Tunable antenna system

A technique for tuning an antenna may include one or more of the following: working against a ground plane, utilizing the third dimension by alternating layers on a substrate, integrating an inductive short stub in the substrate to improve port matching, and making a tuning port available for capacitive loading and resonance modification.

BACKGROUND

A common method of lowering resonant frequency of an antenna is to capacitively load an end of the structure. This method works for different types of antennas, for example a patch antenna or a monopole (e.g., dipole, folded antenna, or spiral).

Antenna bandwidth and quality (Q) factor are related to antenna volume. Generally, a higher antenna volume will result in higher bandwidth. The antenna Q factor, which is inversely related to the bandwidth, increases as the antenna volume is reduced. Therefore, if one is forced to reduce the size of an antenna due to size constraints, the bandwidth of the antenna is reduced as well. In cases where the required operating frequency range exceeds the antenna bandwidth, the antenna may be unable to overcome the narrow bandwidth.

DETAILED DESCRIPTION

In the following description, several specific details are presented to provide a thorough understanding of examples of the claimed subject matter. One skilled in the relevant art will recognize, however, that one or more of the specific details can be eliminated or combined with other components, etc. In other instances, well-known implementations or operations are not shown or described in detail to avoid obscuring aspects of the claimed subject matter.

FIG. 1depicts an example of a tunable antenna system100with variable capacitive loading. The system100includes ground102, switches104, capacitor bank106, an antenna feed108. In operation, some of the switches104may be closed, electrically coupling ground102through the switches104to the capacitor bank106, which is in turn electrically coupled to the antenna feed108.

To tune antenna resonance of the system100, the switches104may be opened or closed to vary the amount of capacitive loading. In the example ofFIG. 1, the capacitor bank106includes multiple fixed capacitors that are switched on or off dynamically depending on the amount of desired capacitive loading.

A more sophisticated technique to change capacitive loading is through a tuning voltage-variable capacitor (varactor)206, as shown inFIG. 2. In this method the capacitive load value can be changed dynamically by changing a voltage input to the capacitor.

FIG. 3depicts an example of a tunable antenna system300with a folded antenna extended to multiple folds. The system300includes a substrate302, a spiral antenna304, a varactor port306, and an antenna port308. The substrate302is optional, but is typical in antenna implementations. The spiral antenna304is an example of a folded antenna that is extended to multiple folds for, for example, size reduction. Capacitive loading of the spiral antenna may or may not be achieved in a similar method as a folded monopole.

FIG. 4depicts an example of a tunable antenna system400with an alternate layer that electrically couples a varactor to ground. The system400includes ground402, a spiral antenna404, a varactor406, an internal trace408, and an antenna feed410. Ground402is coupled to the spiral antenna404at the varactor406. By adjusting voltage to the varactor406, the spiral antenna404can be tuned. The internal trace408electrically coupling the varactor406to the spiral antenna404is on an alternate layer, as is illustrated inFIG. 4by the internal trace408passing underneath a portion of the spiral antenna404. For illustrative purposes, the feed410is coupled to the end of the spiral antenna404opposite the varactor406.

FIG. 5depicts a flowchart500of an example of a method for designing a tunable antenna. The flowchart is depicted as modules organized in a particular manner. However, it should be noted that the modules might be reorganized into a different order, or for parallel operation.

In the example ofFIG. 5, the flowchart500starts at module502with designing a physical structure of an antenna without loading or tuning capacitance. A goal is to design an antenna that has a frequency response that is centered with respect to an operating frequency band. For instance, if the operating band is the 2400 to 2483 MHz WLAN range, it may be advantageous to design the antenna with its center frequency positioned at the center of the WLAN band, or2441.5. It is also typically desirable to minimize return loss.

In the example ofFIG. 5, the flowchart500continues to module504with determining an available dynamic capacitive device tuning range. The dynamic capacitive device may be, by way of example but not limitation, a varactor or bank of switchable capacitors. By way of example but not limitation, a varactor might have a tuning range of 1 to 9 pF, or any other known or convenient tuning range.

In the example ofFIG. 5, the flowchart500continues to module506with introducing an initial capacitive load based on the tuning range. The initial amount of capacitive loading is dependent on the achievable capacitive tuning range provided by the dynamic capacitive device. For instance, if a varactor is capable of providing a 1 to 9 pF tuning range, it may be desirable to start with an initial loading of 5 pF.

In the example ofFIG. 5, the flowchart500continues to module508with re-optimizing antenna dimensions for the desired center frequency, bandwidth, and return loss. At this point, variations in capacitive loading are likely to result in variations in center frequency of the antenna response with respect to the operating band.

In the example ofFIG. 5, the flowchart500continues to decision point510where it is determined whether an acceptable optimization threshold has been reached. The threshold may be arbitrary, or dependent upon specific implementation- or embodiment-related variables. For example, in certain implementations, better optimization may be more important than in others.

While the acceptable optimization threshold has not been reached (510-N), the flowchart500continues to module512with adjusting the amount of loading to increase coverage of the frequency band during the tuning process, then returns to module508and continues from there as described previously. Ideally, but not necessarily, increased coverage achieved by adjusting the capacitive load will result in coverage of the entire frequency band. When the acceptable optimization threshold has been reached (510-Y), the flowchart500ends, having obtained the desirable optimization.

As previously mentioned, there is a direct correlation between antenna bandwidth and antenna volume. Therefore, instead of being limited to a planar structure, one can utilize the z-axis to expand the volume of an antenna, without affecting the xy area. By way of example but not limitation, a spiral antenna can be expanded in volume by alternating the traces between several layers of a substrate material.

FIG. 6shows a 3-D spiral antenna600.FIGS. 7 and 8depict response of the antenna port ofFIG. 6while applying 3 different capacitor values to the tuning port. For example,FIG. 7depicts port response for different capacitive loading on a dual-band tunable antenna.FIG. 8depicts a magnified portion of lower band frequency response with 3 different values for the tuning capacitor.

Tuning an antenna can be based on any desired performance metric. Received signal strength, or RSSI, is a desirable metric on which to base the tuning since it is a good indicator of antenna matching to the desired signal frequency. Other useful performance metrics include Signal to Noise Ratio (SNR) and packet error rate (PER), or combinations of RSSI, SNR, and/or PER. However, any applicable known or convenient performance metric may be used in various embodiments and/or implementations.

FIG. 9depicts an example of a tunable antenna system900with a radio receiver that provides performance metric data associated with a received signal to a tuning voltage calculator. The system900includes an antenna904, a varactor906, a radio receiver910, a performance quantification engine912, and a tuning voltage calculator914. For illustrative purposes only, the antenna904is depicted as a spiral antenna like the spiral antenna304(FIG. 3).

In the example ofFIG. 9, the radio receiver910is coupled by an antenna feed to the antenna904and, in operation, receives signals from the antenna904. Performance metric data associated with the signals are provided to the performance quantification engine912. Performance metric data may include practically any data associated with the signal, such as signal strength. The performance quantification engine912may use the performance metric data directly, or in conjunction with historic signal data, to estimate a desirable performance control signal. In some embodiments, the radio receiver910may include the performance quantification engine912, but this is not critical to an understanding of the techniques described herein. The performance control signal from the performance quantification engine912instructs the tuning voltage calculator914to either make no change to a tuning voltage currently coupled to the varactor906, or to increase or decrease the current tuning voltage. In this way, signals received from the tuned antenna904will, under normal operating conditions that properly implement this technique, have improved performance as measured by the performance metric.

Performance metric data is associated with a received signal, such as RSSI, SNR, PER, or some other performance metric. The performance metric data could provide a performance metric without any processing (e.g., the signal strength could be used directly to estimate performance). A performance metric could use data from multiple signals concurrently, or make use of historic signal data, to estimate RSSI, SNR, PER, or other performance metric.

The performance quantification engine912could repeatedly or periodically perform single-stage tuning, or perform stage one tuning one or more times then use a different performance metric to accomplish stage two tuning. Repetition of either first, second, or other stage tuning could be desirable to adjust to temperature changes or other changes associated with circuit aging, as this aging can change the performance and specifications of circuit active (e.g. transitors) and passive (e.g. resistors, capacitors, and inductors) components. As one of many examples, the first stage tuning could be occasionally repeated to take into account possible changes to the antenna caused by temperature variations, moisture, circuit changes (e.g., bias current could change). In this example, the second stage tuning may be repeated more frequently and more quickly.

As another example the first stage tuning may have lower complexity than the second stage tuning. So, the first stage tuning is fast, and the second stage tuning takes longer to complete. The amount of second stage tuning might be set dynamically (e.g., when the system decides it has resources to spare to do a more thorough tuning) or preset.

As another example, a reason to repeat one or both stages is that a system may dynamically change its frequency of operation and/or its signal bandwidth, which would benefit from retuning the antenna.

A reason to have two stages could be that the first stage must be done quickly to ensure reasonable operation, so would be based on a fast computation, and then fine tuning in a second stage could be done more slowly. Another reason to have two stages is complexity. One of the stages could be based on a simple algorithm that could be updated fairly often. A more complex algorithm could be done in the other stage, which would be performed less often to save power. A third reason to have more than one stage is that the performance metric associated with the first stage could be instantaneous, while the performance metric associated with the second stage could be based on instantaneous as well as past measurements, and hence would need more time to do the calculation.

The performance quantification engine912could generate a performance control signal using multiple performance metrics in parallel. Alternatively, the performance quantification engine912could generate a performance control signal using one or more performance metrics, and fine tune the performance control signal using the same or different performance metrics. In other words, multiple performance metrics could be applied in parallel or serially.

FIG. 10depicts a flowchart1000of an example of a method for a tuning voltage calculation using a performance metric.FIG. 10depicts modules organized in a particular order. However, the modules may be rearranged to change their order or for parallel execution.

In the example ofFIG. 10, the flowchart1000starts at module1002with setting tuning voltage to an initial value. The initial value may be, for example, a starting nominal value, a value that sets a dynamic capacitive device at a level halfway between the minimum and maximum values, an initial “best guess” regarding performance, or some other appropriate, random, or arbitrary starting value. Moreover, the setting could be implicit, for systems that have a value at startup.

In the example ofFIG. 10, the flowchart1000continues to module1004where performance metric data associated with one or more signals is quantified. The signals may be received on an antenna, such as the antennae described with reference toFIGS. 1-9. Performance metric data may be included in the signals themselves, or derived from the signals individually or relative to one another or relative to historic signal data. Quantification may yield a value such as an RSSI, a SNR, or a PER.

In the example ofFIG. 10, the flowchart1000continues to module1006where a tuning voltage that would improve performance associated with the signals is estimated. For example, if the applicable performance metric is RSSI, the tuning voltage estimate will be for a voltage that is estimated to improve RSSI for future signals. Of course, the RSSI used is for signals that were already received, so the improved performance is associated with the received signals with the assumption that future signals will be sufficiently similar such that an improvement in performance for past signals will result in an improvement in performance for future signals; this is typically a safe assumption.

If multiple performance metrics are considered simultaneously, it may be that the estimate is different for one or more of the applicable performance metrics. In such a case, the performance metrics may be weighted and a weighted average performance improvement may be estimated. Any appropriate algorithm could be implemented to achieve desired weighting, or lack thereof, for various performance metrics, and depending upon the embodiment or implementation. The algorithm could also use different weighting dynamically in response to an environment or configurable conditions.

In the example ofFIG. 10, the flowchart1000continues to module1008where tuning voltage is varied in accordance with the estimate. For example, if it is estimated that SNR will be higher if voltage is increased to a tuning capacitor device, then the tuning voltage will be increased in accordance with the estimate.

In the example ofFIG. 10, the flowchart1000continues to decision point1010, where it is determined whether to repeat the quantification of performance metric data. This may be desirable to occasionally or periodically adjust the tuning of the antenna. If it is determined that the quantification is to be repeated (1010—Yes), the flowchart1000returns to module1004and continues as described previously. If, on the other hand, it is determined that the quantification need not be repeated (1010—No), the flowchart1000continues to decision point1012where it is determined whether second stage tuning is desired.

It may be noted that when a system includes second stage tuning, continuing to module1004may be in accordance with a first stage or a second stage. If neither first stage tuning (1010—No) nor second stage tuning (1012—No) is desired, the flowchart1000ends, having performed the tuning function for the requisite duration, number of times, et al.

If it is determined that second stage tuning is desired (1012—Yes) in lieu of repeating first stage tuning, the flowchart1000continues to decision point1014where it is determined whether to use the same metric as before. If it is determined that the same metric is to be used (1014—Yes), the flowchart1000returns to module1004and continues as described previously. It may be noted that first stage tuning (1010—Yes) and second stage tuning with the same metric (1014—Yes) may or may not be identical. For example, the tuning voltage may be set according to the estimate for each repetition, while the tuning voltage may be adjusted more gradually according to the estimate for a fine tuning using the same performance metric or metrics.

If it is determined that the same metric is not to be used (1014—No), then the flowchart1000continues to module1016where a different performance metric or set of performance metrics are considered, then the flowchart1000continues to module1004as described previously. The different performance metric(s) may be an entirely different set of performance metrics from those considered in previous iterations of the flowchart1000, or the sets could be overlapping. Typically, though not necessarily, second stage tuning may be desirable in this case to avoid fluctuations due to differing estimates based upon differing performance metrics; not all performance metrics will necessarily yield the same estimates under identical conditions.

Note that the input impedance of an antenna is also affected when the size is reduced by multiple folds and alternating layers. The detuning of antenna impedance is compensated for by using reactive matching elements. For instance, as in the case of the folded antenna with a capacitive loading built into a PC board structure, if the spiral antenna's input impedance is capacitive at the desired resonant frequency, a shunt inductive stub will retune the input to the desired resistive value. Advantageously, use of a shunt inductive stub in the context of the techniques described herein can reduce mismatch, which would increase SNR and efficiency. This can in turn impact the performance metrics used as described previously.

FIG. 11depicts an example of a tunable antenna device1100. The tunable antenna device1100includes a spiral folded monopole1102implemented with a three-dimensional structure1104, an inductive short stub1106, and a tuning port1108.

In the example ofFIG. 11, the spiral folded monopole1102works against a ground plane. Notably the spiral folded structure enables one to create a small antenna. Unfortunately, although the structure may have good bandwidth characteristics, it is relatively difficult to tune compared to larger antennae.

In the example ofFIG. 11, the three-dimensional structure utilizes the third dimension by alternating layers on a substrate. This provides improved bandwidth characteristics for a relatively small antenna. However, as was indicated with respect to the spiral folded monopole1102above, it is not as easy to tune a small antenna as a large one.

In the example ofFIG. 11, the inductive short stub1104is integrated in the substrate to improve port matching (impedance mismatch). This can somewhat ameliorate the problems introduced by decreasing the size of the antenna using the tuning techniques described herein.

In the example ofFIG. 11, the tuning port1106is available for capacitive loading and resonance modification. The tuning facilitates keeping a frequency band centered, which is of increasing importance as the size of the antenna decreases. This type of tuning may have little to no practical impact on large antennas. However, for frequency ranges in, for example, the Wi-Fi band, with a small antenna, performance can be improved.

Advantageously, using the techniques described herein, an antenna can be made that has a compact size, tunability, and integrated matching. This may facilitate antenna integration with an IC package.

Systems described herein may be implemented on any of many possible hardware, firmware, and software systems. Typically, systems such as those described herein are implemented in hardware on a silicon chip. Algorithms described herein are implemented in hardware, such as by way of example but not limitation RTL code. However, other implementations may be possible. The specific implementation is not critical to an understanding of the techniques described herein and the claimed subject matter.

As used herein, the term “embodiment” means an embodiment that serves to illustrate by way of example but not limitation.