This application claims priority to and incorporates by reference India application serial number 323/MUM/2005 filed on Mar. 22, 2005, titled ZF restricted ML detection
The present invention relates generally to network communications, and more specifically to signal detection techniques in multi-path and multi-channel systems.
As wireless modes of communication proliferate, the need to transmit at higher data rates is gaining importance. Several methods such as Orthogonal Frequency Division Multiplexing (OFDM) and Space Division Multiplexing offer greater spectral efficiency and superior tolerance in communication through multi-path channels.. Multi-path and MIMO (multiple-input-multiple-output) modes of communication are the generally preferred modes of communication as they provide better transmission rates, efficiency and accuracy.
The transmitted signal needs to be accurately detected at the receiver antennas and for this purpose, several detection schemes such as Zero-Forcing (ZF) detection, sphere decoding, Maximum Likelihood (ML) detection, and K-best detection are known in the art and can be used. Each of these known schemes, however, have certain disadvantages, for example, in ML detection, the decoding complexity increases exponentially with the size of the transmitter constellation, while providing very good performance in terms of probability of error. For schemes such as ZF detection the decoding complexity increases only linearly with respect to the size of the transmitter constellation whereas the performance greatly depends on the co-relation among the paths of the MIMO channel and therefore is limited in achieving good performance by itself. The sphere detection scheme involves finding a subset of a received constellation to do an ML search and also doing various mathematical computations such as QR factorization on the channel matrix and therefore has increased complexity. The K-best scheme generally cannot guarantee the survival of ML paths with overall possible candidate paths. This is because the path metrics of the search-tree created sometimes cross each other and causes irreducible errors, which degrades the symbol error rate performance, even if the signal-to-noise ratio (SNR) is high.
Thus, there is a need to provide an efficient and low complexity signal detection mechanism with different levels of tradeoff between performance and complexity.
The accompanying figures together with the detailed description below are incorporated in and form part of the specification, serve to further illustrate various embodiments and to explain various principles and advantages all in accordance with the present invention, and should not be construed to limit the invention.
While embodiments may be described in many different forms, there are shown in the figures and will herein be described in detail certain specific embodiments, with the understanding that the present disclosure is to be considered as an example of the principles of the invention and not intended to limit the invention to the specific embodiments shown and described. Further, the terms and words used herein are not to be considered limiting, but rather merely descriptive. It will also be appreciated that for simplicity and clarity of illustration, common and well-understood elements that are useful or necessary in a commercially feasible embodiment may not be depicted in order to facilitate a less obstructed view of these various embodiments. Also, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements are exaggerated relative to each other. Further, where considered appropriate, reference numerals have been repeated among the figures to indicate corresponding elements.
As wireless modes of communication proliferate, the need to transmit at higher data rates is gaining importance. Once a signal has been transmitted, several detection techniques may be available at the receiver to identify and detect the transmitted signal. Generally, the transmitted signal is detected from a signal constellation corresponding to the transmitter antennas and based on the modulation scheme employed.
An embodiment of the present invention discloses a method of using a detection method, for instance a ZF detection, an MMSE (Minimum Mean Square Error) detection or a substitute for this method to isolate a single constellation point from the transmitter constellation. Those skilled in the art shall appreciate that such generally known detection schemes that can isolate a single constellation point from the transmitted constellation may be used, and all such detection schemes are within the scope of the present invention. Quantizing the received point in the single constellation space or another point obtained from the received point to some of the signal constellation points using some criterion, such a minimum Euclidean distance, provides a reduced set of constellation points from the transmitter constellation. The transmitted signal is then obtained by performing an ML-detection process on the reduced set of constellation points. In one embodiment of the present invention, a ZF method is employed to provide a decoding complexity that is equal to that of a ZF detector added with the complexity of a 4 QAM ML. Typically, a receiver with multiple receiver antennas, for instance as part of part of a mobile device, a personal digital assistant and a laptop, is configured to detect the transmitted signal from the transmitter constellation.
In a typical wireless communication system a modulated signal vector ‘S’ is transmitted through a channel having a corresponding channel matrix ‘H’ and is received at the receiver antennas as a vector ‘Y’. The transmitted modulated signal ‘S’ is affected due to the presence of obstacles and noise ‘N’ in the channel, and therefore the received signal vector ‘Y’ is different from the original modulated signal ‘S’ and can be represented by:
Y=H*S+N
where * denotes matrix multiplication.
For example, in a single transmit and single receive antenna wireless system, where the channel 130 is a multipath channel with the delay spread L, the received symbol at anytime is a function of L successively transmitted signals and is given by the matrix equation:
where,
For MIMO channels 130 with multiple transmit antennas and multiple receive antennas where the received symbol at a particular receive antenna at anytime is a linear combination of symbols from all transmit antennas, the received signal vector is given by the following matrix equation.
where,
Under an embodiment of the invention, a detection method isolates a constellation point of the transmitter constellation by processing an altered signal. The altered signal is a detected signal and comprises a product of the received signal matrix (Y) and a transformation matrix corresponding to the transmission channel. For example, in the case of a ZF detection scheme, the altered signal comprises a product of the received signal matrix (Y) and an inverse of the channel matrix (H−1). The Zero-Forcing (ZF) detection technique is one of the most straightforward approaches used conventionally for detecting signals at the receiver antennas, and can be employed in cases where the complexity of the detection increases only linearly with the size of the constellation, multiplied by the number of transmitted symbols that were entangled due to the obstacles and noise present in the MIMO or multipath channels. For an isolated constellation point, for example, a single point of the constellation obtained by performing a ZF detection only serves to provide a rough estimate of the transmitted signal.
A Quantizing module 120 quantizes the altered signal to obtain a reduced constellation from the transmitter constellation. The Quantizing module 120 can be included within a receiver or a system coupled to the receiver antennas. The reduced constellation is a subset of constellation points from the transmitter constellation. Those skilled in the art shall appreciate that quantizing is a method generally known in the art and can be used to obtain the reduced constellation from the transmitter constellation using mathematical operations performed on the altered signal. However, other mathematical operations that strive to provide a similar reduced constellation using other operations can also be used and all such mathematical operations are within the scope of the present invention.
In one embodiment, an ML detection module 125 coupled to quantizing module 120 is configured to perform an ML detection operation on the reduced constellation. In general, performing ML detection on the reduced constellation substantially reduces the complexity of the detection scheme as opposed to performing ML detection on the complete transmitter constellation.
Under one embodiment of the invention, the altered signal is quantized to obtain a reduced constellation from the transmitter constellation based on a predetermined procedure, step 205. The altered signal can be obtained using, for instance a zero forcing (ZF) detection scheme or a minimum mean square error (MMSE) detection scheme or any such scheme that provides an approximate location of the received signal. For example, a ZF detection technique when applied to the received signal vector Y generates an altered received vector ŝi. This altered signal is quantized to obtain a reduced set of structured constellation depending on the kind of modulation scheme. Some of the modulation schemes used can be a regular Quadrature Amplitude Modulation (QAM) scheme, a rotated Quadrature Amplitude Modulation scheme, a Phase Shift Keying modulation scheme or any such structured modulation scheme such as the lattice constellation modulation as shown in
An ML detection follows on the reduced constellation to obtain the transmitted signal, step 210. Performing ML detection without the quantization, step 205, would increase the complexity exponentially as the size of the constellation increases. Hence, executing an initial detection scheme to obtain a reduced constellation and thereafter performing ML detection provides lesser complexity.
An ML detection method is then executed on the reduced constellation to obtain the transmitted signal, step 345. The ML detector evaluates an Euclidian distance between the altered signal and the Cartesian product of the set of reduced constellation points obtained after quantization, namely S(ŝi, ŷi). Typically, an ML demodulator's complexity is exponential in the size of the constellation used, the exponent being the number of transmitted symbols that got entangled. In the embodiment of the invention, a ZF detection technique (employed to obtain the nearest constellation point to the altered signal) is used to provide an initial symbol estimation. The symbol estimation is then quantized to obtain a reduced constellation, which reduces the complexity of ML demodulation. The reduced constellation enables the ML detector to search only those constellation points that are in close proximity to the ZF detected point. The embodiment of the present invention, wherein the altered signal is obtained by ZF method for a QAM constellation, provides a decoding complexity that is equal to that of a ZF detector added with the complexity of a 4 QAM ML.
In accordance with the embodiment of the invention, a detection method such as ZF detection for an altered signal 415 or 515 provides four nearest constellation points 410 or 510 corresponding to altered signal 415 and altered signal 515 respectively, constituting the reduced constellation. For example, quantizing altered signal 415 produces signal points 410 on the QAM constellation shown in
Number | Date | Country | Kind |
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323/MUM/2005 | Mar 2005 | IN | national |