Œ€์—ญ์—์„œ LTE์™€ NR์‚ฌ์ด์˜ IDC๋ฌธ์ œ๋ฅผ ๊ณ ๋ คํ•˜๋Š” NR sidelink ์ž์›ํ• ๋‹น ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋จผ์ €, ํ‘œ์ค€์— ์ง€์ •๋œ ์ŠคํŽ™ํŠธ๋Ÿผ ๋ฐฉ์ถœ ๋งˆ์Šคํฌ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ˜„์‹ค์ ์ธ IDC ๊ฐ„์„ญ์„ ๋ชจ๋ธ๋งํ•œ๋‹ค. ๊ทธ๋Ÿฐ ๋‹ค์Œ ๋‹ค์ค‘ ์—์ด์ „ํŠธ ๊ฐ•ํ™”ํ•™์Šต์œผ๋กœ ์ž์›ํ• ๋‹น ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๊ฐ ๋‹จ๋ง๋“ค์€ ์ž์‹ ๋“ค์˜ ์ฃผ๋ณ€ ํ™˜๊ฒฝ์„ ๊ด€์ธกํ•˜๊ณ  ๊ด€์ธก๋œ ํ™˜๊ฒฝ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ–‰๋™ํ•˜์—ฌ ๋ณด์ƒ์„ ์–ป๊ณ  Q-network์„ ์ž์‹ ์˜ ๋ณด์ƒ์„ ์ฆ๊ฐ€์‹œํ‚ค๋„๋ก ์ •์ฑ…์„ ์—…๋ฐ์ดํŠธ ๋ฐ ํ•™์Šตํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•˜์—ฌ ์ œ์•ˆ๋œ ์ž์›ํ• ๋‹น ๋ฐ•์‹์ด ๊ธฐ์กด๊ธฐ๋ฒ• ๋Œ€๋น„ํ•˜์—ฌ PDR(Packet Delivery Ratio) ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค.Introduction 1 Efficient feedback mechanism for LTE-D2D Communication 8 CoCo: Context-aware congestion control scheme for C-V2X communications 35 IDC-aware resource allocation based on multi-agents reinforcement learning 67 Concluding remarks 84 Abstract(In Korean) 96 ๊ฐ์‚ฌ์˜ ๊ธ€ 99Docto

    Recent advances in radio resource management for heterogeneous LTE/LTE-A networks

    Get PDF
    As heterogeneous networks (HetNets) emerge as one of the most promising developments toward realizing the target specifications of Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, radio resource management (RRM) research for such networks has, in recent times, been intensively pursued. Clearly, recent research mainly concentrates on the aspect of interference mitigation. Other RRM aspects, such as radio resource utilization, fairness, complexity, and QoS, have not been given much attention. In this paper, we aim to provide an overview of the key challenges arising from HetNets and highlight their importance. Subsequently, we present a comprehensive survey of the RRM schemes that have been studied in recent years for LTE/LTE-A HetNets, with a particular focus on those for femtocells and relay nodes. Furthermore, we classify these RRM schemes according to their underlying approaches. In addition, these RRM schemes are qualitatively analyzed and compared to each other. We also identify a number of potential research directions for future RRM development. Finally, we discuss the lack of current RRM research and the importance of multi-objective RRM studies
    • โ€ฆ
    corecore