5G Research @ Aalto http://5g-research.aalto.fi/en/ Researchers Assist. Prof. Katsuyuki Haneda, Radio science and technology mm-wave channel sounders, channel modeling, antenna design Prof. Risto Wichman, Signal Proc. for communications MIMO for LTE, Massive MIMO (channel estimation), full-duplex radio, Dirty RF, Geolocation databases for TVWS, Stochastic geometry Lecturer Kalle Ruttik, Communications Engineering Software Defined Radio, C-RAN, implementation studies Prof. Jyri Hämäläinen, Mobile communications Network architectures, relays, small cells, DAS, HetNets, RRM, public safety communications, 3GPP compliant simulation tools Prof. Olav Tirkkonen, Communications theory Prof. Tarik Taleb, Networking technology Self-organization, flexible spectrum user, D2D Coding theory (codebooks for massive MIMO), RF imprirments, Statistics for communications Implementation studies Radio access networks, cloud-communications Prof. Riku Jäntti, Communications engineering Staff Scientist Jose Costa Requena, Networking technology Flexible spectrum use, interference modeling and control (ultradense networks), MTC (capillary/sensor networks, wireless automation), indoor DAS, Implementation studies Packet core virtualization, Software Defined Networking, implementation studies 5G challenges • 1000 x more capacity • Ultra-reliable communications 5G challenges Author NSN Huawei NTT Docomo Zander & Mähönen Spectral Total Capacity Spectrum Efficiency Densification Increase 10X 10X 10X 1000X 3X 3.3X 10X 100X 2.8X 24X 15X 1000X 3X 5X 66X 1000X I Spectrum Spectrum • Most of the current mobile radio systems operate on overcrowded bands between 450MHz and 3.5GHz. • On the other hand, between 3.5GHz and 60GHz there is currently around 7GHz unlisenced spectrum available, including large contiguous bands • New access frequency can be made available much more easily on 10-60GHz than below 3.5GHz frequencies. • In the following we introduce some new directions for the mobile systems research on mm-wave frequencies making – somewhat strong - assumptions on the channel properties. From multipath communication to dominant path communication Some mm-wave channel characteristics: – Received power in isotropic antenna is decreasing when TX RX carrier frequency increases – Diffraction losses are tremendously large on high RX frequencies – Signal wall penetration losses are heavy Dominant path communication: – Signal reflections occur but • Major part of the received power signal power decreases heavily comes through line-of-sight and/or in each reflection first reflected signal component. Mm-Wave Channel Modeling Field scattering is limited only to single-bounce 5 Mm-Wave Channel Modeling 1. Are mm-wave radio channels sufficiently multipath-rich to support spatial multiplexing in MIMO transmission? – Yes they are, often as much as lower frequency channels do. x! Window! Pillar! Table! y! Shelf! 7 m! Tx! Rx! 5! 7! 4! 6! 12! 17! 11! 16! 3! 10! 15! 2! 9! 14! 8! 13! 1! Tables! Tx w/o NLOS meas.! Chairs! 6.75 m! 9 Implications from dominant path presumption • Cell shapes – The cell shapes become quasi-deterministic – The cell edges will be sharp – Coverage areas will be usually defined by surrounding physical obstacles – Currently used shadow fading model becomes irrelevant • Coverage vs interference – If cell overlap exists, overheard signals are usually strong. – Shot noise type of interference occurs – unless coordinated communication is applied. • Control approaches – Reactive control structures: Based on e.g. UE and eNB measurements. – Proactive control: Traces and traffic statistics could be used. – Out of band control (<3.5 GHz)? • Multiantenna systems – Integrated antenna arrays become feasible even in mobile devices – Beamforming/steerable directive antennas provide means to overcome heavy attenuation losses. – Due to frequent LOS and large BWs the importance of spatial multiplexing decreases. – Paradigm shift from passive isotropic/sectorized to active directive radio communication Much can be infered from RSS • RSS based fingerprints (Radio maps) can be utilized to discover samall cells in HetNets • RSS based inference: devicer free localization, breathing rate estimation, … Most accurate indoor localization technology Evaluating AAL Systems through Competitive Benchmarking September 2012 Award for "Most accurate indoor localization technology" at the "Evaluating AAL Systems through Competitive Benchmarking" 2012 International Competition. mm-wave antennas Mm-Wave Antennas • Integrated lens antenna with beam-steering capability – Reduction of internal reflections with low permittivity material – Reduction of side-lobe levels, increased cross-polarization discrimination and mutual coupling Mm-Wave Antennas • On-chip beam-steering antenna Bulk process 500 µm thick HR silicon Metal BCB membrane 10.5mm membrane 3.3mm monopole Y Bulk silicon substrate CPW X gold Z port 1 port 2 port 3 port 4 Z Membrane process Metal BCB membrane port 5 Max gain 3.8 dBi Mm-Wave Antennas • Dielectric rod waveguide antenna Si HR Y X Radiation 15 efficiency 84 % – Very wide operating frequency range: from 75 GHz to 1.1 THz – Radiation pattern is almost independent of frequency – Easily integrated into RF components, e.g., directional couplers, phase shifters, amplifiers, and power sensors II Spectral efficiency Massive and networked MIMO • Practical massive MIMO – Remove the pilot contamination problem – Channel estimation based on subspace approach, random matrix theory – Codebooks for massive MIMO – Closed form low coherence frames / Grassmannian codebooks for k-dimensional subspaces in 2m – dimensional spaces, some optimal – Stiefel & Grassmannian codebooks – Convergence of gradient search for low-dimensional matrix completion in high-dimensional spaces – Minimum distance bounds on Stiefel and Grassmannian manifolds • Distributed antenna systems – Over the air synchronization of remote radio units – Centralized base band processing Self-backhauling (Large system) analysis of full-duplex/half-duplex trade-offs taking into account the self-interferference Multihop local area network with full-duplex access points/relays Routing + precoding + interference cancellation Goal: Design a local area network using practical performance figures for full-duplex transceivers 0.8 One hop 1-2 hop Half Duplex 1-2 hop FD, 80 dB attenuation 1-2 hop FD, 90 dB attenuation 1-2 hop FD, no self-interference 0.7 0.6 0.5 CDF • • • • 0.4 0.3 0.2 0.1 0 0.2 0.4 0.6 0.8 1 1.2 Throughput [bps] 1.4 1.6 1.8 2 9 x 10 Full-duplex antenna • Simultaneous receiving and • Transmitting / jamming • Spectrum sensing • Full-duplex Full-duplex antenna design • Relays • Access points • System design • 50dB attenuation on self-interference by antenna design • Nonlinear cancellation of self-interference (~40 dB additional gain by analog and digital cancellation) Full-duplex tranceiver design Cancellation of self-interference by digital signal processing III Densification Virtualization • In Cloud Radio Access Networks (C-RAN), the radio access network (RAN) functionality is moved to the cloud computing infrastructure. • Remote radio units (RRU) of different cells are connected to the cloud via a high speed front-haul link, such as a fiber network. • Unlike classical cellular system where a baseband processing unit is deployed in each cell cite, C-RAN has a central processing system in the cloud. • Advantages: – RRU’s have much less energy consumption and require less CAPEX and OPEX than traditional basestations – C-RAN provides flexibility in terms of signal processing complexity and coordination among cells and networks such that resources can be used efficiently. Aalto C-RAN based TD-LTE testbed Physical Architecture • Network densification with low power cells provides high capacity especially in hotspots. However, in this scenario, interference is the biggest challenge. Hence, inter-cell coordination and joint processing, which are inherent to C-RAN, are vital to achieve the maximum capacity gain. Aalto eMME Architecture AALTO TD-LTE TESTBED • TD-LTE System – Implementation of TD-LTE tesbed (Rel. 8) on general purpose processors and non-real-time operation system – Over 30 000 lines of C++ code – PHY and limited set of RRC and MAC functions – Cloud-RAN setup – Base station can run on virtual server – Flexible spectrum use – Can interact with Fairspectrum geo-location data base – TVWS operation – D2D implementation – Network controlled D2D Cloud RAN architecture – Reliable D2D links – DAS implementation – Antenna port selection – Open loop transmit diversity Remote radio units IV Ultra-reliable communications Ultra-reliable / mission critical MTC • Ultra-reliable low latency D2D communications – Overlay D2D – CQI feedback – Protected D2D resources • Distributed antenna system – Resilience against HW failures – Improved coverage Summary • 5G requirements imposes many challenges – Capacity – Latency – Reliability • Enabling technologies – – – – – New control architectures mm-wave massive and networked MIMO ultra dense networks Scalability and flexibility through Cloud technologies
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