110 research outputs found
Complexity-Aware Scheduling for an LDPC Encoded C-RAN Uplink
Centralized Radio Access Network (C-RAN) is a new paradigm for wireless
networks that centralizes the signal processing in a computing cloud, allowing
commodity computational resources to be pooled. While C-RAN improves
utilization and efficiency, the computational load occasionally exceeds the
available resources, creating a computational outage. This paper provides a
mathematical characterization of the computational outage probability for
low-density parity check (LDPC) codes, a common class of error-correcting
codes. For tractability, a binary erasures channel is assumed. Using the
concept of density evolution, the computational demand is determined for a
given ensemble of codes as a function of the erasure probability. The analysis
reveals a trade-off: aggressively signaling at a high rate stresses the
computing pool, while conservatively backing-off the rate can avoid
computational outages. Motivated by this trade-off, an effective
computationally aware scheduling algorithm is developed that balances demands
for high throughput and low outage rates.Comment: Conference on Information Sciences and Systems (CISS) 2017, to appea
Complexity aware C-RAN scheduling for LDPC codes over BEC
Effective transmission of data over a noisy wireless channel is a vital part of today\u27s high speed technology driven society. In a wireless cell network, information is sent from mobile users to base stations. The information being transmitted is protected by error-control codes. In a conventional architecture the signal processing, including error-control decoding, is performed locally at each base station. Recently, a new architecture has emerged called Centralized Radio Access Network (C-RAN), which involves the centralized processing of the signals in a computing cloud. Using a computing cloud allows computational resources to be pooled, which improves utilization and efficiency. When the computational resources are finite and when the computational load varies over time, then there is a chance that the load exceeds the available resources. This situation creates a so-called computational outage, which has characteristics that are similar to outages caused by channel fading or interference. In this report, the computational complexity is quantified for a common class of error-correcting codes known as low-density parity check (LDPC) codes. To make the analysis tractable, a binary erasure channel is assumed. The concept of density evolution is used to obtain the complexity as a function of the code design parameters and the signal-to-interference-plus-noise ratio (SINR) of the channel. The analysis shows that there is a trade-off in that aggressively signaling at a high data rate causes high computational demands, while conservatively backing off on the rate can dramatically reduce the computational demand. Motivated by this trade-off, a scheduling algorithm is developed that balances the demands for high throughput and low computational outage rates
Random Linear Network Coding for 5G Mobile Video Delivery
An exponential increase in mobile video delivery will continue with the
demand for higher resolution, multi-view and large-scale multicast video
services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a
number of new opportunities for optimizing video delivery across both 5G core
and radio access networks. One of the promising approaches for video quality
adaptation, throughput enhancement and erasure protection is the use of
packet-level random linear network coding (RLNC). In this review paper, we
discuss the integration of RLNC into the 5G NR standard, building upon the
ideas and opportunities identified in 4G LTE. We explicitly identify and
discuss in detail novel 5G NR features that provide support for RLNC-based
video delivery in 5G, thus pointing out to the promising avenues for future
research.Comment: Invited paper for Special Issue "Network and Rateless Coding for
Video Streaming" - MDPI Informatio
Design, implementation and experimental evaluation of a network-slicing aware mobile protocol stack
MenciĂłn Internacional en el tĂtulo de doctorWith the arrival of new generation mobile networks, we currently observe a paradigm
shift, where monolithic network functions running on dedicated hardware are now
implemented as software pieces that can be virtualized on general purpose hardware
platforms. This paradigm shift stands on the softwarization of network functions and
the adoption of virtualization techniques. Network Function Virtualization (NFV)
comprises softwarization of network elements and virtualization of these components.
It brings multiple advantages: (i) Flexibility, allowing an easy management of the virtual
network functions (VNFs) (deploy, start, stop or update); (ii) efficiency, resources can be
adequately consumed due to the increased flexibility of the network infrastructure; and
(iii) reduced costs, due to the ability of sharing hardware resources. To this end, multiple
challenges must be addressed to effectively leverage of all these benefits.
Network Function Virtualization envisioned the concept of virtual network, resulting in
a key enabler of 5G networks flexibility, Network Slicing. This new paradigm represents
a new way to operate mobile networks where the underlying infrastructure is "sliced"
into logically separated networks that can be customized to the specific needs of the
tenant. This approach also enables the ability of instantiate VNFs at different locations
of the infrastructure, choosing their optimal placement based on parameters such as the
requirements of the service traversing the slice or the available resources. This decision
process is called orchestration and involves all the VNFs withing the same network slice.
The orchestrator is the entity in charge of managing network slices. Hands-on experiments
on network slicing are essential to understand its benefits and limits, and to validate the
design and deployment choices. While some network slicing prototypes have been built
for Radio Access Networks (RANs), leveraging on the wide availability of radio hardware
and open-source software, there is no currently open-source suite for end-to-end network
slicing available to the research community. Similarly, orchestration mechanisms must
be evaluated as well to properly validate theoretical solutions addressing diverse aspects
such as resource assignment or service composition.
This thesis contributes on the study of the mobile networks evolution regarding its
softwarization and cloudification. We identify software patterns for network function
virtualization, including the definition of a novel mobile architecture that squeezes the virtualization architecture by splitting functionality in atomic functions.
Then, we effectively design, implement and evaluate of an open-source network
slicing implementation. Our results show a per-slice customization without paying the
price in terms of performance, also providing a slicing implementation to the research
community. Moreover, we propose a framework to flexibly re-orchestrate a virtualized
network, allowing on-the-fly re-orchestration without disrupting ongoing services. This
framework can greatly improve performance under changing conditions. We evaluate
the resulting performance in a realistic network slicing setup, showing the feasibility and
advantages of flexible re-orchestration.
Lastly and following the required re-design of network functions envisioned during
the study of the evolution of mobile networks, we present a novel pipeline architecture
specifically engineered for 4G/5G Physical Layers virtualized over clouds. The proposed
design follows two objectives, resiliency upon unpredictable computing and parallelization
to increase efficiency in multi-core clouds. To this end, we employ techniques such as tight
deadline control, jitter-absorbing buffers, predictive Hybrid Automatic Repeat Request,
and congestion control. Our experimental results show that our cloud-native approach
attains > 95% of the theoretical spectrum efficiency in hostile environments where stateof-
the-art architectures collapse.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en IngenierĂa Telemática por la Universidad Carlos III de MadridPresidente: Francisco Valera Pintor.- Secretario: Vincenzo Sciancalepore.- Vocal: Xenofon Fouka
Characterizing the Computational and Memory Requirements of Virtual RANs
The virtualization of radio access networks (RANs)
is emerging as a key component of future wireless systems, as
it brings agility to the RAN architecture and offers degrees
of design freedom. In this paper, we investigate and characterize
the computational and memory requirements of virtual
RANs. To this end, we build a virtual RAN test-bed leveraging
the srsRAN open-source mobile communication platform and
general-purpose processor-based servers. Through extensive experiments,
we profile the consumption of computing and memory
resources, and we assess the system performance. Further,
we build regression models to predict the system behavior as
the number of connected users increases, under diverse radio
transmission settings. In so doing, we develop a methodology
and prediction models that can help designing and optimizing
virtual RANs
D11.2 Consolidated results on the performance limits of wireless communications
Deliverable D11.2 del projecte europeu NEWCOM#The report presents the Intermediate Results of N# JRAs on Performance Limits of Wireless Communications and highlights the fundamental issues that have been investigated by the WP1.1. The report illustrates the Joint Research Activities (JRAs) already identified during the first year of the project which are currently ongoing. For each activity there is a description, an illustration of the adherence and relevance with the identified fundamental open issues, a short presentation of the preliminary results, and a roadmap for the joint research work in the next year. Appendices for each JRA give technical details on the scientific activity in each JRA.Peer ReviewedPreprin
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
Random Linear Network Coding for 5G Mobile Video Delivery
An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research
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