Patent Application
20100029210
The teachings herein relate generally to cognitive radio networks and sensing spectrum therein that a cognitive radio device may then use opportunistically as it is available and not in use by primary users operating with allocated resources. These teachings are particularly related to employing an analog to digital converter in such cognitive spectrum sensing.
Spectrum sensing is needed in cognitive radios to find empty slots in the radio spectrum which can subsequently be used in an opportunistic manner. Traditionally radio spectrum is divided between different radio systems in a manner that strictly allocates a specific band to a specific system. This strict allocation will be changing to a more flexible spectrum utilization at least in some frequency bands in the future. Primary users are those operating within the more formal networks such as hierarchical networks (e.g., WLAN or cellular such as GSM, GERAN, UTRAN and E-UTRAN) and ad hoc networks (e.g., WiFi). Secondary users are those operating outside the structure of the formal networks. Since essentially all spectrum in crowded areas that is useable by mobile terminals is allocated to some formal network or another, the secondary users find and utilize portions of the existing networks' spectrum in an opportunistic manner. Consequently, two related obstacles face the secondary user: it must not interfere with the primary users, and it must somehow find those portions of the spectrum not currently in use by any of the formal networks. For this latter reason the secondary users are generally referred to as cognitive users; they must be spectrum-aware rather than simply using the radio resources allocated by some access node controlling a cell of users.
The secondary user/cognitive radio therefore utilizes or exploits a free region of spectrum for its own transmissions, outside control of the formal networks. By “free” what is meant is that the primary users/formal networks are not using the spectrum region in question when considering time, frequency and space. Thus, radios that contend for radio resources within a pre-ordained contention period are not considered cognitive radios. Alternatively there could be a band that is dedicated to several radio systems operating under a certain set of rules or policies. The common factor in any case is that the radio spectrum will have to be sensed somehow in order for the cognitive radio/secondary user to locate the free spectral band. This sensing has to at least take into account time, frequency and space.
The cognitive radio may or may not also be in communication with a more traditional cellular or other type network, but the cognitive function is independent. Spectrum sensing may be done by each radio for the entire spectral band to be sent or it may be partitioned in some way among the various cognitive radios. The former is power intensive for radios having a portable power supply, and the latter implies a non-negligible signaling overhead to inform the sister cognitive radios of each other's sensing result, particularly challenging when the spectrum is only available opportunistically.
The cognitive radio system is best served when the spectrum analyzed for these opportunistic frequency ‘holes’ is wideband, giving a higher likelihood of finding a sufficient number of holes not occupied by the primary users to carry on an ongoing communication. However, the continuous-time wideband frequency analysis combined with high accuracy is extremely difficult since it would require high speed and high resolution analog-to-digital converters ADCs.
One way to increase accuracy is to analyze only narrow bands. However, in order to cover wide-bands this method is slow and does not necessarily capture time-variant changes. As a solution to this problem there have been spectrum evaluation schemes that can be broadly categorized as two types. One type analyzes spectrum in narrowband, capable of detecting very weak as well as large signals within this narrow band. The other type evaluates wideband spectrum with limited accuracy, and while the band evaluated is much wider than the narrowband type it can only detect signals which have powers above a specific threshold level. The wideband approach requires implementation of a high speed ADC which increases power consumption of the ADC itself and in addition it increases the speed requirements and power consumption of the following digital circuitry. Generally, very wideband spectrum analysis requires significant power consumption even with moderate accuracies, making the implementation of this type of sensing very challenging.
Being a very forward-looking technology at this stage of development, there is not a great volume of prior art in the spectrum sensing field. Two are noted below as potentially relevant to these teachings.
EP0582037 is entitled Method and Apparatus for Improving Wideband Detection of a Tone. It describes that an in-phase signal is sampled at an input of a first analog-to-digital converter (41), and a quadrature signal is sampled at an input of a second analog-to-digital converter (42). The output of the first analog-to-digital converter (41) is delayed by an amount equal to one, plus an integer number times four, sample periods to provide a delayed in-phase signal. Then the delayed in-phase signal is added to the quadrature signal to provide a sum signal. Then a tone is detected in the sum signal. In one embodiment, a data processor (32) stores the output of the analog-to-digital converters (41, 42) in memory (34) and processes the data as programmed by microcode (33).
WO2007/056673 is entitled Wide-Bandwidth Spectrum Analysis of Transient Signals Using a Real-Time Spectrum Analyzer. This paper describes its teachings as selecting a frequency window for a real time analyzer RTSA acquisition, the frequency window being narrower in bandwidth than the frequency spectrum of interest. An RTSA is tuned to a plurality of different frequencies within the frequency spectrum of interest, where such successive tuning is controlled based on a characteristic of the signal. The RF signal is received, and for each of the plurality of different frequencies, power data is acquired for the signal in a band centered on the frequency and having a bandwidth equal to that of the frequency window. A representation of the frequency spectrum of interest is then constructed from the power data acquired during the successive tunings of the RTSA
But as noted above, wideband spectrum sensing for the cognitive radio purpose is highly power-intensive, and the vast majority of cognitive radios are anticipated to be portable wireless devices. What is needed in the art is a way to find those free areas that may be located anywhere among the wideband spectrum at various times with low power requirements and high confidence level.
In accordance with one embodiment of the invention there is a method that includes downconverting a first analog signal, sampling the downconverted first analog signal using a first set of analog-to-digital converter sampling parameters, and storing a resulting first set of samples. The method continues in downconverting a second analog signal, sampling the downconverted second analog signal using a second set of analog-to-digital converter sampling parameters, and storing a resulting second set of samples. Then are determined samples that are common to the first set of samples and the second set of samples, and the determined samples are output.
In accordance with another embodiment of the invention there is an apparatus that includes a local oscillator, and analog-to-digital processor, a memory and a processor. The local oscillator is configured to downconvert a first analog signal and a second analog signal. The analog to digital converter is configured to sample the downconverted first analog signal using a first set of analog-to-digital converter sampling parameters, and to sample the downconverted second analog signal using a second set of analog-to-digital converter sampling parameters. The memory is configured to store a first set of samples from the analog to digital converter sampling of the first analog signal and to store a second set of samples from the analog to digital converter sampling of the second analog signal. And the processor is configured to determine samples that are common to the stored first set of samples and the stored second set of samples and to output the determined samples that are common.
In accordance with another embodiment of the invention there is a computer readable memory embodying a program of machine-readable instructions executable by a digital data processor to perform actions directed toward Sampling analog signals. In this embodiment the actions include downconverting a first analog signal, sampling the downconverted first analog signal using a first set of analog-to-digital converter sampling parameters, and storing a resulting first set of samples, downconverting a second analog signal, sampling the downconverted second analog signal using a second set of analog-to-digital converter sampling parameters, and storing a resulting second set of samples, determining samples that are common to the first set of samples and the second set of samples, and outputting the determined samples.
In accordance with another embodiment of the invention there is an apparatus that includes conversion means (such as for example an analog to digital converter), storage means (such as for example a computer readable memory), and decision means (such as for example a processor, ASIC or FPGA). The conversion means is for sampling a first analog signal at a first frequency and for sampling a second analog signal at a second frequency. The storage means is for storing a first set of samples from the conversion means' sampling of the first analog signal and for storing a second set of samples from the conversion means' sampling of the second analog signal. And the decision means is for deciding samples that are common to the stored first set of samples and the stored second set of samples and for causing the determined samples that are common to be output for signal processing.
These and other aspects of the invention are detailed more particularly below.
The foregoing and other aspects of these teachings are made more evident in the following Detailed Description when read in conjunction with the attached Drawing Figures.
The inventors' solution to the problem formulated above involves using the folding phenomena of the ADCs for spectrum analysis, which will be shown to reduce significantly the overall power consumption of the spectrum receiver. Detailed further below is how to define the “original” frequencies from the folded spectrum. Specifically, some of the below teachings can be parsed into the following categories:
Use of folding phenomena of the ADC for spectrum estimation.
Use of combinational method for discovering original frequencies in the spectrum estimation.
Use of local oscillator LO shifting for discovering original frequencies in the spectrum estimation.
Use of sampling frequency alteration for discovering original frequencies in the spectrum estimation.
Consider a broad example: the cognitive radio receiver is doing some kind of narrowband spectrum analysis. However, it needs information of the spectrum from some wider band that is analyzed with some narrowband method. This information may be needed, for example, to detect changes in the environment that may affect the narrowband analysis. Mainly the information on large signals, which are passed to receiver input are interesting for the analyzer. Thus some wideband spectrum analyzer is needed. These teachings improve power consumption in that wideband sensing as compared to the prior art.
The spectrum is analyzed using functions found on a typical spectrum analyzer. Extending this to the mobile environment, the spectrum analysis may be done using a wideband high speed ADC with moderate accuracy, or using a lower speed and high accuracy ADC for the narrower bands. If large spectrums would be analyzed in details with high accuracy, going through the entire wideband spectrum would require time, which as above undermines the whole spectrum sensing process when primary users and the holes they leave shift regularly, as it's the case in crowded radio use areas.
The folding aspect of ADCs is known in the art. However, to the invertors' knowledge it has not been used in spectrum evaluation such as that required for example in cognitive radios. In addition, methods how to analyze what are termed below as the “original” frequencies from a folded spectrum have not been explored in the prior art, to inventors' knowledge. These are detailed below.
But prior to describing the various embodiments and aspects of the invention in detail, some general information as to the cognitive radio and its environment are presented at
The ADC and filters detailed below may reside within the receiver portion of the transceiver 10D, within an ASIC 10E such as a RF front end that lies in the position of the transceiver 10D of
The terms “connected,” “coupled,” or any variant thereof, mean any connection or coupling, either direct or indirect, between two or more elements, and may encompass the presence of one or more intermediate elements between two elements that are “connected” or “coupled” together. The coupling or connection between the elements can be physical, logical, or a combination thereof. As employed herein two elements may be considered to be “connected” or “coupled” together by the use of one or more wires, cables and printed electrical connections, as well as by the use of electromagnetic energy, such as electromagnetic energy having wavelengths in the radio frequency region, the microwave region and the optical (both visible and invisible) region, as non-limiting examples.
The PROG 10C is assumed to include program instructions that, when executed by the DP 10A, enable the cognitive radio terminal 10 to operate in accordance with the exemplary embodiments of this invention, as detailed above. Inherent in the DP 10A is a local clock to enable synchronism among the various terminals, which is important in some cognitive radio architectures. The PROG 10C may be embodied in software, firmware and/or hardware, as is appropriate. In general, the exemplary embodiments of this invention may be implemented by computer software stored in the MEM 10B and executable by the DP 10A of the terminal 10, or by hardware (e.g., ASIC 10E or other firmware circuitry), or by a combination (e.g., FPGA 10E) of software and/or firmware and hardware in the terminal 10.
In general, the various embodiments of the terminal 10 can include, but are not limited to, mobile terminals/stations, cellular telephones, personal digital assistants (PDAs) having wireless communication capabilities, portable computers (e.g., laptops) having wireless communication capabilities, image capture devices such as digital cameras having wireless communication capabilities, gaming devices having wireless communication capabilities, music storage and playback appliances having wireless communication capabilities, as well as portable units or terminals that incorporate combinations of such functions and sensor networks.
The MEM 10B may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory. The DP 10A may be of any type suitable to the local technical environment, and may include one or more of general purpose computers, special purpose computers (e.g., the ASIC/FPGA 10E), microprocessors, digital signal processors (DSPs) and processors based on a multi-core processor architecture, as non-limiting examples.
To better understand the embodiments of the invention presented below, the concept of ADC folding is reviewed. When an analog signal, which has high bandwidth, is sampled by a clock signal the spectrum is folded. This happens because the sampled signal can only describe signals that are below the Nyquist frequency (half the sampling frequency, which necessarily depends from the clock signal). Thus, frequencies that are above the Nyquist frequency are folded so that they lie closer to the DC. This concept is shown in
At this point it is important to differentiate between the complex base band signal 28A and a real base band signal 28B. The complex base band signal 28A has the ability to distinguish between the positive and negative frequencies as shown at
Apart from these teachings, one would then expect a straightforward spectrum mapping in which the final stage would be to map the detected spectrum back to the original frequency space using the information about the sampling frequency and the LO frequency. The fourth row 29 of
Respecting the wideband analyzer noted above, traditionally a wideband high-speed ADC covered the necessary band. But as above, in the cognitive radio environment this may not be practical in that power consumption increases with bandwidth, and significantly limiting the bandwidth analyzed is not seen to be productive for the end communications in the cognitive radio networks. According to an embodiment of this invention, the wideband analyzer is implemented by folding the spectrum using the folding property of the ADC, which enables a significant reduction in power consumption as the following example illustrates. Consider the case of a 100 MHz ADC. Folding the spectrum twice can cover a bandwidth of 250 MHz, which would traditionally require an ADC clocked at 500 MHz, so the clock speed difference is 5-fold. However, the folding requires two conversions to be made so the actual speed difference is closer to 2.5-fold in this example. It is known that the dynamic power consumption of digital circuitry is directly proportional to the clock rate. That means that for the above example that the folded topology uses 60% less energy than the traditional wideband implementation.
From the folded spectrum the original frequencies must be determined. Several different techniques are presented. In a first technique to determine the original frequencies from the folded spectrum, the wideband and folded ADC are combined. The wideband spectrum is first analyzed with a wideband high speed ADC. Then the same ADC is changed or re-programmed to a folding mode in which its speed is reduced, and therefore its power is also reduced. Equivalently a second ADC may be used instead of re-programming the wideband ADC, but that implementation is seen as less practical for a cognitive radio apparatus and for power savings some reduction would need to be made to the wideband ADC anyway. The information of the wideband spectrum is then combined to the folded spectrum to evaluate the original frequencies of the folded spectrum. This leads to a net reduction in power consumption since the wideband high speed ADC is used only when something changes significantly. This first technique clearly involves either a highly adjustable wideband ADC or two separate ADCs, each of which increases the integrated circuit IC layout area and cost.
In a second technique to determine the original frequencies from the folded spectrum, a shifted LO signal can be used. If the LO signal is slightly changed (i.e. change the center frequency of the reception band), the signals in the folded spectrum shift differently depending whether they originally belong to an odd or an even folding section.
Looking ahead to
In a third technique to determine the original frequencies from the folded spectrum, a shifted sampling frequency FS is used, and this is illustrated at
Negative side:
Positive side:
Zero:
Adding the sampling frequency difference results in:
Negative side:
Positive side:
Zero:
Picking out the common frequencies results in row 64 of
−20−2Fs=−220 MHz
−20+Fs=80 MHz
−40 MHz
+20 MHz
So from this example we can see that the −220 MHz is a falsely detected frequency (see
As can be seen from the above, a significant advantage of the embodiments of this invention lies in the use of a folding ADC so as to achieve significant power savings, and in some cases also the implementation of the ADC may become simpler due to the lower sampling frequency. As previously shown, folding the spectrum twice results in approximately 60% power savings. The amount of power saving and reliability of the estimation are inversely proportional to each other.
However in the folding, ADC signals from different folding sections are overlapped after the ADC (as previously explained). If the number of input signals is high or if spectrum is folded many times it appears more difficult to differentiate signals from the folding spectrum (i.e. these techniques work best for relatively sparsely occupied spectrum). There exists also a bandwidth problem which concerns the real bandwidths of the expected signals, illustrated at
Consider another example. Assume a first signal 802 with bandwidth of 40 MHz from −20 to +20 MHz as in row 810 of
In general, the various embodiments may be implemented in hardware or special purpose circuits, software (computer readable instructions embodied on a computer readable medium), logic or any combination thereof. For example, some aspects such as the sequence generator may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the invention is not limited thereto. While various aspects of the invention may be illustrated and described as block diagrams, flow charts, or using some other pictorial representation such as
Embodiments of the inventions may be practiced in various components such as integrated circuit modules. The design of integrated circuits ICs is by and large a highly automated process. Complex and powerful software tools are available for converting a logic level design into a semiconductor circuit design ready to be etched and formed on a semiconductor substrate.
Programs, such as those provided by Synopsys, Inc. of Mountain View, Calif. and Cadence Design, of San Jose, Calif. automatically route conductors and locate components on a semiconductor chip using well established rules of design as well as libraries of pre-stored design modules. Once the design for a semiconductor circuit has been completed, the resultant design, in a standardized electronic format (e.g., Opus, GDSII, or the like) may be transmitted to a semiconductor fabrication facility or “fab” for fabrication.
Various modifications and adaptations may become apparent to those skilled in the relevant arts in view of the foregoing description, when read in conjunction with the accompanying drawings. However, any and all modifications of the teachings of this invention will still fall within the scope of the non-limiting embodiments of this invention.
Although described in the context of particular embodiments, it will be apparent to those skilled in the art that a number of modifications and various changes to these teachings may occur. Thus, while the invention has been particularly shown and described with respect to one or more embodiments thereof, it will be understood by those skilled in the art that certain modifications or changes may be made therein without departing from the scope and spirit of the invention as set forth above, or from the scope of the ensuing claims.
