The present invention is directed to communication systems and, more particularly, to systems and methods for estimating channel characteristics in orthogonal frequency-division multiplexing (OFDM) systems with transmitter diversity.
Radio-frequency local area network (LAN) systems are highly regulated by the federal government. For example, the frequency bands of approximately 5.15-5.25 GHz, 5.25-5.35 GHz, and 5.725-5.825 GHz unlicensed national information structure (U-NII) bands are regulated by Title 47, Section 15.407 of the United States Code of Federal Regulations (CFR). While the CFR specifies certain limitations on the use of radio-frequency networks, other standards committees, such as the Institute of Electrical and Electronics Engineers (IEEE), specify technical requirements for wireless systems to ensure cross-compatibility of wireless systems from different manufacturers. For example, the IEEE “Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: High-Speed Physical Layer in the 5 GHz Band” (hereinafter “the IEEE 5 GHz standard”) provides several requirements for systems operating in the 5 GHz band.
One of the requirements set forth in the IEEE 5 GHz standard is an OFDM physical layer convergence procedure (PLCP) sub-layer. Specifically,
The short-training period 110 contains ten symbols (e.g., t1, t2 . . . t9, t10), which are used for signal detecting, coarse-frequency acquisition, diversity selection, and other functions as defined by the IEEE 5 GHz standard. Since the short-training period 110 is described in detail in the IEEE 5 GHz standard, further discussion of the short-training period 110 is omitted here.
The long-training period 120 contains a guard interval (GI2) and two long-training symbols, T1 and T2. As specified in the IEEE 5 GHz standard, each of the long-training symbol T1 and T2 consists of 53 sub-carriers including a zero value at DC, which are modulated by elements of sequence X, given by:
Additionally, the IEEE 5 GHz standard requires that the long-training symbols be generated according to:
where x(t) is a time-domain representation of the long training symbol; w(t) is a weighting factor for the purpose of spectral shaping; k is a sub-carrier index; X(k) is a coefficient of the training symbol as defined by Eq. 1; and TG/2 is the guard interval, which is defined by the IEEE 5 GHz standard as 1.6 μs.
In addition to specifying the content of the long-training symbols according to Eq. 2, the IEEE 5 GHz standard further requires that the number of long-training symbols be two (e.g., T1 and T2), thereby improving the accuracy of channel estimation.
The IEEE 5 GHz standard further dictates that the first long training symbol T1 be identical to the second long training symbol T2. Thus, designating the identical long-training symbols as X, the first long-training symbol X 155 and the second long-training symbol X 165 are transmitted consecutively during the long-training period 120. Hence, for a two-branch transmitter-diversity OFDM system as shown in
Similarly, a second transmitter 265 transmits:
The transmitted signals are received at a receiver 205 as a function of the transmitted symbol and the channel characteristics. After removing the guard interval, each received symbol is inverse Fourier transformed. Thus, for a two-branch transmitter-diversity OFDM system as shown in
Y1=(HA·X)+(H9·X)+Z1 [Eq. 3].
where Z1 represents the received noise, the channel characteristics HA and HB are presumed to be time-invariant during the frame duration, and the propagation delay over these two channels are presumed to be substantially the same. Since the same long-training symbol X is transmitted from both branches of the two-branch transmitter-diversity system, Eq. 3 simplifies to:
Y1=(HA+HB)·X+Z2 [Eq. 4].
Similarly, the subsequent received data blocks are represented by:
Y2=(HA+HB)·X+Z2 [Eq. 5],
Y3=(HA+HB)·S+Z3 [Eq. 6],
Y4=HA·DAI+HB·DBI+Z4 [Eq. 7],
and:
Y5=HA·DA2+HB·DB2+Z5 [Eq. 8].
Eqs. 4 and 5, in the aggregate, result in:
(Y1+Y2)·X*=(HA+HB)(2|X|2)+(Z1+Z2)·X* [Eq. 9],
which may be re-written as:
or, more specifically, as:
where N represents the number of OFDM sub-carriers, and k represents the sub-carrier index
Since, as shown in Eq. 1, X(k)∈{±1} for all k, the complex coefficient X*(k) of the transmitted symbol X(k) will be equal to the transmitted symbol X(k). Furthermore, since X(k)∈{±1}, the square norm |X(k)|2 of the transmitted symbol X(k) will be 1. Additionally, since X(k)∈{±1}, the statistics of (Z1(k)+Z2(k))X(k), without loss of generality, is the same as that of (Z1(k)+Z2(k)).
By omitting the noise terms, the aggregate effect of both channels HC=HA+HB can be estimated by:
While Eq. 11 provides an avenue for calculating the combined channel characteristics for HC, it is evident that the duplicative transmission of X provides very little assistance in distinguishing channel characteristics of the individual channels HA and HB. In other words, because two branches HA and HB are used for transmitting a single X, a classic one-equation two-unknown system is presented in which only the aggregate characteristics HC may be calculated to any degree of certainty. Furthermore, while the duplicative transmission of X increases the signal-to-noise ratio (SNR), the increase in SNR provides little help in resolving the characteristics of each individual channel.
Although complex algorithms exist to segregate the individual channel effects from the aggregate channel effect, these algorithms make additional presumptions about the channels in order to properly estimate the characteristics of each channel. Thus, these channel estimation algorithms are only as good as their initial presumptions. Furthermore, due to the complexity of these channel estimation algorithms, when the two-branch transmitter-diversity system is expanded to multiple-branches (e.g., three-branch, four-branch, etc.), the complexity of calculations increases exponentially.
Thus, a heretofore-unaddressed need exists in the industry to address the aforementioned deficiencies and inadequacies.
The present invention is directed to systems and methods for estimating channel characteristics in OFDM environments with transmitter diversity.
Briefly described, in architecture, one embodiment of the system comprises logic components that are adapted to transmit a training symbol over a first channel during a first period; transmit the training symbol over a second channel during the first period; transmit a complex conjugate of the training symbol over the first channel during a second period; and transmit a negative complex conjugate of the training symbol over the second channel during the second period.
The present disclosure also provides methods for estimating channel characteristics in OFDM environments with transmitter diversity.
In this regard, one embodiment of the method comprises the steps of transmitting a training symbol over a first channel during a first period; transmitting the training symbol over a second channel during the first period; transmitting a complex conjugate of the training symbol over the first channel during a second period; and transmitting a negative complex conjugate of the training symbol over the second channel during the second period.
Other systems, methods, features, and advantages will be or become apparent to one with skill in the art upon examination of the following drawings and detailed description. It is intended that all such additional systems, methods, features, and advantages be included within this description.
Many aspects of the disclosure can be better understood with reference to the following drawings. The components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Moreover, in the drawings, like reference numerals designate corresponding parts throughout the several views.
Reference is now made in detail to the description of the embodiments as illustrated in the drawings. While several embodiments are described in connection with these drawings, there is no intent to limit the invention to the embodiment or embodiments disclosed herein. On the contrary, the intent is to cover all alternatives, modifications, and equivalents.
Several embodiments of the invention are described below, in which additional training symbols may be used to further estimate channel characteristics. Thus, unlike prior systems and methods, which required enormous processing power or additional presumptions about a multi-branch transmitter-diversity system, the embodiments below provide for simpler calculations and fewer presumptions in characterizing multi-branch transmitter-diversity systems.
Thus, as shown in
The duplicative transmission of X is followed by transmission of signaling information S 370a during the signaling period 330. Upon transmitting the signaling information S 370a, a complex conjugate X* 385a of the long-training symbol is transmitted during a first data period 340. Since, as described above, each element in X is real, it is axiomatic that each element in X* is also real. Additionally, since each element in X is real, it is also axiomatic that X* is identical to X. It should, however, be understood that, outside of the context of the IEEE 5 GHz standard, X need not be wholly real-valued, and that X may contain complex numbers having imaginary components.
Similarly, as shown in
As described here, rather than merely duplicating the transmission of X, the system of
Thus, if the first transmitter 460 and second transmitter 465 transmits X (i.e., inverse Fourier transforms X to generate a time domain signal x, adds a cyclic prefix to generate xcp, converts xcp to a radio-frequency (RF) analog signal XRF by an RF module, and radiates xRF at the transmit antenna), then the received symbol Y1 is represented in the frequency domain by:
Y1=(HA·X)+(HB·X)+Z1 [Eq. 12].
where Z1 represents the noise for first received symbol. Since the same training symbol X is transmitted from both branches of the two-branch transmitter-diversity system, Eq. 12 may be simplified to:
Y1=(HA+HB)·X+Z1 [Eq. 13].
Similarly, since the same training symbol is transmitted again, the second transmission from the two transmitters 460, 465 may be seen as:
Y2=(HA+HB)·X+Z2 [Eq. 14].
Also, if signaling information 370a is transmitted as a third transmitted symbol T3, then:
Y3=(HA+HB)·S+Z3 [Eq. 15],
where S represents the frequency-domain signaling information. In one embodiment, upon transmitting the signaling information S, the complex conjugate X* 385a of the long-training symbol is transmitted from the first transmitter 460 as the fourth symbol T4, and a negative complex conjugate −X* is transmitted from the second transmitter 465 as the fourth symbol T4. As described above, since X is real, both the complex conjugate X* and the negative complex conjugate −X* are real. Additionally, since X is real:
X*=X [Eq. 16],
−X*=−X [Eq. 17],
and:
|X(k)|2=1 [Eq. 18].
Thus, in the context of the IEEE 5 GHz standard, the fourth received symbol may be represented as:
Y4=(HA·X)+(HB·(−X))+Z4 [Eq. 19],
or simply:
Y4=(HA−HB)·X+Z4 [Eq. 20].
Combining Eqs. 13 and 20 provides an approach in which HA and HB may be isolated. In other words, unlike prior-art approaches in which an aggregate effect HC=HA+HB of the channels is calculated, individual channel characteristics of HA and HB may be calculated since:
It should be appreciated that each item in Eq. 21 is a frequency domain representation of an OFDM symbol. From the perspective of the sub-carrier, Eq. 21 may be rewritten as:
(Y1(k)+Y4(k))·X(k)*=2HA(k)·|X(k)|2+(Z1(k)+Z2(k))·X*(k),k=1, N [Eq. 22],
where N represents the number of OFDM sub-carriers, and k represents the sub-carrier index.
The channel transfer function HA (k) may be obtained by:
Thus, based on Eq. 23, HA can be estimated as:
or, more simply:
It should be appreciated that an estimation error proportional to the noise term (Z1+Z4)X/2 is inherent in Eqs. 24 and 25. Generally, the mean of the estimation error is equal to E(Z1+Z4)/2=0, where E represents the statistical-expected-value function. Correspondingly, the variance of the estimation error is equal to var ((Z1+Z4)X/2)=var((Z1+Z4)/2)=var((Z1+Z4)/2)=σZ2/2, where var() represents the statistical-variance function, and Z1 and Z4 are presumed to have variance σz2.
The characteristics of the second channel HB may similarly be obtained using:
or, more simply:
or:
Therefore, HB may be estimated as:
Similar to Eqs. 24 and 25, an estimation error proportional to the noise term (Z1−Z4)X/2 is inherent in Eqs. 28 and 29. Thus, the mean of the estimation error is equal to E((Z1−Z4)X/2)=0, and the variance of the estimation error is equal to var((Z1−Z4)X/2)=var((Z1−Z4)/2)=σZ2/2.
Thus, as seen from Eqs. 12 through 29, each individual channel may be accurately characterized by transmitting X and −X* during one of the data periods. Hence, rather than merely characterizing the aggregate of the channels, estimates of each individual channel may be derived from the approach outlined above.
In another embodiment, greater signal integrity and lower estimation error may be achieved by combining Eqs. 13, 14, and 20. Since Eqs. 13 and 14 represent duplicative transmissions of the same training symbol X, combining Eqs. 13 and 14 may be seen as a further signal averaging. Thus, by exploiting the SNR improvement gained by the duplicative transmission of the training symbol X, the channels may be isolated according to:
(Y1+Y2+2Y4)X*=4 HA·|X|2+(Z1+Z2+2Z4)·X* [Eq. 30],
and:
or, equivalently:
Therefore, HA can be estimated by:
Thus, unlike Eqs. 24, 25, 28, and 29, the estimation error induced by the noise term for Eq. 32 is (Z1+Z2+2Z4)X/4. Here, the mean of the estimation error is equal to E((Z1+Z2+2Z4)X/4)=0, and the variance of the estimation error is equal to var((Z1+Z2+2Z4)X/4)=var((Z1+Z2+2Z4)/4)=3σZ2/8, where Z1, Z2, and Z4 are assumed to have variance σz2.
As seen from Eq. 32, the variance of the estimation error is reduced, thereby improving the accuracy of estimation. Similarly, the characteristics of the second channel HB may be obtained by:
thereby resulting in the mean of the estimation error being equal to E((Z1+Z2−2Z4)X/4)=0, and the variance of the estimation error being equal to var((Z1+Z2−2Z4)X/4)=var((Z1+Z2−2Z4)/4)=3σZ2/8, where Z1, Z2, and Z4 are assumed to have variance of σZ2/8, where Z1, Z2, and Z4 are assumed to have variance of σz2.
In a more general sense, the variance of the estimation error can be further reduced with the transmission of additional long training symbols X or the transmission of additional complex conjugates X* and negative complex conjugates −X* of the long training symbol X.
While multiple-branch transmitter-diversity systems have been shown above, another embodiment of the invention may be seen as a method for estimating channel characteristics. Embodiments of such a method is shown in
If the channel estimation is performed in accordance with the IEEE 5 GHz standard, then the first period is one of the long-training periods in the preamble of the physical layer convergence procedure (PLCP), and the second period is one of the subsequent data periods.
As seen from
Although exemplary embodiments have been shown and described, it will be clear to those of ordinary skill in the art that a number of changes, modifications, or alterations to the invention as described may be made. For example, while a two-branch transmitter-diversity system has been shown for purposes of illustration, it will be clear to one of ordinary skill in the art that the disclosed approach may be extended to multiple-branch transmitter-diversity systems having three, four, or more branches. Additionally, while
This application claims the benefit of U.S. provisional patent application serial No. 60/400,888, filed Aug. 1, 2002, which is incorporated herein by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
5303263 | Shoji et al. | Apr 1994 | A |
5481572 | Skold et al. | Jan 1996 | A |
6185258 | Alamouti et al. | Feb 2001 | B1 |
6449314 | Dabak et al. | Sep 2002 | B1 |
6507604 | Kuo | Jan 2003 | B1 |
6611551 | Jones et al. | Aug 2003 | B1 |
6707856 | Gardner et al. | Mar 2004 | B1 |
6775329 | Alamouti et al. | Aug 2004 | B2 |
6850481 | Wu et al. | Feb 2005 | B2 |
6885708 | Thomas et al. | Apr 2005 | B2 |
6959047 | Al-Dhahir et al. | Oct 2005 | B1 |
7120200 | Alamouti et al. | Oct 2006 | B2 |
20020044524 | Laroia et al. | Apr 2002 | A1 |
20030072452 | Mody et al. | Apr 2003 | A1 |
20030128751 | Vandenameele-Lepla | Jul 2003 | A1 |
20040005010 | He et al. | Jan 2004 | A1 |
Number | Date | Country | |
---|---|---|---|
20040022174 A1 | Feb 2004 | US |
Number | Date | Country | |
---|---|---|---|
60400888 | Aug 2002 | US |