introduction to channel borrowing scheme in cellular networks

1. Introduction to channel borrowing
scheme cellular networks
By
Tanmoy Barman
HALDIA INSTITUTE OF TECHNOLOGY
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2. Introduction
Advances in cellular mobile technology have engendered a new
paradigm of computing, called mobile computing. The frequency
spectrum allocated to this service is not sufficient with respect to
enormous growth of mobile communication users. Tracking down a
mobile user in a cellular network which is a collection of geometric areas
called cells each serviced by a base station is the other concern to the
designer. This service also needs another problem to be solved, that is
the access of common information by mobile users. Other than the
issues in existing technology, many other issues on developing
technology need to be addressed. One main issue in cellular system
design reduces to one of economics. Essentially we have a limited
resource transmission spectrum that must be shared by several users.
Unlike wired communications which benefits from isolation provided by
cables, wireless users within close proximity of one another can cause
significant interference to one another. To address this issue, the
concept of cellular communications was introduced around in 1968 by
researchers at AT&T Bell Labs.
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3. Channel Allocation
There are several challenges in mobile cellular environment which is
generally conceived as a collection of geometric areas called cells, each
serviced by a base station (BS) located at its centre. A number of cells
are again linked to a mobile switching centre (MSC) which also acts as a
gateway of the cellular network to the existing wired network (shown in
Figure 1). The problems in this area are clearly divided in two parts.
Some of them are based on electronics and telecommunication and
some of them are information based.
The basic concept being that a given geography is divided into polygons
(hexagon) called cells. Each cell is allocated a portion of the total
frequency spectrum. As users move into a given cell, they are then
permitted to utilize the channel allocated to that cell. The virtue of the
cellular system is that different cells can use the same channel given
that the cells are separated by a minimum distance according to the
system propagation characteristics; otherwise, intercellular or co-
channel interference occurs. The minimum distance necessary to reduce
co-channel interference is called the reuse distance. The reuse distance
is defined as the ratio of the distance, D, between cells that can use the
same channel without causing interference and the cell radius, R. Note
that R is the distance from the center of a cell to the outermost point of
the cell in cases when the cells are not circular.
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4. Figure 1
A given radio spectrum is to be divided into a set of disjointed channels
that can be used simultaneously while minimizing interference in
adjacent channel by allocating channels appropriately (especially for
traffic channels).
Channel allocation deals with the allocation of channels to cells in a
cellular network. Once the channels are allocated, cells may then allow
users within the cell to communicate via the available channels.
Channels in a wireless communication system typically consist of time
slots, frequency bands and/or CDMA pseudo noise sequences, but in an
abstract sense, they can represent any generic transmission resource.
There are three major categories for assigning these channels to cells
(or base-stations). They are
Fixed Channel Allocation,
Dynamic Channel Allocation and
Hybrid Channel Allocation.
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5. Fixed Channel Allocation
Fixed Channel Allocation (FCA) systems allocate specific channels to
specific cells. This allocation is static and cannot be changed. For
efficient operation, FCA systems typically allocate channels in a manner
that maximizes frequency reuse. Thus, in a FCA system, the distance
between cells using the same channel is the minimum reuse distance for
that system. The problem with FCA systems is quite simple and occurs
whenever the offered traffic to a network of base stations is not uniform.
Consider a case in which two adjacent cells are allocated N channels
each. There clearly can be situations in which one cell has a need for
N+k channels while the adjacent cell only requires N-m channels (for
positive integers k and m). In such a case, k users in the first cell would
be blocked from making calls while m channels in the second cell would
go unused. Clearly in this situation of non-uniform spatial offered traffic,
the available channels are not being used efficiently. FCA has been
implemented on a widespread level to date(shown in Figure 2).
In FCA schemes, a set of channels is permanently allocated to each cell
in the network.
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6. If the total number of available channels in the system S is divided into
sets, the minimum number of channel sets N required to serve the entire
coverage area is related to the frequency reuse distance D as follows:
N = D2 / 3R2
Due to short term fluctuations in the traffic, FCA schemes are often not
able to maintain high quality of service and capacity attainable with static
traffic demands. One approach to address this problem is to borrow free
channels from neighboring cells.
Figure 2
Dynamic Channel Allocation
In DCA schemes, all channels are kept in a central pool and are
assigned dynamically to new calls as they arrive in the system. After
each call is completed, the channel is returned to the central pool. It is
fairly straightforward to select the most appropriate channel for any call
based simply on current allocation and current traffic, with the aim of
minimizing the interference. DCA scheme can overcome the problem of
FCA scheme. However, variations in DCA schemes center around the
different cost functions used for selecting one of the candidate channels
for assignment (shown in figure 3).
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7. Figure 3
DCA schemes can be centralized or distributed.
The centralized DCA scheme involves a single controller selecting a
channel for each cell;
The distributed DCA scheme involves a number of controllers scattered
across the network (MSCs).
Centralized DCA schemes can theoretically provide the best
performance. However, the enormous amount of computation and
communication among BSs leads to excessive system latencies and
renders centralized DCA schemes impractical. Nevertheless, centralized
DCA schemes often provide a useful benchmark to compare practical
decentralized DCA schemes.
Dynamic Channel Allocation (DCA) attempts to alleviate the problem
mentioned for FCA systems when offered traffic is non-uniform. In DCA
systems, no set relationship exists between channels and cells. Instead,
channels are part of a pool of resources. Whenever a channel is needed
by a cell, the channel is allocated under the constraint that frequency
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8. reuse requirements cannot be violated. There are two problems that
typically occur with DCA based systems.
• First, DCA methods typically have a degree of randomness
associated with them and this leads to the fact that frequency
reuse is often not maximized unlike the case for FCA systems in
which cells using the same channel are separated by the minimum
reuse distance.
• Secondly, DCA methods often involve complex algorithms for
deciding which available channel is most efficient. These
algorithms can be very computationally intensive and may require
large computing resources in order to be real-time.
Centralised DCS Scheme
 For a new call, a free channel from the central pool is selected that
would maximize the number of members in its co-channel set.
 Minimize the mean square of distance between cells using the
same channel.
Scheme Description
First Available Among the DCA schemes the simplest one is the
(FA) FA strategy. In F A, the first available channel within
the reuse distance encountered during a channel
search is assigned to the call.
The FA strategy minimizes the system
computational time.
Locally Optimized The channel selection is based on the future
Dynamic blocking probability in the vicinity of the cell where a
Assignment call is initiated.
(LODA)
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9. Scheme Description
Mean Square The MSQ scheme selects the available channel that
(MSQ), minimizes the mean square of the distance among
the cells using the same channel.
1-clique This scheme uses a set of graphs, one for each
channel, expressing the non co-channel
interference structure over the whole service area
for that channel.
Distributed DCA Scheme
 Based on one of the three parameters:-
 Co-channel distance
- co-channel cells in the neighborhood not using the channel.
- Sometimes adjacent channel interference taken in to
account.
 Signal strength measurement
- anticipated CIR above threshold.
 Signal to noise interference ratio
- satisfy desired CIR ratio.
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10. Hybrid Channel Allocation
HCA schemes are the combination of both FCA and DCA techniques. In
HCA schemes, the total number of channels available for service is
divided into fixed and dynamic sets. The fixed set contains a number of
nominal channels that are assigned to cells as in the FCA schemes and,
in all cases, are to be preferred for use in their respective cells. The
dynamic set is shared by all users in the system to increase flexibility.
Request for a channel from the dynamic set is initiated only when the
cell has exhausted using all its channels from the fixed set (shown in
figure 4).
Extra features:-
3:1 (fixed to dynamic), provides better service than
fixed scheme for 50% traffic.
Beyond 50% fixed scheme perform better.
For dynamic, with traffic load of 15% to 32%, better
results are found with HCA.
Example: When a call requires service from a cell and all of its nominal
channels are busy, a channel from the dynamic set is assigned to the
call.
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11. Figure 4
Switching strategies
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12. Comparison between FCA and DCA
FCA DCA
 Performs better under heavy  Performs better under
traffic light/moderate traffic
 Low flexibility in channel  Flexible channel allocation
assignment
 Not always maximum channel
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13.  Maximum channel reusability reusability
 Sensitive to time and spatial  Insensitive to time and time spatial
changes changes
 Not stable grade of service per  Stable grade of service per cell in
cell in an interference cell an interference cell group
group
 Low to moderate forced call
 High forced call termination termination probability
probability
 Suitable in microcellular
 Suitable for large cell environment
environment
 High flexibility
 Low flexibility
 Radio equipment covers the
 Radio equipment covers all temporary channel assigned to the
channels assigned to the cell cell
 Independent channel control  Fully centralized to fully distributed
control dependent on the scheme
 Low computational effort
 High computational effort
 Low call set up delay
 Moderate to high call set up delay
 Low implementation
complexity  Moderate to high implementation
complexity
 Complex, labor intensive
frequency planning  No frequency planning
 Low signaling load  Moderate to high signaling load
 Centralized control  Centralized, distributed control
depending on the scheme
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14. Common Principles of Channel Allocation
Schemes
The large array of possible channel allocation systems can become
cumbersome. However, all channel allocation methods operate under
simple, common principles. Throughout this report we have touched on
three points which an efficient channel allocation scheme should
address:
1. Channel allocation schemes must not violate minimum frequency
reuse conditions.
2. Channel allocation schemes should adapt to changing traffic
conditions.
3. Channel allocation schemes should approach (from above) the
minimum frequency reuse constraints so as to efficiently utilize
available transmission resources.
As the first requirement suggests, all channel allocation schemes adhere
to condition 1. From a frequency reuse standpoint, a fixed channel
allocation system distributes frequency (or other transmission) resources
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15. to the cells in an optimum manner; i.e., common channels are separated
by the minimum frequency reuse distance. Thus, a fixed channel
allocation scheme perfectly satisfies condition 3 as well. However, a
fixed allocation scheme does not satisfy condition 2.
Philosophically, any dynamic channel allocation scheme will meet the
requirements of all of the
above three conditions to some degree. At the system architecture level
dynamic channel allocation schemes may differ widely, but
fundamentally, their only difference is in the degree to which they satisfy
condition 3. Different DCA schemes attempt to satisfy condition 3 (in
addition to conditions 1 and 2) by approaching the minimum frequency
reuse constraint arbitrarily closely, and by doing so in as short a time
period as possible. The above three conditions point to the fact that
design of dynamic channel allocation schemes falls within the general
class of optimization problems. Furthermore, since we can always
assume that the available number of base stations is finite and the
transmission resources will always be countable (due to FCC
requirements if nothing else) then our problem can be reduced to the
subclass of combinatorial optimization problems. As with all
combinatorial optimization problems, there will exist a solution space
and a cost function. A typical element of the solution space could be a
particular layout of frequency channels among the base-stations. The
cost function can be loosely characterized as the difference between the
frequency reuse of an arbitrary solution and the frequency reuse of the
optimized solution. The error associated with a non-optimized cost is
realized as a future increased blocking probability or an otherwise
unwarranted lack of channel availability. It is typically assumed that the
solution to the wireless dynamic channel allocation problem is NP-
complete [Yue, Cox - 1971]. The definition of np-completeness follows
from the conjecture made in the late 1960's that there exists a class of
combinatorial optimization problems of such inherent complexity that any
algorithm, solving each instance of such a problem to optimality, requires
a computational effort that grows super polynomially with the size of the
problem. In the case of dynamic channel allocation, the complexity is
generally attributed to the required inclusion of co-channel interference
in any analysis of dynamic channel allocation schemes. The author is
aware of one published article to date offering an analytical method
(approximate) for calculating the performance of dynamic channel
allocation. Recently, several approximation techniques have been
proposed as methods for solving condition 3 of the dynamic channel
allocation problem. In particular there has been interest in applying
simulated annealing techniques [Duque-Anton] and neural network
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16. methods to dynamic channel allocation.
Conclusion
This document has been briefly discussed about the static and dynamic
allocation techniques on cellular networks. These techniques have been
implemented in different areas and each technique has its advantages
and disadvantages. Numbers of works are going on this field so far and
furthermore many researches are going to make these techniques more
stable. Growing up mobile technologies must need a reliable technique
to cope up with this matter.
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17. Bibliography
This document has been created with the help of
Wireless communication department paper
Challenges of computing in mobile cellular environment—a survey
by
S. DasBit*, S. Mitra
Wireless telecommunication Lab Document
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