23,585 research outputs found
Green Networking in Cellular HetNets: A Unified Radio Resource Management Framework with Base Station ON/OFF Switching
In this paper, the problem of energy efficiency in cellular heterogeneous
networks (HetNets) is investigated using radio resource and power management
combined with the base station (BS) ON/OFF switching. The objective is to
minimize the total power consumption of the network while satisfying the
quality of service (QoS) requirements of each connected user. We consider the
case of co-existing macrocell BS, small cell BSs, and private femtocell access
points (FAPs). Three different network scenarios are investigated, depending on
the status of the FAPs, i.e., HetNets without FAPs, HetNets with closed FAPs,
and HetNets with semi-closed FAPs. A unified framework is proposed to
simultaneously allocate spectrum resources to users in an energy efficient
manner and switch off redundant small cell BSs. The high complexity dual
decomposition technique is employed to achieve optimal solutions for the
problem. A low complexity iterative algorithm is also proposed and its
performances are compared to those of the optimal technique. The particularly
interesting case of semi-closed FAPs, in which the FAPs accept to serve
external users, achieves the highest energy efficiency due to increased degrees
of freedom. In this paper, a cooperation scheme between FAPs and mobile
operator is also investigated. The incentives for FAPs, e.g., renewable energy
sharing and roaming prices, enabling cooperation are discussed to be considered
as a useful guideline for inter-operator agreements.Comment: 15 pages, 9 Figures, IEEE Transactions on Vehicular Technology 201
A survey of machine learning techniques applied to self organizing cellular networks
In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future
Measurement-Adaptive Cellular Random Access Protocols
This work considers a single-cell random access channel (RACH) in cellular
wireless networks. Communications over RACH take place when users try to
connect to a base station during a handover or when establishing a new
connection. Within the framework of Self-Organizing Networks (SONs), the system
should self- adapt to dynamically changing environments (channel fading,
mobility, etc.) without human intervention. For the performance improvement of
the RACH procedure, we aim here at maximizing throughput or alternatively
minimizing the user dropping rate. In the context of SON, we propose protocols
which exploit information from measurements and user reports in order to
estimate current values of the system unknowns and broadcast global
action-related values to all users. The protocols suggest an optimal pair of
user actions (transmission power and back-off probability) found by minimizing
the drift of a certain function. Numerical results illustrate considerable
benefits of the dropping rate, at a very low or even zero cost in power
expenditure and delay, as well as the fast adaptability of the protocols to
environment changes. Although the proposed protocol is designed to minimize
primarily the amount of discarded users per cell, our framework allows for
other variations (power or delay minimization) as well.Comment: 31 pages, 13 figures, 3 tables. Springer Wireless Networks 201
Benchmarking Practical RRM Algorithms for D2D Communications in LTE Advanced
Device-to-device (D2D) communication integrated into cellular networks is a
means to take advantage of the proximity of devices and allow for reusing
cellular resources and thereby to increase the user bitrates and the system
capacity. However, when D2D (in the 3rd Generation Partnership Project also
called Long Term Evolution (LTE) Direct) communication in cellular spectrum is
supported, there is a need to revisit and modify the existing radio resource
management (RRM) and power control (PC) techniques to realize the potential of
the proximity and reuse gains and to limit the interference at the cellular
layer. In this paper, we examine the performance of the flexible LTE PC tool
box and benchmark it against a utility optimal iterative scheme. We find that
the open loop PC scheme of LTE performs well for cellular users both in terms
of the used transmit power levels and the achieved
signal-to-interference-and-noise-ratio (SINR) distribution. However, the
performance of the D2D users as well as the overall system throughput can be
boosted by the utility optimal scheme, because the utility maximizing scheme
takes better advantage of both the proximity and the reuse gains. Therefore, in
this paper we propose a hybrid PC scheme, in which cellular users employ the
open loop path compensation method of LTE, while D2D users use the utility
optimizing distributed PC scheme. In order to protect the cellular layer, the
hybrid scheme allows for limiting the interference caused by the D2D layer at
the cost of having a small impact on the performance of the D2D layer. To
ensure feasibility, we limit the number of iterations to a practically feasible
level. We make the point that the hybrid scheme is not only near optimal, but
it also allows for a distributed implementation for the D2D users, while
preserving the LTE PC scheme for the cellular users.Comment: 30 pages, submitted for review April-2013. See also: G. Fodor, M.
Johansson, D. P. Demia, B. Marco, and A. Abrardo, A joint power control and
resource allocation algorithm for D2D communications, KTH, Automatic Control,
Tech. Rep., 2012, qC 20120910,
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-10205
A Fully-Integrated Quad-Band GSM/GPRS CMOS Power Amplifier
Concentric distributed active transformers (DAT) are used to implement a fully-integrated quad-band power amplifier (PA) in a standard 130 nm CMOS process. The DAT enables the power amplifier to integrate the input and output matching networks on the same silicon die. The PA integrates on-chip closed-loop power control and operates under supply voltages from 2.9 V to 5.5 V in a standard micro-lead-frame package. It shows no oscillations, degradation, or failures for over 2000 hours of operation with a supply of 6 V at 135° under a VSWR of 15:1 at all phase angles and has also been tested for more than 2 million device-hours (with ongoing reliability monitoring) without a single failure under nominal operation conditions. It produces up to +35 dBm of RF power with power-added efficiency of 51%
- …