Abstract:
The present invention relates to use of a smart antenna for a RF reader on a Radio Frequency Identification (RFID) system to significantly increase the operating range of the RFID system. The smart antenna can be an adaptive antenna array. The smart antenna comprises a plurality of antenna elements and, by combining the signals from multiple antenna elements, significantly increases the received signal-to-noise ratio. In a noise limited environment, combining the signals to maximize the received signal-to-noise ratio can be based on the maximal ratio combining (MRC) principle. To achieve the best signal quality, the received signal from each antenna can be phase-shifted such that the resultant signals from all antennas are in phase. In addition, the signal from each antenna can be scaled in amplitude based on the square root of its received signal-to-noise ratio.

Description:
CROSS REFERENCE TO RELATED APPLICATION 
   This application claims the benefit of U.S. Provisional Patent Application No. 60/528,349 filed Dec. 10, 2003 the entirety of which is hereby incorporated by reference into this application. 

   BACKGROUND OF THE INVENTION 
   1. Field of the Invention 
   This invention relates generally to a Radio Frequency Identification (RFID) system. More particularly, it relates to an adaptive antenna array for a RF reader for increasing the operating range of the RFID system. 
   2. Description of Related Art 
   A conventional Radio Frequency Identification (RFID) system consists of a reader and a plurality of RF tags. The RF reader transmits a radio signal containing a unique identification (ID) to poll one of a plurality of RF tags. The RF tag polled responds by sending back a radio signal. A variety of RFID systems have been used in different applications such as warehouse inventory control systems. 
   There are two types of conventional RFID systems: active and passive. The RF tag in the active RFID system requires power to operate. For the battery-powered active RF tag, it is desirable to have reduced power consumption so that the operating life can be extended. The RF tag in the passive RFID system derives and stores power from a RF signal transmitted by the RF reader and responds by transmitting back a signal by using the stored energy. Conventional RFID systems are limited to short range operation because of limited transmission power available on the return link from the RF tag to the RF reader. RFID systems typically contain a small number of RF readers and a large number of RF tags. The RF tags typically have limited complexity and low cost. Accordingly, the majority of the complex signal processing and the associated implementation are at the RF reader side. It is desirable to increase the operating range of the RFID system. 
   SUMMARY OF THE INVENTION 
   The present invention relates to use of a smart antenna for a RF reader on a Radio Frequency Identification (RFID) system to significantly increase the operating range of the RFID system. The smart antenna can be an adaptive antenna array. The smart antenna comprises a plurality of antenna elements and, by combining the signals from multiple antenna elements, significantly increases the received signal-to-noise ratio. In a noise limited environment, combining the signals to maximize the received signal-to-noise ratio can be based on the maximal ratio combining (MRC) principle. To achieve the best signal quality, the received signal from each antenna can be phase-shifted such that the resultant signals from all antennas are in phase. In addition, the signal from each antenna can be scaled in amplitude based on the square root of its received signal-to-noise ratio. 
   The invention will be more fully described by reference to the following drawings. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  is a schematic diagram of a RFID system with a smart antenna in accordance with the teachings of the present invention. 
       FIG. 2  is a schematic diagram of an implementation of smart antenna processing. 
       FIG. 3  is a schematic diagram of an implementation of a beamforming module which can be used in the smart antenna processing. 
       FIG. 4  is a schematic diagram of an implementation of smart antenna processing including a closed loop MRC implementation with antenna weight magnitude control. 
   

   DETAILED DESCRIPTION 
   Reference will now be made in greater detail to a preferred embodiment of the invention, an example of which is illustrated in the accompanying drawings. Wherever possible, the same reference numerals will be used throughout the drawings and the description to refer to the same or like parts. 
     FIG. 1  is a schematic diagram of Radio Frequency Identification (RFID) system  10  in accordance with the teachings of the present invention. 
   RFID reader  12  transmits and receives signals  11  to and from RFID tags  13 . RFID reader  12  includes smart antenna processing module  20  for adaptively combining signals from a plurality of antennas  21   a – 21   d . Smart antenna processing module  20  is connected by transmit receive switches  16   a – 16   d  and bandpass filters  14   a – 14   d  to antennas  21   a – 21   d . Smart antenna processing module  20  can combine signals  11  to maximize the received signal-to-noise ratio (SNR) based weights determined by maximal ratio combining (MRC). 
   There are various ways to determine the MRC weights. One embodiment adaptively adjusts the antenna weight by correlating each of the received signals with a combined signal as the received signal arrives. The correlation time determines the post-detection SNR of the weight computation. Increasing the correlation time allows optimal antenna weights to be achieved in very low signal-to-noise ratio environments. The signal-to-noise ratio improvements come from both the antenna combining gain and the diversity gain. With the MRC antenna weights, the received signals from different antennas can be coherently combined (i.e., in phase) while uncorrelated noise from different antennas is combined incoherently. As a result, the signal-to-noise ratio after the combining is increased. Additionally, the signals received by some antennas could experience fading, in which the signal strength could be reduced significantly. Combining signals from all the antennas reduces the probability of the signal fading in the output signal and thereby achieves diversity gain. For example, in 802.11b with a 2 element antenna array, 8 to 9 dB of SNR gain can be achieved in a Rayleigh fading environment. With a 4 element antenna array, 12 to 14 dB of SNR gain can be achieved in a Rayleigh fading environment. 
     FIG. 2  shows an embodiment of smart antenna processing module  20  employing a closed loop adaptive signal processing operation for antenna weight computation and signal combining. A plurality of antennas  21   a – 21   d  may receive or transmit signals  11 . The BPF and T/R switches from  FIG. 1  can also be used. Signals  11  are amplified in amplifiers  22   a–d . The outputs of amplifiers  22   a–d  are downconverted in respective downconverters  23   a–d . Each of downconverters  23   a–d  multiplies the output of respective amplifiers  22   a–d  by a local oscillator in-phase signal (LOI) and a local oscillator quadrature phase signal (LOQ) in respective multipliers  24   a–b . It will be appreciated that various numbers of antennas and processing elements could be used in accordance with the teachings of the present invention. 
   The resultant signals are applied to respective low-pass filters (LPF)  25   a ,  25   b  in automatic gain control (AGC) loop  26  that normalizes the signal level before the MRC algorithm. AGC loop  26  provides a consistent performance for smart antenna processing module  20  at different input signal levels. Variable gain amplifiers  28   a ,  28   b  are applied to the respective outputs of LPF  25   a ,  25   b  and MRC beamforming module  30 . At the output of the variable gain amplifiers  28   a ,  28   b , power detectors  27   a–d  are applied to sum the signal power of all antennas and compare the signal power to a threshold value. The difference between the signal power of all antennas and the threshold value can be integrated to maintain the signal level after AGC loop  26  at the same level and can be used to adjust the gain of variable gain amplifiers  28   a ,  28   b . Accordingly, in this implementation, the MRC algorithm is able to work at different input signal levels. 
   MRC beamforming module  30  performs real time adaptive signal processing to obtain the maximum signal-to-noise ratio. In an implementation of MRC beamforming module  30  the antenna weights are used to align the phases of the four antenna signals received from antennas  21   a–d  and also scale the signal in proportion to the square-root of the signal-to-noise ratio in each individual channel. For example, in one implementation, the signal envelope is used as an approximation to scale the signal in proportion to the square-root of the signal-to-noise ratio in each individual channel. This approximation is accurate assuming the noise is the same in each channel and the SNR is high enough to be approximated accurately by the signal plus noise in each channel. 
   MRC beamforming module  30  can employ a Cartesian feedback loop, as shown in  FIG. 3 . MRC beamforming module  30  provides baseband processing which performs complex conjugate multiplication of the output of a baseband I and Q channel filter with a baseband reference I and Q channel as follows:
 
 I _ERROR i   =I   i   *I   s   +Q   i   *Q   s 
 
 Q _ERROR i   =I   i   *Q   s   −Q   i   *I   s 
 
   The resultant signal (I_ERROR i , Q_ERROR i ) at the output of MRC beamforming module  30  is a complex signal with phase equal to the difference of the reference complex signal and the individual signal and an envelope proportional to the envelope of the individual signal. Signal I_ERROR is applied to low-pass filter (LPF)  32   a  and signal Q_ERROR is applied to low-pass filter (LPF)  32   b . The output of the LPF&#39;s  32   a ,  32   b  is antenna weight  33  (IWi, QWi, i=1,2,3, . . . ). The antenna weights and combining are performed at an RF frequency. 
   The outputs of amplifiers  22   a–d  are applied to respective modulators  34   a–d  and are each multiplied by antenna weight  33 . Accordingly, the antenna weight is implemented using a modulator in which the baseband control signals are used to create phase shift and amplitude scaling in the signal without the use of a phase shifter and variable gain amplifier. The outputs of modulators  34   a–d  are combined in summer  35  to generate combined output signal  36 . The combined signal  36  is forwarded to receiver  37 . 
   Combined signal  36  is applied to downconverter  38  and is multiplied by LOI and LOQ in respective multipliers  39   a ,  39   b . The resultant signals are applied to low-pass filters (LPF)  40   a ,  40   b . The outputs from the low-pass filters (LPF)  40   a ,  40   b  are amplified with quadrature phase signal amplifiers  41   a ,  41   b  and are applied to MRC beamforming module  30  to be used for updating antenna weight  33 , as described above. 
   It has been found that if the antenna weight setting produces a combined signal which is small in magnitude, the antenna weight thus derived can be small in magnitude, leading to a smaller set of weights. The combined signal thus derived can become small and be indistinguishable from circuit noise. The receiver noise figure degrades significantly. Also, if the initial weight produces a combined signal which is large in magnitude, the antenna weight thus derived leads to a set of large weights resulting in a larger combined signal which can saturate the circuit to generate the antenna weight and the RF modulator. Accordingly, it is desirable to provide an algorithm to maintain the antenna weight magnitude control. As shown in  FIG. 4 , antenna weight magnitude control loop  42  monitors the power in the combined signal. If the magnitude of the weight is small, the power of the combined signal is small. Alternatively, if the magnitude of the weight is large, the power of the combined signal is large. Power detector  43  of antenna weight magnitude control loop  42  compares the power of combined signal  36  with a threshold level. The difference between the power of combined signal  36  and the threshold level is filtered with low-pass filter (LPF)  44 . The filtered output is fed forward through limiter  48  to variable gain amplifiers  46   a ,  46   b  to adjust the magnitude of the combined signal. The outputs of variable gain amplifiers  46   a ,  46   b  are used in correlators  47  of the MRC beamforming module  30  to derive the antenna weights (IW i , QW i , i=1,2,3 . . . )  33 . A higher gain in variable gain amplifiers  46   a ,  46   b  produces a larger antenna weight and a lower gain in variable amplifiers  46   a ,  46   b  produces a smaller antenna weight. By varying the gain of variable gain amplifiers  46   a ,  46   b  in the baseband SUM channel signal paths, the magnitude of the antenna weight is adjusted to a proper level to keep the output signal power in a small range. 
   To achieve a fast beamforming operation, the LPF bandwidth and the bandwidth of the antenna weight magnitude control loop  42  should be wide. Wider loop bandwidth can lead to excessive fluctuations in the antenna weights. Limiter  48  is used to limit antenna weight fluctuations. Limiter  48  reduces weight fluctuation while maintaining a wide loop bandwidth in the antenna weight magnitude control loop  42 . 
   Conventional RFIDs generally work by modulating the signal transmitted by the RFID reader and transmitting the modulated signal back to the RFID reader. Thus, the reader may simultaneously receive the RFID reader transmitted signal and the signal from the RFID. The reader must then suppress the RFID reader transmitted signal both in the RFID reader output, as well as in the weight generation circuitry. Since the RFID reader transmitted signal is generally orders of magnitude stronger than the signal from the RFID, this can be a significant issue. This suppression can be done using a variety of techniques, including a) filtering, b) the use of a power inversion algorithm in the smart antenna, c) signal cancellation, and d) a combination of a), b), and c). For example, for b), in  FIG. 2 , the beamforming algorithm used in beamforming module  30  could be power inversion, rather than as shown in  FIG. 3 . For example, a power inversion algorithm which can be used is described in U.S. Pat. No. 6,784,831, hereby incorporated by reference into this application. 
   It is to be understood that the above-described embodiments are illustrative of only a few of the many possible specific embodiments, which can represent applications of the principles of the invention. Numerous and varied other arrangements can be readily devised in accordance with these principles by those skilled in the art without departing from the spirit and scope of the invention.