5,469 research outputs found
The Impact of Sensing Range on Spatial-Temporal Opportunity
In this paper, we study the impact of secondary user (SU) sensing range on spectrum access opportunity in cognitive radio networks. We first derive a closed-form ex- pression of spectrum access opportunity by taking into ac- count the random variations in number, locations and trans- mitted powers of primary users (PUs). Then, we show how SU sensing range affects spectrum access opportunity, and the tradeoff between SU sensing range and spectrum ac- cess opportunity is formulated as an optimization problem to maximize spectrum access opportunity. Furthermore, we prove that there exists an optimal SU sensing range which yields the maximum spectrum access opportunity, and nu- merical results validate our theoretical analysis
Performance Limits of Compressive Sensing Channel Estimation in Dense Cloud RAN
Towards reducing the training signaling overhead in large scale and dense
cloud radio access networks (CRAN), various approaches have been proposed based
on the channel sparsification assumption, namely, only a small subset of the
deployed remote radio heads (RRHs) are of significance to any user in the
system. Motivated by the potential of compressive sensing (CS) techniques in
this setting, this paper provides a rigorous description of the performance
limits of many practical CS algorithms by considering the performance of the,
so called, oracle estimator, which knows a priori which RRHs are of
significance but not their corresponding channel values. By using tools from
stochastic geometry, a closed form analytical expression of the oracle
estimator performance is obtained, averaged over distribution of RRH positions
and channel statistics. Apart from a bound on practical CS algorithms, the
analysis provides important design insights, e.g., on how the training sequence
length affects performance, and identifies the operational conditions where the
channel sparsification assumption is valid. It is shown that the latter is true
only in operational conditions with sufficiently large path loss exponents.Comment: 6 pages, two-column format; ICC 201
Cooperative Multi-Bitrate Video Caching and Transcoding in Multicarrier NOMA-Assisted Heterogeneous Virtualized MEC Networks
Cooperative video caching and transcoding in mobile edge computing (MEC)
networks is a new paradigm for future wireless networks, e.g., 5G and 5G
beyond, to reduce scarce and expensive backhaul resource usage by prefetching
video files within radio access networks (RANs). Integration of this technique
with other advent technologies, such as wireless network virtualization and
multicarrier non-orthogonal multiple access (MC-NOMA), provides more flexible
video delivery opportunities, which leads to enhancements both for the
network's revenue and for the end-users' service experience. In this regard, we
propose a two-phase RAF for a parallel cooperative joint multi-bitrate video
caching and transcoding in heterogeneous virtualized MEC networks. In the cache
placement phase, we propose novel proactive delivery-aware cache placement
strategies (DACPSs) by jointly allocating physical and radio resources based on
network stochastic information to exploit flexible delivery opportunities.
Then, for the delivery phase, we propose a delivery policy based on the user
requests and network channel conditions. The optimization problems
corresponding to both phases aim to maximize the total revenue of network
slices, i.e., virtual networks. Both problems are non-convex and suffer from
high-computational complexities. For each phase, we show how the problem can be
solved efficiently. We also propose a low-complexity RAF in which the
complexity of the delivery algorithm is significantly reduced. A Delivery-aware
cache refreshment strategy (DACRS) in the delivery phase is also proposed to
tackle the dynamically changes of network stochastic information. Extensive
numerical assessments demonstrate a performance improvement of up to 30% for
our proposed DACPSs and DACRS over traditional approaches.Comment: 53 pages, 24 figure
Survey on wireless technology trade-offs for the industrial internet of things
Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment
- …