266 research outputs found
Reliable and Low-Latency Fronthaul for Tactile Internet Applications
With the emergence of Cloud-RAN as one of the dominant architectural
solutions for next-generation mobile networks, the reliability and latency on
the fronthaul (FH) segment become critical performance metrics for applications
such as the Tactile Internet. Ensuring FH performance is further complicated by
the switch from point-to-point dedicated FH links to packet-based multi-hop FH
networks. This change is largely justified by the fact that packet-based
fronthauling allows the deployment of FH networks on the existing Ethernet
infrastructure. This paper proposes to improve reliability and latency of
packet-based fronthauling by means of multi-path diversity and erasure coding
of the MAC frames transported by the FH network. Under a probabilistic model
that assumes a single service, the average latency required to obtain reliable
FH transport and the reliability-latency trade-off are first investigated. The
analytical results are then validated and complemented by a numerical study
that accounts for the coexistence of enhanced Mobile BroadBand (eMBB) and
Ultra-Reliable Low-Latency (URLLC) services in 5G networks by comparing
orthogonal and non-orthogonal sharing of FH resources.Comment: 11pages, 13 figures, 3 bio photo
A Comprehensive Survey of the Tactile Internet: State of the art and Research Directions
The Internet has made several giant leaps over the years, from a fixed to a
mobile Internet, then to the Internet of Things, and now to a Tactile Internet.
The Tactile Internet goes far beyond data, audio and video delivery over fixed
and mobile networks, and even beyond allowing communication and collaboration
among things. It is expected to enable haptic communication and allow skill set
delivery over networks. Some examples of potential applications are
tele-surgery, vehicle fleets, augmented reality and industrial process
automation. Several papers already cover many of the Tactile Internet-related
concepts and technologies, such as haptic codecs, applications, and supporting
technologies. However, none of them offers a comprehensive survey of the
Tactile Internet, including its architectures and algorithms. Furthermore, none
of them provides a systematic and critical review of the existing solutions. To
address these lacunae, we provide a comprehensive survey of the architectures
and algorithms proposed to date for the Tactile Internet. In addition, we
critically review them using a well-defined set of requirements and discuss
some of the lessons learned as well as the most promising research directions
Spectrum Sharing, Latency, and Security in 5G Networks with Application to IoT and Smart Grid
The surge of mobile devices, such as smartphones, and tables, demands additional capacity. On the other hand, Internet-of-Things (IoT) and smart grid, which connects numerous sensors, devices, and machines require ubiquitous connectivity and data security. Additionally, some use cases, such as automated manufacturing process, automated transportation, and smart grid, require latency as low as 1 ms, and reliability as high as 99.99\%. To enhance throughput and support massive connectivity, sharing of the unlicensed spectrum (3.5 GHz, 5GHz, and mmWave) is a potential solution. On the other hand, to address the latency, drastic changes in the network architecture is required. The fifth generation (5G) cellular networks will embrace the spectrum sharing and network architecture modifications to address the throughput enhancement, massive connectivity, and low latency.
To utilize the unlicensed spectrum, we propose a fixed duty cycle based coexistence of LTE and WiFi, in which the duty cycle of LTE transmission can be adjusted based on the amount of data. In the second approach, a multi-arm bandit learning based coexistence of LTE and WiFi has been developed. The duty cycle of transmission and downlink power are adapted through the exploration and exploitation. This approach improves the aggregated capacity by 33\%, along with cell edge and energy efficiency enhancement. We also investigate the performance of LTE and ZigBee coexistence using smart grid as a scenario.
In case of low latency, we summarize the existing works into three domains in the context of 5G networks: core, radio and caching networks. Along with this, fundamental constraints for achieving low latency are identified followed by a general overview of exemplary 5G networks. Besides that, a loop-free, low latency and local-decision based routing protocol is derived in the context of smart grid. This approach ensures low latency and reliable data communication for stationary devices.
To address data security in wireless communication, we introduce a geo-location based data encryption, along with node authentication by k-nearest neighbor algorithm. In the second approach, node authentication by the support vector machine, along with public-private key management, is proposed. Both approaches ensure data security without increasing the packet overhead compared to the existing approaches
Joint Design of Wireless Fronthaul and Access Links in Massive MIMO CRANs
Cloud radio access network (CRAN) has emerged as a promising mobile network architecture for the current 5th generation (5G) and beyond networks. This thesis focuses on novel architectures and optimization approaches for CRAN systems with massive multiple-input multiple-output (MIMO) enabled in the wireless fronthaul link. In particular, we propose a joint design of wireless fronthaul and access links for CRANs and aim to maximize the network spectral efficiency (SE) and energy efficiency (EE).
Regarding downlink transmission in massive MIMO CRANs, the precoding designs of the access link are optimized by accounting for both perfect instantaneous channel state information (CSI) and stochastic CSI of the access link separately. The system design adopts a decompress-and-forward (DCF) scheme at the remote radio heads (RRHs), with optimization of the multivariate compression covariance noise. Constrained by the maximum power budgets set for the central unit (CU) and RRHs, we aim to maximize the network sum-rate and minimize the total transmit power for all user equipments (UEs). Moreover, we present a separate optimization design and compare its performance, feasibility, and computational efficiency with the proposed joint design. Considering the uplink transmission, we utilize a compress-and-forward (CF) scheme at the RRHs. Assuming that perfect CSI is available at the CU, our objective is to optimize the precoding matrix of the access link while adopting conventional precoding methods for the fronthaul link. This thesis also proposes an unmanned aerial vehicle (UAV)-enabled CRAN architecture with a massive MIMO CU as a supplement system to the terrestrial communication networks. The locations of UAVs are optimized along with compression noise, precoding matrices, and transmit power. To tackle the non-convex optimization problems described above, we employ efficient iterative algorithms and conduct a thorough exploration of practical simulations, yielding promising results that outperform benchmark schemes.
In summary, this thesis explores future wireless CRAN architectures, leveraging promising technologies including massive MIMO and UAV-enabled communications. Furthermore, this work presents comprehensive optimization designs aimed at further enhancing the network efficiency
Otimização do fronthaul ótico para redes de acesso de rádio (baseadas) em computação em nuvem (CC-RANs)
Doutoramento conjunto (MAP-Tele) em Engenharia Eletrotécnica/TelecomunicaçõesA proliferação de diversos tipos de dispositivos moveis, aplicações e serviços
com grande necessidade de largura de banda têm contribuído para o aumento
de ligações de banda larga e ao aumento do volume de trafego das
redes de telecomunicações moveis. Este aumento exponencial tem posto
uma enorme pressão nos mobile operadores de redes móveis (MNOs). Um
dos aspetos principais deste recente desenvolvimento, é a necessidade que as
redes têm de oferecer baixa complexidade nas ligações, como também baixo
consumo energético, muito baixa latência e ao mesmo tempo uma grande
capacidade por baixo usto. De maneira a resolver estas questões, os MNOs
têm focado a sua atenção na redes de acesso por rádio em nuvem (C-RAN)
principalmente devido aos seus benefícios em termos de otimização de performance
e relação qualidade preço. O standard para a distribuição de sinais
sem fios por um fronthaul C-RAN é o common public radio interface (CPRI).
No entanto, ligações óticas baseadas em interfaces CPRI necessitam de uma
grande largura de banda. Estes requerimentos podem também ser atingidos
com uma implementação em ligação free space optical (FSO) que é um sistema
ótico que usa comunicação sem fios. O FSO tem sido uma alternativa
muito apelativa aos sistemas de comunicação rádio (RF) pois combinam a
flexibilidade e mobilidade das redes RF ao mesmo tempo que permitem a
elevada largura de banda permitida pelo sistema ótico. No entanto, as ligações
FSO são suscetíveis a alterações atmosféricas que podem prejudicar
o desempenho do sistema de comunicação. Estas limitações têm evitado o
FSO de ser tornar uma excelente solução para o fronthaul. Uma caracterização
precisa do canal e tecnologias mais avançadas são então necessárias
para uma implementação pratica de ligações FSO. Nesta tese, vamos estudar
uma implementação eficiente para fronthaul baseada em tecnologia
á rádio-sobre-FSO (RoFSO). Propomos expressões em forma fechada para
mitigação das perdas de propagação e para a estimação da capacidade do
canal de maneira a aliviar a complexidade do sistema de comunicação. Simulações
numéricas são também apresentadas para formatos de modulação
adaptativas. São também considerados esquemas como um sistema hibrido
RF/FSO e tecnologias de transmissão apoiadas por retransmissores
que ajudam a alivar os requerimentos impostos por um backhaul/fronthaul
de C-RAN. Os modelos propostos não só reduzem o esforço computacional,
como também têm outros méritos, tais como, uma elevada precisão na estimação
do canal e desempenho, baixo requisitos na capacidade de memória
e uma rápida e estável operação comparativamente com o estado da arte
em sistemas analíticos (PON)-FSO. Este sistema é implementado num recetor
em tempo real que é emulado através de uma field-programmable gate
array (FPGA) comercial. Permitindo assim um sistema aberto, interoperabilidade,
portabilidade e também obedecer a standards de software aberto.
Os esquemas híbridos têm a habilidade de suportar diferentes aplicações,
serviços e múltiplos operadores a partilharem a mesma infraestrutura de
fibra ótica.The proliferation of different mobile devices, bandwidth-intensive applications
and services contribute to the increase in the broadband connections
and the volume of traffic on the mobile networks. This exponential growth
has put considerable pressure on the mobile network operators (MNOs). In
principal, there is a need for networks that not only offer low-complexity,
low-energy consumption, and extremely low-latency but also high-capacity
at relatively low cost. In order to address the demand, MNOs have given significant
attention to the cloud radio access network (C-RAN) due to its beneficial
features in terms of performance optimization and cost-effectiveness.
The de facto standard for distributing wireless signal over the C-RAN fronthaul
is the common public radio interface (CPRI). However, optical links
based on CPRI interfaces requires large bandwidth. Also, the aforementioned
requirements can be realized with the implementation of free space
optical (FSO) link, which is an optical wireless system. The FSO is an appealing
alternative to the radio frequency (RF) communication system that
combines the flexibility and mobility offered by the RF networks with the
high-data rates provided by the optical systems. However, the FSO links are
susceptible to atmospheric impairments which eventually hinder the system
performance. Consequently, these limitations prevent FSO from being an
efficient standalone fronthaul solution. So, precise channel characterizations
and advanced technologies are required for practical FSO link deployment
and operation. In this thesis, we study an efficient fronthaul implementation
that is based on radio-on-FSO (RoFSO) technologies. We propose closedform
expressions for fading-mitigation and for the estimation of channel
capacity so as to alleviate the system complexity. Numerical simulations
are presented for adaptive modulation scheme using advanced modulation
formats. We also consider schemes like hybrid RF/FSO and relay-assisted
transmission technologies that can help in alleviating the stringent requirements
by the C-RAN backhaul/fronthaul. The propose models not only
reduce the computational requirements/efforts, but also have a number of
diverse merits such as high-accuracy, low-memory requirements, fast and
stable operation compared to the current state-of-the-art analytical based
approaches. In addition to the FSO channel characterization, we present
a proof-of-concept experiment in which we study the transmission capabilities
of a hybrid passive optical network (PON)-FSO system. This is
implemented with the real-time receiver that is emulated by a commercial
field-programmable gate array (FPGA). This helps in facilitating an
open system and hence enables interoperability, portability, and open software
standards. The hybrid schemes have the ability to support different
applications, services, and multiple operators over a shared optical fiber
infrastructure
Performance Analysis of Non-Orthogonal Multiple Access (NOMA) in C-RAN, H-CRAN and F-RAN for 5G Systems
The world of telecommunication is witnessing a swift transformation towards fifth generation (5G) cellular networks. The future networks present requisite needs in ubiquitous throughput, low latency, and high reliability. They are also envisioned to provide diversified services such as enhanced Mobile BroadBand (eMBB) and ultra-reliable low-latency communication (URLLC) as well as improved quality of
user experience. More interestingly, a novel mobile network architecture allowing centralized processing and cloud computing has been proposed as one of the best candidates for fifth generation. It is denoted as Cloud Radio Access Network (CRAN) and Heterogeneous Cloud Radio Access Network (H-CRAN). Furthermore, the 5G architecture will be fog-like, namely fog radio access networks (F-RAN) enabling a functional split of network functionalities between cloud and edge nodes
with caching and fog computing capabilities.
Meanwhile non-orthogonal multiple access (NOMA) has been proposed as an promising multiple access (MA) technology for future radio access networks (RANs) to meet the heterogeneous demands for high throughput, low latency and massive connectivity. One of the main challenges of NOMA is that how well it is to be compatible with other emerging techniques for meeting the requirements of 5G. However, comprehensive performance analysis on NOMA and practical resource allocation designs in co-existence with other emerging networks have not been fully studied and investigated in the literature. This thesis focuses on potential performance enhancement brought by NOMA for the C-RAN, H-CRAN and F-RAN and is expected to
address some of the aforementioned key challenges of 5G. The research work of this thesis can be divided into three parts.
In the first part of our research, we focus on investigating the performance analysis of NOMA in a C-RAN. The problem of jointly optimizing user association, muting and power-bandwidth allocation is formulated for NOMA-enabled C-RANs. To
solve the mixed integer programming problem, the joint problem is decomposed into two subproblems as 1) user association and muting 2) power-bandwidth allocation optimization. To deal with the first subproblem, we propose a centralized and heuristic algorithm to provide the optimal and suboptimal solutions to the remote radio head (RRH) muting problem for given bandwidth and transmit power, respectively.
The second subproblem is then reformulated and we propose an optimal solution to bandwidth and power allocation subject to users data rate constraints. Moreover, for given user association and muting states, the optimal power allocation is derived in a closed-form. Simulation results show that the proposed NOMA-enabled C-RAN outperforms orthogonal multiple access (OMA)-based C-RANs in terms of total achievable rate, interference mitigation and can achieve significant fairness improvement.
Our second work investigates the performance of NOMA in H-CRAN, where coordination of macro base station (MBS) and remote radio heads (RRHs) for H-CRAN with NOMA is introduced to improve network performance. We formulate the problem of jointly optimizing user association, coordinated scheduling and power allocation for NOMA-enabled H-CRANs. To efficiently solve this problem, we decompose the joint optimization problem into two subproblems as 1) user association and scheduling 2) power allocation optimization. Firstly the users are divided based on
different interference they suffer. This interference-aware NOMA approach account for the inter-tier interference. Proportional fairness (PF) scheduling for NOMA is utilized to schedule users with a two-loop optimization method to enhance throughput and fairness. Based on the user scheduling scheme, optimal power allocation optimization is performed by the hierarchical decomposition approach. It is then followed by algorithm for joint scheduling and power allocation. Simulation results show that the proposed NOMA-enabled H-CRAN outperforms OMA-based H-CRANs in terms of total achievable rate and can achieve significant fairness improvement.
In the third part of our research, we propose a NOMA-enabled fog-cloud structure in a novel density-aware F-RAN to tackle different aspects such as throughput and latency requirements of high and low user-density regions, in order to meet the heterogeneous requirements of eMBB and URLLC traffic. A framework of the multi-objective problem is formulated to cater the high throughput and low-latency requirements in a high and low user-density mode respectively. In the first problem, we study the joint caching placement and association strategy aiming at minimizing the average delay. To deal with the first problem, we apply McCormick envelopes and Lagrange partial relaxation method to transform it into three convex sub-problems, which is then solved by proposed distributed algorithm. The second problem is to jointly optimize transmission mode selection, subchannel assignment and power allocation to maximize the sum data rate of all fog user equipments
(F-UEs) while satisfying fronthaul capacity and fog-computing access point (F-AP) power constraints. Moreover, for given transmission mode selection and subchannel assignment, the optimal power allocation is derived in a closed-form. Simulation
results are provided for the proposed NOMA-enabled F-RAN framework and reveal that the ultra-low latency and high throughput can be achieved by properly utilizing the available resources
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