The invention relates generally to wireless communications systems, and more particularly, to managing the precoding of wireless transmissions in a multi-user wireless communications network.
The 3rd Generation Partnership Project (3GPP) was established to produce globally applicable technical specifications and technical reports for a 3rd generation mobile system based on evolved Global System for Mobile communications (GSM) core networks and the radio access technologies that they support (i.e., Universal Terrestrial Radio Access (UTRA) in both Frequency Division Duplex (FDD) and Time Division Duplex (TDD) modes). The scope was subsequently amended to include the maintenance and development of the GSM technical specifications and technical reports including evolved radio access technologies (e.g., General Packet Radio Service (GPRS) and Enhanced Data rates for GSM Evolution (EDGE)). 3GPP Long Term Evolution (LTE) is a project within the 3GPP to improve the Universal Mobile Telecommunication System (UMTS) mobile phone standard.
In wireless communications systems such as the systems being standardized through the 3GPP, precoding is used to improve channel quality and throughput. Conventional precoding typically relies on channel estimations that are made using recently received information (e.g., recently received pilot symbols). Although the channel estimations may accurately reflect the actual past channel responses, the channel estimations are backward-looking only. Because transmission conditions tend to vary over time, subsequent transmissions may exhibit different channel responses, which in turn may limit or negate the benefits of precoding.
In accordance with an embodiment of the invention, instead of precoding directly from channel estimations, previously generated channel estimations are used to predict future channel estimations, and the precoding is accomplished in response to the predicted future channel estimations instead of directly from the previously generated channel estimation. Because precoding is accomplished in response to a prediction about future channel estimations instead of directly from the previously generated channel estimations, which reflect past channel conditions, the precoding can be better matched to conditions that will be experienced in subsequent transmissions.
In an embodiment, a method for operating a wireless communications system that supports multi-user multiple-input multiple-output (MU-MIMO) communications between a base station and multiple mobile stations involves generating a channel estimation, predicting a future channel estimation from the channel estimation, precoding data in response to the predicted future channel estimation, and transmitting the precoded data.
In another embodiment, a base station that supports MU-MIMO communications between the base station and multiple mobile stations includes a channel estimator configured to generate a channel estimation from received symbols, a channel estimation predictor configured to predict a future channel estimation from the channel estimation, a precoder configured to precode data in response to the predicted future channel estimation, and a transmitter configured to transmit the precoded data.
In another embodiment, a mobile station that supports MU-MIMO communications between a base station and the mobile station includes a channel estimator configured to generate a channel estimation from received symbols, a channel estimation predictor configured to predict a future channel estimation from the channel estimation, a precoding scheme selector configured to select a precoding scheme in response to the predicted future channel estimation, and a transmitter configured to transmit an indication of the precoding scheme to a base station.
Other aspects and advantages of the present invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, illustrating by way of example the principles of the invention.
Throughout the description, similar reference numbers may be used to identify similar elements.
Multi-user multiple-input multiple-output (MU-MIMO) is an advanced spatial multiplexing technique for wireless transmission.
In the embodiment of
Two categories of precoding include codebook based precoding and non-codebook based precoding. An embodiment of the invention that is applicable to codebook based precoding is described below with reference to
Codebook Based Precoding
Codebook based precoding is a technique that enables precoding information to be efficiently sent in a wireless communication, typically in the uplink direction from a UE to an eNB. The technique involves establishing a codebook that includes a set of precoding matrices, with each precoding matrix in the set being uniquely identifiable by a codebook index. In operation, a transmitter (e.g., the eNB 102) transmits data such as pilot symbols to a receiver (e.g., a UE 104). The UE uses the pilot symbols to generate a channel estimation and the channel estimation is used by the receiver to select one of the precoding matrices from the set of precoding matrices. Typically, the precoding matrix that maximizes the channel throughput is selected. Once a precoding matrix is selected, the corresponding codebook index is transmitted back to the eNB and the eNB uses the selected precoding matrix to precode subsequent downlink transmissions. The UE may also generate channel quality information, for example, as channel quality indicators (CQIs), and provide the CQIs to the eNB along with the codebook indexes. The codebook index(s) and CQIs are then used by the eNB to establish a precoding scheme.
An exemplary codebook based precoding scheme is referred to as the Per-User Unitary Rate Control (PU2RC) scheme. In a PU2RC scheme that operates in a MIMO system with M transmit antennas at the eNB, a set of precoding matrices, i.e. codebook E={E(0) . . . E(G-1)}, is adopted. Given the set of precoding matrices, the gth precoding matrix can be expressed as: E(g)=[e0(g) . . . eM-1(g)], and em(g) is the mth precoding vector in the set of precoding matrices.
In operation, each UE 104 generates a channel estimation and calculates a CQI value for each vector in each matrix in the set E. Each UE also selects a preferred precoding matrix, which can be identified by a codebook index. The codebook index and the CQIs are then fed back to the eNB 102. The eNB gathers the feedback information, which indicates the index of a preferred precoding matrix and the CQIs for all the precoding vectors in the matrix. The eNB then groups the UEs that identify the same preferred precoding matrix, and selects a group with the highest group priority among the different groups. At the same time, inside the selected precoding group, the eNB allocates each precoding vector to the user with the highest priority. Finally, the eNB establishes a precoding scheme that corresponds to the selected group.
In an embodiment, the precoding vectors in one precoding matrix can be assigned to multiple users or multiple streams of the same user. In another embodiment, the precoding matrix can be set to a unitary matrix, which can mitigate the interference between the different transmit antennas because of the orthogonality between the different precoding vectors in the precoding matrix.
In accordance with an embodiment of the invention, when using codebook based precoding, the channel estimation that is made at a particular UE is used to predict a future channel estimation and the predicted future channel estimation, instead of the previously generated channel estimation, is used to select a precoding matrix and to calculate CQIs.
Operation of the system is now described in more detail with reference to
ym,n,k=smhm,n,k+ηm,n,k (1)
where ηm,n,k is the noise. Generating a channel estimation involves finding the value of hm,n,k The basic process for finding the value of hm,n,k involves multiplying ym,n,k by (smsm*)−1sm*, where the superscript * and −1 represent conjugation and inverse, respectively. This process can be expressed as:
ĥm,n,k=(smsm*)−1sm*ym,n,k (2)
In an embodiment, a channel estimation for the kth UE is expressed in a channel response matrix as:
The SNR of each precoding vector is calculated as the follows:
where ek is the precoding vector and σk2 is the mean of the noise variance. The CQI is obtained from the value of SNR.
Referring again to
Non-adaptive filtering utilizes real-time information about the wireless propagation channel to update filter coefficients. An example of a non-adaptive prediction filter is described with reference to
Referring to
In an embodiment, the filter coefficients, wi, can be obtained using the Wiener-Hopf equation:
w1=R−1p (6)
where R is the expectation mean of the auto-correlation matrix of vector ĥm,n,k=[ĥm,n,k(t−1), ĥm,n,k(t−2), . . . , ĥm,n,k(t−Δ)] and p is the expectation of the cross correlation between ĥm,n,k and the desired response ĥm,n,k(t−1). Although one filtering technique for predicting a future channel estimate is described with reference to
Once the channel estimation predictor 130 generates a predicted future channel estimation, the predicted future channel estimation is provided to the channel feedback module 132. The precoding matrix selector 134 of the channel feedback module uses the predicted future channel estimation to select a precoding matrix and to identify the corresponding codebook index. The CQI calculator 136 of the channel feedback module uses the predicted future channel estimation to calculate CQIs for the UE 104. Precoding matrix information (e.g., in the form of the corresponding codebook index) and the CQIs are then transmitted uplink to the eNB 102 for use in precoding.
Non-Codebook Based Precoding
As mentioned above, another embodiment of the invention involves using predicted future channel estimates in a system that utilizes non-codebook based precoding. Non-codebook based precoding involves generating precoding matrices directly from the channel estimations. One non-codebook based technique for precoding utilizes singular value decomposition (SVD) to generate precoding matrices from channel estimations. In an embodiment, assuming M transmit antennas and N receive antennas, a channel estimation, as represented by the channel response matrix for the kth UE, can be expressed as:
The singular value decomposition of the channel response matrix is expressed as:
Hk=UkΛkVkH (8)
where, Uk will be adopted in the receiving processing, i.e., as:
In accordance with an embodiment of the invention, channel estimates are used to generate predicted future channel estimations and the predicted future channel estimations, instead of the previously generated channel estimations, are used in an SVD operation to generate precoding matrices.
In operation, the channel estimator 158 generates channel estimations from the information received via an uplink channel. For example, the channel estimator uses known techniques to generate channel estimations. The channel estimations are provided to the channel estimation predictor 160, which uses the channel estimations to predict future channel estimations. As described above, the channel estimation predictor may utilize, for example, adaptive or non-adaptive filtering techniques to generate the predicted future channel estimations. The predicted future channel estimations generated by the channel estimation predictor are then provided to the SVD module 162 for use in singular value decomposition. The SVD module generates precoding matrices, e.g., precoding matrices V1-VK, directly from the predicted future channel estimations and the precoding matrices are used by the precoder 110 to precode subsequent downlink transmissions. The above-described technique takes advantage of channel reciprocity between the eNB and UEs in the TDD wireless communications system, wherein channel reciprocity involves essentially equivalent channel responses in the uplink and downlink directions.
Although specific embodiments of the invention have been described and illustrated, the invention is not to be limited to the specific forms or arrangements of parts as described and illustrated herein. The invention is limited only by the claims.
Number | Date | Country | Kind |
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2007 1 0181175 | Oct 2007 | CN | national |
Filing Document | Filing Date | Country | Kind | 371c Date |
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PCT/IB2008/054185 | 10/10/2008 | WO | 00 | 5/3/2010 |
Publishing Document | Publishing Date | Country | Kind |
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WO2009/047739 | 4/16/2009 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
20040157567 | Jootar et al. | Aug 2004 | A1 |
20050227697 | Borst et al. | Oct 2005 | A1 |
20060034165 | Levy | Feb 2006 | A1 |
20070191066 | Khojastepour et al. | Aug 2007 | A1 |
20070201575 | Ariyavisitakul et al. | Aug 2007 | A1 |
20070254597 | Li et al. | Nov 2007 | A1 |
20070254602 | Li et al. | Nov 2007 | A1 |
Number | Date | Country |
---|---|---|
1 816 758 | Aug 2007 | EP |
2004042982 | May 2004 | WO |
Entry |
---|
Zhou, Q., et al “Joint Tomlinson-Harashima Precoding and Scheduling for Multiuser MIMO with Imperfect Feedback”; IEEE Wireless Communications and Networking Conference, pp. 1233-1238 (Apr. 2006). |
Castro, P., et al “Adaptive Precoding In MIMO Wireless Communication Systems Using Blind Channel Prediction Over Frequency Selective Fading Channels”; IEEE/Sp 13th Workshop on Statistical Signal Processing, pp. 173-178 (Jul. 2005). |
Spiteri, S., et al; “Prediction for Time-Varying SVD Systems”; 15th IEEE Intl. Symposium on Personal, Indoor and Mobile Radio Communications, vol. 3, pp. 1608-1612 (Sep. 2004). |
Nguyen, H., et al. “Prediction of the Eigenvectors for Spatial Multiplexing MIMO Systems in Time-Varying Channels”; Proc. of the 5th IEEE Intl. Symposium on Signal Processing and Information Technology, pp. 119-124 (Dec. 2005). |
Zhou, et al. “How Accurate Channel Prediction Needs to be for Transmit-Beamforming with Adaptive Modulation Over Rayleigh MIMO Channels?”; IEEE Trans. on Wireless Communications, vol. 3, No. 4, pp. 1285-1294(Jul. 1, 2004) (identified as Giannakis in ISR). |
International Search Report and Written Opinion for International Patent Appln. PCT/IB2008/054185 (Apr. 6, 2009). |
D. J. Love and R. W. Heath Jr., “Limited Feedback Unitary Precoding for Spatial Multiplexing Systems,” IEEE Transactions Information Theory, vol. 51, pp. 2967-2976, Aug. 2005. |
R1-050889, Samsung, “MIMO for Long Term Evolution”, 3GPP TSG RAN WG1 Meeting #42, London, UK, Aug. 2005. |
3GPP TR 25.876, “Multiple-Input Multiple output in UTRA” V1.8.0 (Oct. 2005). |
R1-051314, Texas Instruments, Performance of pre-coded MIMO and per group rate control for OFDMA E-UTRA, RAN1#43, Seoul, Korea, Nov. 7-11, 2005. |
R1-070293, Single user throughput simulation results for non-codebook based pre-coding in EUTRA TDD 3GPP TSG RAN WG1 Meeting #47bis, Sorrento, Italy, Jan. 15-19, 2007. |
3GPP TS 36.211, “Physical Channels and Modulation” V1.1.0 (May 2007). |
Number | Date | Country | |
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20100254473 A1 | Oct 2010 | US |