Hit Minimum SAR With EM Software

May 20, 2009
The use of finite-difference-time-domain (FDTD) electromagnetic (EM) software can predict specific absorption rate (SAR) levels for cellular telephone antennas under different conditions.

Electromagnetic (EM) energy and human health issues have long been a concern with the growing use of portable wireless devices. Because of this, many countries now require compliance with specific absorption rate (SAR) specifications for EM radiation. Fortunately, by using SAR simulation software, designers can estimate SAR performance at the initial stages of product concept and development, saving countless design iterations (and cost) in order to comply with SAR requirements. SAR simulations are useful for a wide range of product designs, including cellular handsets and other portable wireless devices.

Wireless technology has brought a great deal of convenience to consumers around the world, but the proliferation of radiated EM energy requires designers to pay increasing attention to how low EM radiation impacts the human body. The regulating bodies of the major markets are paying a great deal of attention to this area as well. In cellular telephone research and development, antenna engineers place great importance on a number of parameters to determine the impact of a product on its users, including SAR, total radiated power (TRP), total isotropic sensitivity (TIS), return loss, and efficiency.

EM simulation software for antenna design, such as tools from Agilent Technologies based on finite-difference-time-domain (FDTD) algorithms, is compatible with a wide range of mechanical design software and optimally suited for modeling complete computer-aided-engineering (CAE) designs, such as multiple antennas embedded within a compact mobile telephone handset. The software can simulate a complex solid handset by importing files from the mechanical design software, such as AutoCAD, while also providing the capabilities for parameterizing the physical shape and size of the mobile handset for optimization and simulation sweeps. The software can display various parameter curves and can more visually display EM variations with time step. After simulation, designers can obtain the far- and near-field EM radiation values, radiation patterns, efficiency, antenna impedance and gain, port S-parameters, SAR, and steady-state field data.

The SAR is defined as the EM radiation (exposure) energy absorbed by an organism in a unit time (s) and unit mass (kg). It can be divided into local and average SAR. The relevant expression for local SAR is given by:

SAR = σ E2/ρ = C (dT/dt)|t = 0 where
E = the electric field strength value within the organization (V/m);
σ = the conductivity of the medium (S/m);
ρ = the tissue density (kg/m3);
C = the specific heat capacity of the tissue under study (J/kg-K); and
(dT/dt)|t = 0 = the initial temperature increase at time = 0 (K/s).

The SAR standards are different in Europe versus the United States. In the US, the SAR is averaged over 1 g of tissue while the European standard averages the SAR over 10 g of issue. The units of measure in both cases are mW/g or W/kg.

When designing an antenna for a mobile handset, a major concern is the impact of the EM radiation from the wireless communications terminals upon the human head (of the cellular telephone user). The SAR value is closely associated with the radiated power of the mobile telephone. In the design of a cell phone, it is necessary to maximize antenna efficiency while minimizing SAR values.

A SAR measurement system includes the human model, electronic measuring instruments, a scanning positioning system, test fixtures, connecting cables, and other accessories. The distribution of the electric field within the measurement system and the model handset can be measured by the use of an automatic positioning field probe. According to the measured field strength value, it is possible to calculate the distribution of SAR and the space average peak SAR. When performing SAR measurements on a folding antenna design, the antenna should be tested both fully opened and retracted or folded. A mobile telephone that can be turned, such as a sliding or rotary design, should be tested in both states if it can be used to make calls with both the cover closed and opened, since it will transmit EM energy in both states.

The initial step in this SAR simulation is to import the Standard Anthropomorphic Model (SAM) head model (IEEE Standard 1528a-2005) and the mobile telephone model into the simulation software. The standard shape of the head model is based on human studies of adult men, and the model of the ear can simulate the ear's state when the individual uses a handheld wireless device.

In the actual SAR test, the simulation is divided into two states: the "press close to cheek" state and the "tilt 15 deg." state. These distinctions are based on the different habits of handset owners in using their mobile telephones, and in trying to determine accurate SAR readings for the two different positions of the mobile handsets relative to the human head. Another test distinction is left ear and right ear. Figure 1 shows the head model and the relative position for the cellular telephone model during testing. Figure 1 and 2 give the "press close to cheek" and "tilt 15 deg." positions from the perspective of the three observations of the floor plan. The relative placement of the mobile telephone must be accounted for when performing the simulation.

The first step in performing the SAR simulation involves adjusting the location of the cellular telephone model. The relative position of the cellular telephone model and the head model has a great impact upon the SAR value; therefore, either in a simulation or during testing, the positioning of the two models is extremely important. After the model is imported into the simulation software, the relative position of the head model and the cellular telephone models should be adjusted according to the chosen state.

While adjusting the model, the software tools are used to set the coarse adjustment in the Geometry/View interface, (which provides accurate positioning in the planes of XY, YZ, and XZ planes, and zooming in for accurate positioning adjustments). In addition, the software can be used to select the devices to be adjusted and its editing tools applied for achieving accurate positioning. For this example simulation, the "press close to cheek" option was selected with the cellular telephone handset on the right side of the head model, and with the telephone handset receiver model positioned at the center of the human ear.

To adjust the model, it is best to maintain a fixed position for the cellular telephone by changing the position of head model to adjust the relative position between them. This is because the other devices around the antenna have a certain impact on SAR values, so in the actual test, it is sometimes necessary to replace some devices such as microphones, batteries, and so on, to test if these devices have any impact on SAR. When the software is used to assess the impact of the replacement device upon the antenna, it is possible to directly import any replacement devices into the simulation setup in order to study the effects and not have to readjust the relative position between the cellular telephone handset and the head model if the locations of the mobile telephone remains the same.

The next step in the simulation involves subdividing the simulation mesh for EM analysis. If the grid subdivision is too coarse, it will affect the accuracy of the simulation results. If it is too fine, it will increase the amount of computing power needed and extend the simulation time. Devices that are the most important to model in the simulation setup, such as antennas, should be meshed with precedence over the others. Considering the accuracy and the time factor, the mesh size for the head model is optimized at 2.5 x 2.5 x 2.5 mm, the cellular telephone mesh size at 1.5 x 1.5 x 1.5 mm, the printed-circuit-board (PCB) z-direction mesh size at 1 mm, and the antenna mesh size at 1.5 x 1.5 x 1.5 mm. Figure 3 and 4 show the overall partitioning of the mesh and the three-dimensional view of the overall modeling/test setup, respectively.

Following subdivision of the mesh, the next step in the simulation sequence involves setting the simulation parameters. The conductivity and dielectric constant of the tissue fluid within the head have significant impact on the SAR. When at a certain dielectric constant, the SAR is directly proportional to the conductivity. Therefore, before testing the SAR, it is necessary to precisely define the dielectric constant of the human tissue in the simulation. It is important to note that the tissue fluid is not the same during the testing of high-frequency and low-frequency sources, so it is necessary to set the dielectric constant and the conductivity of the high-frequency and lowfrequency conditions, and then carry out the simulation. For the greatest accuracy, the parameters must be the same when used in the simulation and in measurements. In this example simulation, the target simulation object is the cellular handset's embedded antenna, which works at GSM 900 and 1800 MHz frequencies. The 10-g (European SAR standard) options were chosen for the simulation.

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Once the settings have been established, it is time to perform the simulation. The simulation should include calculations for VSWR and S-parameters. The software guarantees that the mesh exactly follows the shape of the feed and the antenna that is directly related to the success of simulation. The use of a hardware-accelerator card in the simulation computer can increase the computing speed of the simulation by 10 to 20 times.

For this example, the software was run on a Dell 490 desktop computer with Acceleware hardware-accelerator card. The driving source was a sinusoid and the simulation channel was 512, with a corresponding frequency of 1710 MHz to emulate the operation of the cellular telephone handset. While conducting the SAR simulation, the time-consumption of a channel was 17 minutes (see Fig. 5).

In order to compare the simulations with measured results, it is necessary to perform testing with the same settings as used in the simulation.

Six measurement channels were chosen for testing for the GSM900/1800 handset; the channels correspond with the different frequency points. Figure 6 shows the SAR level simulation results for channel Ch512. The value of the 10-g standard is 0.805 mW/g, in contrast to the result measured in the laboratory at 0.756 mW/g. In the same way, other channels were analyzed, with the results shown in the table.

The American and European standards with regard to SAR values are somewhat different. In the United States, for example, the Federal Communications Commission (FCC) works closely with federal health and safety agencies, such as the Food and Drug Administration (FDA), to determine limits for safe exposure to RF energy. The SAR requirements in the US call for values of less than or equal to 1.6 mW/g (or 1.6 W/kg), averaged over 1 g of tissue. The FCC requires cellular telephone manufacturers to ensure that their telephones comply with these objective limits for safe exposure. Any cellular telephone at or below these SAR levels is considered a "safe" telephone in the US, as measured by these standards. In contrast, the European standards require that that SAR values be less than or equal to 2.0 mW/g averaged over 10 g of tissue. The data in the table is within the acceptable range. It shows that the SAR values of the antenna under study fall safely within both US and European standards requirements.

As has been shown, it is possible to perform SAR simulations on embedded cellular telephone antennas using FDTD EM simulation software. The simulation results compare favorably with measured results, with simulations completed relatively quickly and with high precision. These simulated results can provide engineers with the insight and guidance needed to improve the efficiency of an antenna design while minimizing the SAR levels, without time-consuming design iterations. The EM software can also accurately simulate a number of critical parameters for antennas, such as Hearing Aid Compatibility (HAC), to help designers predict antenna performance, while shortening the design cycle and reducing design risk.

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