Networking Plan Issues

 
Networking Plan Issues
DNP is considered as a subset of a more general framework: Dynamic Network Planning and Management
(DNPM) – a framework dealing with planning and managing a reconfigurable network [541]. Reconfigurability and spectrum issues are changing the way wireless networks are planned. Planners
are mindful of QoS constraints and the need to reduce infrastructure costs in the B3G era.
Traditionally, mobile operators have designed and deployed the radio access networks to cover
the traffic demand of the planned services in a static approach, considering the busy hour traffic in
a given geographical zone. This means that the operator installs as many base stations as needed to
attend to the traffic foreseen in each zone. In doing so, the conventional network planning methods
consist of some predefined phases, namely, the initial dimensioning and the detailed planning with
the help of an appropriate planning tool, and such methods can be applied only prior to the network
deployment.
The current planning process follows several steps to obtain the site locations and configurations
that satisfy the network planning requirements of coverage, capacity, and QoS in a geographical area.
An initial number of sites and configurations can be obtained as a preliminary dimensioning exercise,
based on the network data obtained by the operator in this first phase. According to the estimated
number of sites in the dimensioning phase, sites are selected in the desired geographical area in the
second phase. This selection could become a complicated task. Although some algorithms can be
used in the planning process to assist the planners in the selection of sites, and this task can be
carried out by automatic tools, the restrictions to the problem sometimes make the effort of using
these algorithms not worthwhile. These restrictions in the selection of sites are due to the difficulty of
the operators in choosing the desirable positions for the sites. Increasingly, people and governments
are more concerned about mobile telephony and antennas on the roofs of the city, and it is very
complicated for the operators to acquire new sites. NPs must often restrict themselves to the set
of sites they have from earlier network deployments. Once the sites are selected and placed on the
scenario, the radio network deployment should be analyzed to check that the initial requirements of
coverage, capacity, and quality of service are satisfied. This evaluation can be performed by means
of a radio network planning tool.
However, reconfigurable networks are continuously transforming, according to time- and spacevariant
demand. More specifically, the distribution pattern of subscribers, user-related information
(profiles), and available terminal types are different from those of conventional networks. This means
that the reconfiguration mechanisms for the base stations of a particular RAT can control the changeable
parameters and operational modes, targeting optimal network configurations. Moreover, software
download support must be integrated into network infrastructure. A flexible management covers electric
tilting of antenna angles, frequency settings, the maximum size of the active/candidate cell for
Mobile Terminals (MT), power allocation for high-speed data services, which has adaptive modulation
and code schemes implemented, and complete reconfiguration between RATs for a common
platform. According to the temporal-spatial changing traffic, some of these parameters are subject
to change. Therefore, the busy-hour traffic for some particular hotspots in the conventional network
planning paradigm is not the only criteria for planning anymore. Moreover, there will be no
exact separation between planning and management, but DNPM has to be applied to reconfigurable
contexts.
Consequently, while considering the gains and characteristics exclusively offered by the flexibility
of the reconfigurable system, the suitable planning methods and the affecting factors need
to be studied; innovative engineering mechanisms need to be defined, in order to guarantee for
the best possible planning design, not only before network deployment but also during network
operation.
In the reconfigurability context, DNPM is a complete framework that cooperates with other mechanisms
such as the Joint Radio Resource management (JRRM) and Dynamic Spectrum Management
(DSM), for efficient network deployment. During network planning, modeling of network performance,
taking into consideration a given traffic distribution and network deployment cost, is needed.
The measurements of network performance should not only be based on the carrier strength that
a MT can receive but also on the performance improvement given by other resource management
mechanisms. In the optimization phase, algorithms like “Greedy,” “Taboo Search,” and “Simulated Annealing” are considered in an approach involving combinations of snapshot simulations. In the
management phase of DNPM, radio network elements and some key resource management related
parameters are subject to reconfiguration. Reconfiguration is triggered by the management entities
like the network element manager so that self-tuning of a radio network targeting optimal parameter
settings can be carried out. Typical examples are the vertical antenna tilting, power adjustment, spectrum
management, and multistandard base station reconfiguration. For an on-the-fly reconfiguration,
a faster heuristic search, rather than the classic algorithms, needs to be used.
Early research in the field of reconfigurable networks shows significant dependencies between
network planning and network management resulting from the time- and space-variant conditions
that render initial planning insufficient. The assumption is that the transceivers within the service area
are reconfigurable. The situation that arises owing to the changes requires reallocation of RATs to
the transceivers of the “target” region. The problem tackled is called the RDQ-A problem because
its solution aims at new assignments of RATs to transceivers, demand to transceiver/RATs, and
applications to QoS levels.
The RDQ-A problem can be generally described from a certain input and a certain objective
(output). The input to this problem provides information on the service area and demand, as well as
on the system. The service area is divided into a set of area portions, called pixels. What is of interest
are the applications (services) offered in the service area, the quality levels (QoS levels) through which
each service can be offered, the RATs through which each service can be offered and the expected
demand per service and pixel. Moreover, the additional requirements are the utility volume and the
resource consumption, when a service is offered at a certain quality level, through a certain RAT.
The aspects of the system that need to be taken into account are the set of sites that cover the service
area region that needs reconfiguration, and their locations (pixels), the set of transceivers per site, the
set of RATs that can be used per transceiver, and the coverage and the anticipated capacity, when a
certain RAT is used by a certain transceiver, taking into account intra- and inter-RAT interference.
The objective (output) of the RDQ-A problem is to determine new configurations, for example, new
allocations of RATs to transceivers, demand to transceiver/RATs, and applications to QoS levels.
The three allocations should optimize a utility-based objective function, which is associated with the
resulting QoS levels. Moreover, the allocations should respect constraints. The demand in the service
area should be satisfied. Applications should be assigned to acceptable QoS levels. Permissible RATs
should be assigned to transceivers. The allocations of RATs to transceivers should provide adequate
capacity and coverage levels.
Initially, the overall RDQ-A problem is split into a number of subproblems, depending on the
corresponding number of available transceivers and RATs, that have to be solved in parallel. In
each of the resultant subproblems, the transceivers are assigned with a specific RAT. The second
phase includes the solution of these subproblems, which can be done in parallel. Each subproblem
aims at allocating the demand to the available transceivers. For this procedure, it is assumed
that the lowest QoS levels are assigned to the offered services. In the third phase, called improvement
phase, the QoS levels to be assigned are gradually augmented in a greedy fashion. Finally,
the fourth phase summarizes the three past phases and selects the best combination of allocations
that maximizes an objective function associated with the utility, by means of the resulting
QoS levels. In the sequel, there are some indicative results from the application of the aforementioned
algorithm to a simulated network that deploys reconfigurable transceivers working at multiple
RATs [547].
The network planning problem can be solved with the utilization of the appropriate optimization
functionality. This refers mainly to the respective midterm algorithms, necessary for dynamic
network planning issues. Simulations for dynamic networks taking into account multistandard radio
network elements must be performed and the requisite recommendations for network planning must be
deduced. Automatic network planning is another use-case for reconfigurable, multistandard network
elements, for example, the autonomous selection of carrier frequencies [548].