The Effect of Power Increment on Cell Breathing and Capacity
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Date
2022
Authors
Qashou Ahmad
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Abstract
Over the past decade, wireless communications have seen exponential growth and will certainly continue to witness spectacular developments due to the emergence of new interactive multimedia applications and highly integrated systems driven by the rapid growth in information services and microelectronic devices. However, In the 3G mobile networks, broadband data access at high transmission rates will be needed to provide users with packet-based connectivity to the services.
In 3rd generation (3G) systems, although there is no need for frequency planning as in 2G systems, the limitation of both capacity and coverage due to interference levels in the system makes the planning task for 3G systems much more complex than for the 2G systems. In 2G systems, coverage prediction and capacity estimation are mostly separable.
In traditional FDMA/TDMA systems, coverage is purely determined by RF transmission aspects, and the maximum capacity of the cell is only limited by the number of radio terminals at the base station (BS). In contrast, since the communication channels are separated by different time and frequency slots, in a CDMA 3G system, all users access the same frequency band simultaneously. Each communication channel is separated by modulating the data signal with a noise-like carrier, which is unique to the link, and spreading the modulated signal over a large frequency bandwidth.
Since the signal appears like noise over the channel, the signals from all other users constitute a certain level of interference. This leads to a new definition of capacity, that of "soft capacity." According to this concept, it is permissible to accept more users into the cell at the price of a slight loss in quality in terms of mean signal-to-interference ratio (SIR).
Due to the soft-capacity nature of CDMA networks, the coverage of a cell depends intensely on the desired QoS in terms of sustainable interference level, spatial mobile user distribution, and corresponding time-dependent user traffic intensity. Hence, on the dynamics of the power control procedure used to adjust interference. The fact that capacity in CDMA networks is influenced by the number of users in the cell has let the cell coverage area be considered elastic. This well-known cell breathing effect leads to an iterative approach to compute the power allocated to each user and the level of interference. These computations depend directly on the user locations and on the services (data rate) used. Thus, 3G-radio network planning is performed through simulations of user and service distributions.
Cell breathing happens when part of the cell loses coverage and becomes a "dead area". This can be explained when a new mobile user is admitted to the network, the interference observed by each user in the cell increases, and their SIR at the BS decreases. As a result, users are required to transmit with higher power to compensate for the increase in the interference level. Eventually, as more users are admitted to the network, users at the edge of the cell are transmitting at their maximum power.
As they move closer to the cell boundary, they will run out of the necessary power to maintain the connection; they will be dropped. In effect, cell coverage has shrunk. This means that during periods of low traffic, such as in the early morning, users can take advantage of a relatively large footprint for cell coverage. But as the traffic level rises during the day, users on the outer edges of a particular cell may effectively lose coverage and suddenly find themselves unable to make or receive calls.
In this project, we aim to create a simulation model that shows the effect of increasing the transmitted power of a cell in a geographical coverage area during periods, of low traffic and when the traffic level rises during the day. Such model will be verified by collecting data through comprehensive drive test in the targeted cluster or region while monitoring the required cluster KPIs, which will determine the performance of cell throughout the day, therefore enables us to get a clearer understanding on the relation between the increasing the power and the traffic load on the cell's coverage area.