The present invention relates to digital communications, and particularly to detection of multiple streams in a multiple-input multiple-output (MIMO) system.
In the last few years wireless services have become more and more important. Likewise the demand for higher network capacity and performance has increased. Multiple-input multiple-output (MIMO) technique can provide significant performance gain on the system capacity over the traditional single-input single-output (SISO) systems. Therefore, the MIMO technique is becoming a favourite solution to support higher data rate transmission in communications. See documents [1]-[7] below. In a MIMO system, high-rate data transmission is achieved by dividing the original data stream into several parallel data substreams, each of which is transmitted from a corresponding transmitting antenna (spatial multiplexing). The number of spatial streams depends on the number of antennas so that it is the minimum of the number of the transmit antennas and the number of receive antennas. All data substreams are independent of each other and different data substreams act as interference upon reception by a plurality of receiving antennas. The receiver has the possibility to separate and equalize the multiple signal paths and data streams by using the channel properties (the channel estimate) and knowledge of the coding scheme.
[1] Yuanbin Guo, McCain, D., “Reduced QRD-M detector in MIMO-OFDM systems with partial and embedded sorting,” Global Telecommunications Conference, 2005. GLOBECOM'05. IEEE, Vol. 1, 2005.
[2] Chin W. H., “QRD based tree search data detection for MIMO communication systems,” Vehicular Technology Conference, 2005. VTC 2005-Spring.
[3] P. W. Wolniansky, G. J. Foschini, G. D. Golden and R. A. Valenzuela, “V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel”.
[4] Jiang Yue, Kyeong Jin Kim, G. D. Gibson and Ronald A. Iltis, “Channel estimation and data detection for MIMO-OFDM systems”.
[5] Kyeong Jin Kim, Jiang Yue, Iltis R. A., Gibson J. D., “A QRD-M/Kalman filter-based detection and channel estimation algorithm for MIMO-OFDM systems,” IEEE transactions on Wireless communications, Vol. 4, March 2005.
[6] Kawai H., Higuchi K., Maeda N., Sawahashi M., “Independent adaptive control of surviving symbol replica candidates at each stage based on minimum branch metric in QRD-MLD for OFDCM MIMO multiplexing [mobile radio],” Vehicular Technology Conference, 2004. VTC2004-Fall, Vol. 3, September 2004.
[7] Yongmei Dai; Sumei Sun; Zhongding Lei, “A Comparative Study of QRD-M Detection and Sphere Decoding for MIMO-OFDM Systems,” Personal, Indoor and Mobile Radio Communications, 2005. PIMRC 2005. IEEE 16th International Symposium on, vol.1, no.pp. 186-190, 11-14 Sep. 2005
MIMO is applicable to all kinds of wireless communication technologies. In the recent 3GGP UTRA (UMTS Terrestrial Radio Access) Releases, a WCDMA and MIMO with up to 4 transmit and 4 receive antennas can be used which means up to 4 spatial streams. Further, a TDD (time division duplex) mode and a FDD (frequency division duplex) mode are available to provide different transmission directions (downlink/uplink, forward/reverse). In the TDD mode the PARC (Per Antenna Rate Control) is used. The PARC is able to adapt the modulation and the coding rate to the quality of the channel. There are four coding schemes consisting of QPSK and 16QAM as well as FEC (Forward Error Correction) code rate ½ and ¾. In total the PARC is able to provide four data streams. The FDD mode uses a D-TxAA (Double Transmit Adaptive Array) which is based on the STTD (Space-Time Transmit Diversity) principle defined in Release 99. In D-TxAA, if four transmit antennas are employed in the transmitter, the transmit antennas are divided into two subgroups and each sub-group transmits independent data stream with TxAA (Transmit Antenna Array) operation of a pair of transmit antennas. The data rate of each sub-group can be controlled independently. The D-TxAA can be seen as twofold Transmit Diversity chain. Each chain is controlled similar to the PARC depending on the channel.
The 3GPP release 8 is also known as “Long Term Evolution” (LTE) and relate to E-UTRA (Evolved UTRA). The LTE uses orthogonal frequency-division multiplexing (OFDM) in downlink. The OFDM is one of the most competitive candidates among techniques used for high-rate data transmission in wireless environments. OFDM is a digital multi-carrier modulation scheme, which uses a number of closely spaced orthogonal sub-carriers. Each sub-carrier is modulated with a conventional modulation scheme (such as QAM) at a low symbol rate, maintaining data rates similar to conventional single-carrier modulation schemes in the same bandwidth. The orthogonality of the sub-carriers results in zero cross talk, even though they are so close that their spectra overlap. Low symbol rate helps manage time-domain spreading of the signal (such as multipath propagation) by allowing the use of a guard interval between symbols. More specifically, since low symbol rate modulation schemes (i.e. where the symbols are relatively long compared to the channel time characteristics) suffer less from intersymbol interference (ISI) caused by multipath, it is advantageous to transmit a number of low-rate streams in parallel instead of a single high-rate stream. Since the duration of each symbol is long, it is feasible to insert a guard interval between the OFDM symbols, thus eliminating the ISI. In practice, OFDM signals are generated at the transmitter using the inverse Fast Fourier transform (IFFT) algorithm which converts a frequency-domain data into time-domain data, the thereby map the data on to the orthogonal subcarriers. For example, the IFFT correlates the frequency-domain input data with its orthogonal basis functions which are sinusoidal at certain frequencies. At the receiver, the Fast Fourier transform (FFT) is used for converting the received time-domain signal into frequency domain. Ideally, the FFT output would be the original symbols that were inputted to the IFFT at the transmitter. However, in practice the FFT output values contain random non-idealities caused by the transmission channel and multipath propagation. Therefore, channel estimates may be generated for each of the subcarries, so that a detector is able to effectively detect the symbols from the received FFT output symbols and the channel estimates. MIMO can used to facilitate the detection. Thus, combination of the MIMO and the OFDM, so called MIMO-OFDM system can achieve high data rates while providing better system performance by using both antenna diversity and frequency diversity, which makes it attractive for high-data-rate wireless applications.
One challenge for practical implementation of spatial-multiplexing-based MIMO system is to design a receiver that offers a good trade-off between its complexity and its performance. The maximum likelihood signal detecting (MLSD) method can be used to achieve the best performance in MIMO communications, but its huge complexity makes it impractical for real applications. The search-tree based QR Decomposition-M (QRD-M) algorithm achieves near the MLSD-performance, while requiring comparatively low complexity. In QRD-M, the signal detecting order has great impacts on the performance and several methods have been proposed in [3] and [4] to achieve better performance based on channel impulse responses.
An object of the invention is to provide a novel QRD-M based detection in a multi-stream MIMO system.
The objects of the invention are achieved by a method, a processor program, a processor-readable medium, an apparatus, a wireless terminal and a wireless base station which are characterized by what is stated in the independent claims. The preferred embodiments of the invention are disclosed in the dependent claims.
According to the invention, multiple spatial signal streams received from a multiple-input multiple output (MIMO) channel are pre-ordered multiple received spatial signal streams from a multiple-input multiple output (MIMO) channel based on modulation alphabets of said received spatial signal streams prior to performing a QR Decomposition-M detection. An improvement in the performance of QRD-M detection can be achieved without increasing the complexity of the receiver design in comparison with the conventional ones.
In embodiments of the invention, elements of a signal vector formed from said received spatial signal streams, and elements of an estimated transmission channel matrix of the MIMO channel are pre-ordered based on said modulation alphabets of said received spatial signal streams prior to performing said QR Decomposition-M detection. In an embodiment of the invention, elements of a signal vector formed from said received spatial signal streams, and elements of an estimated transmission channel matrix of the MIMO channel are pre-ordered into groups based on said modulation alphabets of said received spatial signal streams such that each of said group corresponds to different value of said modulation alphabets. In a further embodiment, A further preordering, such as a H-norm ordering and a H-inverse ordering, is performed within each group of said elements of said signal vector and said elements of said transmission channel matrix prior to performing said QR Decomposition-M detection. In an embodiment of the invention, the received spatial signal streams include 16QAM-modulated spatial signal streams having a modulation alphabet with value 16, and QPSK-modulated spatial signal streams having a modulation alphabet with value 4. In still further embodiments, the received spatial signal streams include multiple spatial signal streams from an orthogonal frequency division multiplexing (OFDM) MIMO channel or a transmit antenna array (TxAA) MIMO channel or a double transmit antenna array (D-TxAA) MIMO channel. In an embodiment of the invention, the received spatial signal streams include multiple spatial signal streams with independently variable modulation schemes, such as multiple spatial signal streams which are rate controlled by a per-antenna rate control (PARC).
In the following the invention will be described in greater detail by means of preferred embodiments with reference to the attached [accompanying] drawings, in which
In the following, some examples are given of wireless multi-stream MIMO systems and receivers wherein the detection according to the present invention may be implemented. However, the invention is not intended to be restricted to these examples but the principles of the present invention can be generally applied to any wireless MIMO (multiple-input multiple-output) communications between remotely-positioned communication stations in a communication system, such as in a cellular communication system operable pursuant to a second/third/fourth generation (2G/3G/4G) communication standard, or in other types of cellular, and other, communication systems, such as WLAN (wireless local area network), WiMAX, etc. In particular, the present invention may be implemented systems pursuant to 3GPP Releases 7 and 8 for HSPDA (high speed packet data access) and LTE (long term evolution) which use a multi-stream MIMO, e.g. PARC (per-antenna rate control) or D-TxAA (Double transmit adaptive array).
Further, the principles of the present invention can be applied to one or both of the transmission directions between a mobile station or user equipment and a base transceiver station. In other words, in some embodiments the invention is applied on the downlink/forward link, that is, communication of data by the base transceiver station to the mobile station, in which the base transceiver station forms the transmitter station and the mobile station forms the receiver station. In some embodiments of the present invention the mobile station forms the transmitter station and the base transceiver station forms the receiver station. Further, in any communication system that provides for duplex communications, the communication stations operable pursuant to a communication session are capable both of sending and receiving data, and each communication station may operate as both a transmitter station and a receiver station.
An example of a communication system employing a multi-stream MIMO with the PARC technique is shown in
At the receiver, the signals transmitted from the Nt transmit antennas are received by the Nr receive antennas ANT1 . . . ANTNr. The receiver may be a weighting matrix (W) based MIMO receiver, for example. In an embodiment shown in
An example of a transmitter employing a multi-stream MIMO with the double-TxAA (D-TxAA) technique is shown in
A MIMO-OFDM system model with Nt transmit and Nr receive antennas is shown in
The principles of the present invention can be applied in the detector banks 26 and 34 of the receivers shown in the
Let us know study the theory of the MIMO-OFDM system shown in
y=Hx+n (2.1)
Where y and n are the Nr -size received signal vector and the additive white Gaussian noise (AWGN) vector with power σ2, respectively. x denotes the Nt-size the transmitted signal vector. H denotes MIMO channel matrix, defined in (2.2).
Let us now examine the use of the conventional maximum likelihood signal detecting (MLSD) and QR Decomposition-M (QRD-M) algorithms for detecting the signals according to equation (2.2.).
With multi-stream interference (MSI) due to the signals from the different transmit antennas on the same sub-carrier and interfering each other, MLSD is the optimal receiver to minimize the error probability. MLSD performs vector decoding in accordance with equation (3.1).
Where the minimization is performed by searching all the possible constellation points in x. It can be noticed that MLSD has complexity exponential to the number of Tx antennas and modulation alphabets.
QR-decomposition based M-searching is a near-optimal scheme to achieve a good tradeoff between the system complexity and performance. The QR decomposition can be applied to the channel matrix H at each sub-carrier as
H=QR (3.2)
Where Q is a Nr by Nr sized unitary matrix and R is Nr by Nt sized matrix
Where T is a Nt by Nt up-triangle matrix.
Multiplying (2.1) with Q* from left side (* denoting the conjugation transposition) and using both (3.2) and (3.3), (3.4) can be obtained.
Ignoring the bottom part of (3.4), we obtain
{tilde over (y)}
u
=Tx+ñ
u (3.5)
Because T is an up-triangle matrix, the MLSD algorithm is exactly equivalent to a tree searching problem to find the leaf note holding the minimum metric as
Where Φ is the set including all possible values of x. Based on the breadth-first tree searching algorithm, QRD-M is proposed in paper [2] and [5]. It reduces system complexities, as opposed to MLSD algorithm, by keeping only a fixed number of candidates with the smallest accumulated metrics at each stage of the tree searching. Conclusively, the QRD-M searching algorithm can be summarized as follows:
In practice, the pre-ordering before QR-decomposition has great impacts on QRD-M performance. There exist two well-known signal pre-ordering methods named H-norm ordering in paper [4] and H-inverse ordering in paper [2]. H-norm ordering is based on the column norms of the channel matrix H, in the other word the channel gain of the signal elements, while H-inverse ordering is done based on the row norm of the pseudo inverse of the channel matrix, i.e. H*. It is noticed that H-inverse has more complexities than H-norm due to its pseudo inverse operation.
Because the H-inverse signal pre-ordering has the similar progress as that of H-norm, for simplicity of expression we only present the H-norm signal ordering progress in this report. At first, we will rewrite (2.1) into
Where h(i) denotes the i-th column vector of matrix H and x(i) denotes the i-th element in signal vector x. By defining (3.8),
E(i)=∥h(i)∥2 (3.8)
the flowchart of the H-norm signal ordering can be implemented as illustrated in
According to the present invention, the performance of QRD-M detection, particularly the bit error performance, can be improved by a novel sorting the detection order based on modulation alphabets at different antennas in a multi-stream MIMO in which in modulation of the streams can be varied independently. Suitable multi-stream MIMO system include, for example, per-antenna rate control (PARC) and D-TxAA described above. An example embodiment of the invention is illustrated by a flowchart shown in
Let us first explain the meaning of the term modulation alphabet as used herein. In digital modulation, an analog carrier signal is modulated by a digital bit stream. This can be described as a form of digital-to-analog conversion. The changes in the carrier signal are chosen from a finite number of alternative symbols, i.e. the modulation alphabet. Examples of the basic digital modulation techniques include a quadrature phase-shift keying (QPSK) and a quadrature-amplitude modulation (QAM). In the QPSK, an inphase signal (the I signal, for example a cosine waveform) and a quadrature phase signal (the P signal, for example a sine wave) are phase modulated with 4 phases, e.g. 0, +90, +180 ja +270 astetta, and the modulation alphabet consists of 4 symbols each representing 2 bits (00, 01, 10, 11). In 8-PSK, 8 modulation phases are employed to form a modulation alphabet of 8 symbols each representing 3 bits (000, 001, 010, 011, 100, 101, 110, 111). In the QAM, an inphase signal (the I signal, for example a cosine waveform) and a quadrature phase signal (the Q signal, for example a sine wave) are amplitude modulated with a finite number of amplitudes. The resulting signal is a combination of a finite number of at least two phases, and a finite number of at least two amplitudes. Each of these phases or amplitudes are assigned a unique pattern of binary bits. Usually, each phase or amplitude encodes an equal number of bits. This number of bits comprises the symbol that is represented by the particular phase. Generally, If the alphabet consists of M=2N alternative symbols, each symbol represents a message consisting of N bits. For example in 16QAM, the modulation alphabet consists of 16 alternative symbols, each symbol representing 4 bits. In the case of QPSK and QAM, the modulation alphabet is often conveniently represented on a constellation diagram, showing the amplitude of the I signal at the x-axis, and the amplitude of the Q signal at the y-axis, for each symbol.
In equation (3.7), x(i) denotes the i-th element of the signal vector x. In an embodiment of the invention, we further define m(i) which denotes the modulation order of the i-th element of the signal vector x. For example, if x(i) is QPSK modulated, then m(i) equals to 4, and if x(i) is 16QAM modulated, m(i) equals to 16, and so on.
Referring now to
The conventional QRD-M signal detection and the ordered QRD-M signal detection according to the present invention were our proposed schemes are analyzed by numerical simulations. The simulation specifications are summarized in Table 1.
The techniques described herein may be implemented by various means. For example, these techniques may be implemented in hardware (one or more devices), firmware (one or more devices), software (one or more modules), or combinations thereof. For a hardware implementation, the processing units used for channel estimation may be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof. For a firmware or software, implementation can be through modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in memory unit and executed by the processors. The memory unit may be implemented within the processor or external to the processor, in which case it can be communicatively coupled to the processor via various means as is known in the art. Additionally, components of systems described herein may be rearranged and/or complimented by additional components in order to facilitate achieving the various aspects, goals, advantages, etc., described with regard thereto, and are not limited to the precise configurations set forth in a given figure, as will be appreciated by one skilled in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Number | Date | Country | Kind |
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20075083 | Feb 2007 | FI | national |