39 research outputs found
Fundamental Limits on Latency in Transceiver Cache-Aided HetNets
Stringent mobile usage characteristics force wire- less networks to undergo a
paradigm shift from conventional connection-centric to content-centric
deployment. With respect to 5G, caching and heterogeneous networks (HetNet) are
key technologies that will facilitate the evolution of highly content- centric
networks by facilitating unified quality of service in terms of low-latency
communication. In this paper, we study the impact of transceiver caching on the
latency for a HetNet consisting of a single user, a receiver and one
cache-assisted transceiver. We define an information-theoretic metric, the
delivery time per bit (DTB), that captures the delivery latency. We establish
coinciding lower and upper bounds on the DTB as a function of cache size and
wireless channel parameters; thus, enabling a complete characterization of the
DTB optimality of the network under study. As a result, we identify cache
beneficial and non-beneficial channel regimes.Comment: 5 pages, ISIT 201
Delivery Time Minimization in Edge Caching: Synergistic Benefits of Subspace Alignment and Zero Forcing
An emerging trend of next generation communication systems is to provide
network edges with additional capabilities such as additional storage resources
in the form of caches to reduce file delivery latency. To investigate this
aspect, we study the fundamental limits of a cache-aided wireless network
consisting of one central base station, transceivers and receivers from
a latency-centric perspective. We use the normalized delivery time (NDT) to
capture the per-bit latency for the worst-case file request pattern at high
signal-to-noise ratios (SNR), normalized with respect to a reference
interference-free system with unlimited transceiver cache capabilities. For
various special cases with and that satisfy , we establish the optimal tradeoff between cache storage and latency. This
is facilitated through establishing a novel converse (for arbitrary and
) and an achievability scheme on the NDT. Our achievability scheme is a
synergistic combination of multicasting, zero-forcing beamforming and
interference alignment.Comment: submitted to ICC 2018; fixed some typo
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
A review on green caching strategies for next generation communication networks
© 2020 IEEE. In recent years, the ever-increasing demand for networking resources and energy, fueled by the unprecedented upsurge in Internet traffic, has been a cause for concern for many service providers. Content caching, which serves user requests locally, is deemed to be an enabling technology in addressing the challenges offered by the phenomenal growth in Internet traffic. Conventionally, content caching is considered as a viable solution to alleviate the backhaul pressure. However, recently, many studies have reported energy cost reductions contributed by content caching in cache-equipped networks. The hypothesis is that caching shortens content delivery distance and eventually achieves significant reduction in transmission energy consumption. This has motivated us to conduct this study and in this article, a comprehensive survey of the state-of-the-art green caching techniques is provided. This review paper extensively discusses contributions of the existing studies on green caching. In addition, the study explores different cache-equipped network types, solution methods, and application scenarios. We categorically present that the optimal selection of the caching nodes, smart resource management, popular content selection, and renewable energy integration can substantially improve energy efficiency of the cache-equipped systems. In addition, based on the comprehensive analysis, we also highlight some potential research ideas relevant to green content caching
An overview of VANET vehicular networks
Today, with the development of intercity and metropolitan roadways and with
various cars moving in various directions, there is a greater need than ever
for a network to coordinate commutes. Nowadays, people spend a lot of time in
their vehicles. Smart automobiles have developed to make that time safer, more
effective, more fun, pollution-free, and affordable. However, maintaining the
optimum use of resources and addressing rising needs continues to be a
challenge given the popularity of vehicle users and the growing diversity of
requests for various services. As a result, VANET will require modernized
working practices in the future. Modern intelligent transportation management
and driver assistance systems are created using cutting-edge communication
technology. Vehicular Ad-hoc networks promise to increase transportation
effectiveness, accident prevention, and pedestrian comfort by allowing
automobiles and road infrastructure to communicate entertainment and traffic
information. By constructing thorough frameworks, workflow patterns, and update
procedures, including block-chain, artificial intelligence, and SDN (Software
Defined Networking), this paper addresses VANET-related technologies, future
advances, and related challenges. An overview of the VANET upgrade solution is
given in this document in order to handle potential future problems
5G Backhaul Challenges and Emerging Research Directions: A Survey
5G is the next cellular generation and is expected to quench the growing thirst for taxing data rates and to enable the Internet of Things. Focused research and standardization work have been addressing the corresponding challenges from the radio perspective while employing advanced features, such as network densi cation, massive multiple-input-multiple-output antennae, coordinated multi-point processing, intercell interference mitigation techniques, carrier aggregation, and new spectrum exploration. Nevertheless, a new bottleneck has emerged: the backhaul. The ultra-dense and heavy traf c cells should be connected to the core network through the backhaul, often with extreme requirements in terms of capacity, latency, availability, energy, and cost ef ciency. This pioneering survey explains the 5G backhaul paradigm, presents a critical analysis of legacy, cutting-edge solutions, and new trends in backhauling, and proposes a novel consolidated 5G backhaul framework. A new joint radio access and backhaul perspective is proposed for the evaluation of backhaul technologies which reinforces the belief that no single solution can solve the holistic 5G backhaul problem. This paper also reveals hidden advantages and shortcomings of backhaul solutions, which are not evident when backhaul technologies are inspected as an independent part of the 5G network. This survey is key in identifying essential catalysts that are believed to jointly pave the way to solving the beyond-2020 backhauling challenge. Lessons learned, unsolved challenges, and a new consolidated 5G backhaul vision are thus presented