199 research outputs found
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Low-Complexity Multi-User MIMO Algorithms for mmWave WLANs
Very high throughput and high-efficiency wireless local area networks (WLANs) have become essential for today's significant global Internet traffic and the expected significant global increase of public WiFi hotspots. Total Internet traffic is predicted to expand 3.7-fold from 2017 to 2022. In 2017, 53% of overall Internet traffic used by WiFi networks, and that number is expected to increase to 56.8% by 2022. Furthermore, 80% of overall Internet traffic is expected to be video traffic by 2022, up from 70% in 2017. WiFi networks are also expected to move towards denser deployment scenarios, such as stadiums, large office buildings, and airports, with very high data rate applications, such as ultra-high definition video wireless streaming. Thus, in order to meet the predicted growth of wireless traffic and the number of WiFi networks in the world, an efficient Internet access solution is required for the current IEEE 802.11 standards.
Millimeter wave (mmWave) communication technology is expected to play a crucial role in future wireless networks with large user populations because of the large spectrum band it can provide. To further improve spectrum efficiency over mmWave bands in WLANs with large numbers of users, the IEEE 802.11ay standard was developed from the traditional IEEE 802.11ad standard, aiming to support multi-user MIMO. Propagation challenges associated with mmWave bands necessitate the use of analog beamforming (BF) technologies that employ directional transmissions to determine the optimal sector beam between a transmitter and a receiver. However, the multi-user MIMO is not exploited, since analog BF is limited to a single-user, single-transmission. The computational complexity of achieving traditional multi-user MIMO BF methods, such as full digital BF, in the mmWave systems becomes significant due to the hardware constraints. Our research focuses on how to effectively and efficiently realize multi-user MIMO transmission to improve spectrum efficiency over the IEEE 802.11ay mmWave band system while also resolving the computational complexity challenges for achieving a multi-user MIMO in mmWave systems.
This thesis focuses on MAC protocol algorithms and analysis of the IEEE 802.11ay mmWave WLANs to provide multi-user MIMO support in various scenarios to improve the spectrum efficiency and system throughput. Specifically, from a downlink single-hop scenario perspective, a VG algorithm is proposed to schedule simultaneous downlink transmission links while mitigating the multi-user interference with no additional computational complexity. From a downlink multi-hop scenario perspective, a low-complexity MHVG algorithm is conducted to realize simultaneous transmissions and improve the network performance by taking advantage of the spatial reuse in a dense network. The proposed MHVG algorithm permits simultaneous links scheduling and mitigates both the multi-user interference and co-channel interference based only on analog BF information, without the necessity for feedback overhead, such as channel state information (CSI). From an uplink scenario perspective, a low-complexity user selection algorithm, HBF-VG, incorporates user selection with the HBF algorithm to achieve simultaneous uplink transmissions for IEEE 802.11ay mmWave WLANs. With the HBF-VG algorithm, the users can be selected based on an orthogonality criterion instead of collecting CSI from all potential users. We optimize the digital BF to mitigate the residual interference among selected users. Extensive analytical and simulation evaluations are provided to validate the performance of the proposed algorithms with respect to average throughput per time slot, average network throughput, average sum-rate, energy efficiency, signal-to-interference-plus-noise ratio (SINR), and spatial multiplexing gain
Massive MIMO for Internet of Things (IoT) Connectivity
Massive MIMO is considered to be one of the key technologies in the emerging
5G systems, but also a concept applicable to other wireless systems. Exploiting
the large number of degrees of freedom (DoFs) of massive MIMO essential for
achieving high spectral efficiency, high data rates and extreme spatial
multiplexing of densely distributed users. On the one hand, the benefits of
applying massive MIMO for broadband communication are well known and there has
been a large body of research on designing communication schemes to support
high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT)
is still a developing topic, as IoT connectivity has requirements and
constraints that are significantly different from the broadband connections. In
this paper we investigate the applicability of massive MIMO to IoT
connectivity. Specifically, we treat the two generic types of IoT connections
envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable
low-latency communication (URLLC). This paper fills this important gap by
identifying the opportunities and challenges in exploiting massive MIMO for IoT
connectivity. We provide insights into the trade-offs that emerge when massive
MIMO is applied to mMTC or URLLC and present a number of suitable communication
schemes. The discussion continues to the questions of network slicing of the
wireless resources and the use of massive MIMO to simultaneously support IoT
connections with very heterogeneous requirements. The main conclusion is that
massive MIMO can bring benefits to the scenarios with IoT connectivity, but it
requires tight integration of the physical-layer techniques with the protocol
design.Comment: Submitted for publicatio
Reconfigurable Intelligent Surfaces for 6G -- Applications, Challenges and Solutions
It is expected that scholars will continuously strengthen the depth and
breadth of theoretical research on RIS, and provide a higher theoretical upper
bound for the engineering application of RIS. While making breakthroughs in
academic research, it has also made rapid progress in engineering application
research and industrialization promotion. This paper will provide an overview
of RIS engineering applications, and make a systematic and in-depth analysis of
the challenges and candidate solutions of RIS engineering applications. Future
trends and challenges are also provided.Comment: 2
D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies
This document provides the most recent updates on the technical contributions and research
challenges focused in WP3. Each Technology Component (TeC) has been evaluated
under possible uniform assessment framework of WP3 which is based on the simulation guidelines
of WP6. The performance assessment is supported by the simulation results which are in their
mature and stable state. An update on the Most Promising Technology Approaches (MPTAs)
and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission
technologies in 5G systems has also been provided. This consolidated view is further
supported in this document by the presentation of the impact of MPTAs on METIS scenarios
and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675
Multiuser MIMO techniques with feedback
Kooperative Antennenanlagen haben vor kurzem einen heißen Forschungsthema geworden, da Sie deutlich höhere spektrale Effizienz als herkömmliche zelluläre Systeme versprechen. Der Gewinn wird durch die Eliminierung von Inter-Zelle Störungen (ICI) durch Koordinierung der-Antenne Übertragungen erworben. Vor kurzem, verteilte Organisation Methoden vorgeschlagen. Eine der größten Herausforderungen für das Dezentrale kooperative Antennensystem ist Kanalschätzung für den Downlink Kanal besonders wenn FDD verwendet wird. Alle zugehörigen Basisstationen im genossenschaftlichen Bereich müssen die vollständige Kanal Informationen zu Wissen, die entsprechenden precoding Gewicht Matrix zu berechnen. Diese Information ist von mobilen Stationen übertragen werden Stationen mit Uplink Ressourcen zu stützen. Wird als mehrere Basisstationen und mehreren mobilen Stationen in kooperativen Antennensysteme und jede Basisstation und Mobilstation beteiligt sind, können mit mehreren Antennen ausgestattet sein, die Anzahl der Kanal Parameter wieder gefüttert werden erwartet, groß zu sein. In dieser Arbeit wird ein effizientes Feedback Techniken der downlink Kanal Informationen sind für die Multi-user Multiple Input Multiple Output Fall vorgeschlagen, der insbesondere auf verteilte kooperative Antennensysteme zielt. Zuerst wird ein Unterraum-basiertes Kanalquantisierungsverfahren vorgeschlagen, das ein vorbestimmtes Codebuch verwendet. Ein iterativer Codebuchentwurfsalgorithmus wird vorgeschlagen, der zu einem lokalen optimalen Codebuch konvergiert. Darüber hinaus werden Feedback-Overhead-Reduktionsverfahren entwickelt, die die zeitliche Korrelation des Kanals ausnutzen. Es wird gezeigt, dass das vorgeschlagene adaptive Codebuchverfahren in Verbindung mit einem Datenkomprimierungsschema eine Leistung nahe an dem perfekten Kanalfall erzielt, was viel weniger Rückkopplungsoverhead im Vergleich zu anderen Techniken erfordert. Das auf dem Unterraum basierende Kanalquantisierungsverfahren wird erweitert, indem mehrere Antennen auf der Senderseite und/oder auf der Empfängerseite eingeführt werden, und die Leistung eines Vorcodierungs- (/Decodierungs-) Schemas mit regulierter Blockdiagonalisierung (RBD) wurde untersucht. Es wird ein kosteneffizientes Decodierungsmatrixquantisierungsverfahren vorgeschlagen, dass eine komplexe Berechnung an der Mobilstation vermeiden kann, während es nur eine leichte Verschlechterung zeigt. Die Arbeit wird abgeschlossen, indem die vorgeschlagenen Feedback-Methoden hinsichtlich ihrer Leistung, ihres erforderlichen Feedback-Overheads und ihrer Rechenkomplexität verglichen werden.Cooperative antenna systems have recently become a hot research topic, as they promise significantly higher spectral efficiency than conventional cellular systems. The gain is acquired by eliminating inter-cell interference (ICI) through coordination of the base antenna transmissions. Recently, distributed organization methods have been suggested. One of the main challenges of the distributed cooperative antenna system is channel estimation for the downlink channel especially when FDD is used. All of the associated base stations in the cooperative area need to know the full channel state information to calculate the corresponding precoding weight matrix. This information has to be transferred from mobile stations to base stations by using uplink resources. As several base stations and several mobile stations are involved in cooperative antenna systems and each base station and mobile station may be equipped with multiple antennas, the number of channel state parameters to be fed back is expected to be big. In this thesis, efficient feedback techniques of the downlink channel state information are proposed for the multi-user multiple-input multiple-output case, targeting distributed cooperative antenna systems in particular. First, a subspace based channel quantization method is proposed which employs a predefined codebook. An iterative codebook design algorithm is proposed which converges to a local optimum codebook. Furthermore, feedback overhead reduction methods are devised exploiting temporal correlation of the channel. It is shown that the proposed adaptive codebook method in conjunction with a data compression scheme achieves a performance close to the perfect channel case, requiring much less feedback overhead compared with other techniques. The subspace based channel quantization method is extended by introducing multiple antennas at the transmitter side and/or at the receiver side and the performance of a regularized block diagonalization (RBD) precoding(/decoding) scheme has been investigated as well as a zero-forcing (ZF) precoding scheme. A cost-efficient decoding matrix quantization method is proposed which can avoid a complex computation at the mobile station while showing only a slight degradation. The thesis is concluded by comparing the proposed feedback methods in terms of their performance, their required feedback overhead, and their computational complexity. The techniques that are developed in this thesis can be useful and applicable for 5G, which is envisioned to support the high granularity/resolution codebook and its efficient deployment schemes. Keywords: MU-MIMO, COOPA, limited feedback, CSI, CQ, feedback overhead reduction, Givens rotatio
Multi-Antenna Techniques for Next Generation Cellular Communications
Future cellular communications are expected to offer substantial improvements for the pre- existing mobile services with higher data rates and lower latency as well as pioneer new types of applications that must comply with strict demands from a wider range of user types. All of these tasks require utmost efficiency in the use of spectral resources. Deploying multiple antennas introduces an additional signal dimension to wireless data transmissions, which provides a significant alternative solution against the plateauing capacity issue of the limited available spectrum. Multi-antenna techniques and the associated key enabling technologies possess unquestionable potential to play a key role in the evolution of next generation cellular systems.
Spectral efficiency can be improved on downlink by concurrently serving multiple users with high-rate data connections on shared resources. In this thesis optimized multi-user multi-input multi-output (MIMO) transmissions are investigated on downlink from both filter design and resource allocation/assignment points of view. Regarding filter design, a joint baseband processing method is proposed specifically for high signal-to-noise ratio (SNR) conditions, where the necessary signaling overhead can be compensated for. Regarding resource scheduling, greedy- and genetic-based algorithms are proposed that demand lower complexity with large number of resource blocks relative to prior implementations.
Channel estimation techniques are investigated for massive MIMO technology. In case of channel reciprocity, this thesis proposes an overhead reduction scheme for the signaling of user channel state information (CSI) feedback during a relative antenna calibration. In addition, a multi-cell coordination method is proposed for subspace-based blind estimators on uplink, which can be implicitly translated to downlink CSI in the presence of ideal reciprocity. Regarding non-reciprocal channels, a novel estimation technique is proposed based on reconstructing full downlink CSI from a select number of dominant propagation paths. The proposed method offers drastic compressions in user feedback reports and requires much simpler downlink training processes.
Full-duplex technology can provide up to twice the spectral efficiency of conventional resource divisions. This thesis considers a full-duplex two-hop link with a MIMO relay and investigates mitigation techniques against the inherent loop-interference. Spatial-domain suppression schemes are developed for the optimization of full-duplex MIMO relaying in a coverage extension scenario on downlink. The proposed methods are demonstrated to generate data rates that closely approximate their global bounds
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