18,000 research outputs found
Optimal channel allocation with dynamic power control in cellular networks
Techniques for channel allocation in cellular networks have been an area of
intense research interest for many years. An efficient channel allocation
scheme can significantly reduce call-blocking and calldropping probabilities.
Another important issue is to effectively manage the power requirements for
communication. An efficient power control strategy leads to reduced power
consumption and improved signal quality. In this paper, we present a novel
integer linear program (ILP) formulation that jointly optimizes channel
allocation and power control for incoming calls, based on the
carrier-to-interference ratio (CIR). In our approach we use a hybrid channel
assignment scheme, where an incoming call is admitted only if a suitable
channel is found such that the CIR of all ongoing calls on that channel, as
well as that of the new call, will be above a specified value. Our formulation
also guarantees that the overall power requirement for the selected channel
will be minimized as much as possible and that no ongoing calls will be dropped
as a result of admitting the new call. We have run simulations on a benchmark
49 cell environment with 70 channels to investigate the effect of different
parameters such as the desired CIR. The results indicate that our approach
leads to significant improvements over existing techniques.Comment: 11 page
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Applications of Soft Computing in Mobile and Wireless Communications
Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications
Bio-Inspired Resource Allocation for Relay-Aided Device-to-Device Communications
The Device-to-Device (D2D) communication principle is a key enabler of direct
localized communication between mobile nodes and is expected to propel a
plethora of novel multimedia services. However, even though it offers a wide
set of capabilities mainly due to the proximity and resource reuse gains,
interference must be carefully controlled to maximize the achievable rate for
coexisting cellular and D2D users. The scope of this work is to provide an
interference-aware real-time resource allocation (RA) framework for relay-aided
D2D communications that underlay cellular networks. The main objective is to
maximize the overall network throughput by guaranteeing a minimum rate
threshold for cellular and D2D links. To this direction, genetic algorithms
(GAs) are proven to be powerful and versatile methodologies that account for
not only enhanced performance but also reduced computational complexity in
emerging wireless networks. Numerical investigations highlight the performance
gains compared to baseline RA methods and especially in highly dense scenarios
which will be the case in future 5G networks.Comment: 6 pages, 6 figure
Hybrid Spectrum Sharing in mmWave Cellular Networks
While spectrum at millimeter wave (mmWave) frequencies is less scarce than at
traditional frequencies below 6 GHz, still it is not unlimited, in particular
if we consider the requirements from other services using the same band and the
need to license mmWave bands to multiple mobile operators. Therefore, an
efficient spectrum access scheme is critical to harvest the maximum benefit
from emerging mmWave technologies. In this paper, we introduce a new hybrid
spectrum access scheme for mmWave networks, where data is aggregated through
two mmWave carriers with different characteristics. In particular, we consider
the case of a hybrid spectrum scheme between a mmWave band with exclusive
access and a mmWave band where spectrum is pooled between multiple operators.
To the best of our knowledge, this is the first study proposing hybrid spectrum
access for mmWave networks and providing a quantitative assessment of its
benefits. Our results show that this approach provides major advantages with
respect to traditional fully licensed or fully unlicensed spectrum access
schemes, though further work is needed to achieve a more complete understanding
of both technical and non technical implications
- …