KR100936202B1 - Pattern diversity to support a mimo receiver and associated methods - Google Patents

Abstract

The MIMO communication system includes a transmitter and a transmit antenna array coupled to the transmitter and having M antenna elements for transmitting M source signals. The receiving antenna array is connected to the receiver and has N antenna elements that receive M or more different summations of the M source signals, where N is less than M. The signal separation processor is coupled to the receiver to form a mixing matrix comprising M or more different summations of the M source signals such that the mixing matrix has a coefficient equal to at least M. The signal separation processor separates the desired source signals from the mixing matrix.

Description

PATTERN DIVERSITY TO SUPPORT A MIMO RECEIVER AND ASSOCIATED METHODS

TECHNICAL FIELD The present invention relates to the field of communications systems, and more particularly, to a multiple-input multiple-output (MIMO) receiver operating using a compact antenna array.

A multiple input multiple output (MIMO) wireless communication system includes a plurality of antenna elements in a transmitter and a plurality of antenna elements in a receiver. Each antenna array is formed in a transmitter and a receiver based on the antenna elements associated with it.

Due to the presence of various scattering objects in a multipath environment, antenna elements are used in an environment where each signal experiences multipath propagation. Once the receiving antenna elements capture the transmitted signals, signal processing techniques are then applied to separate the transmitted signals and recover the user data.

The signal processing technique may be a blind source separation (BSS) process. This separation is "blind" because this separation is performed with limited information about the transmission signal, the source of the transmission signal, and the influence of the propagation channel affecting the transmission signal. Three blind signal separation techniques commonly used are principal component analysis (PCA), independent component analysis (ICA), and singular value decomposition (SVD).

MIMO communication systems are advantageous in that the capacity of the radio link between the transmitter and the receiver can be improved. Multipathy environments enable multiple orthogonal channels to be created between the transmitter and the receiver. The data for a single user can then be transmitted over the air on these channels in parallel and simultaneously using the same bandwidth.

Current MIMO communication systems use spatial diversity antenna elements such that the number of orthogonal channels that can be formed is not reduced. The problem with such an implementation is that the performance of the MIMO communication system is generally proportional to the number of antenna elements used.

As the number of antenna elements increases, the size of the antenna array of the MIMO communication system also increases. When a MIMO receiver is implemented in a small portable communication device, there is little volume available for many antenna elements, and mounting the antenna element outside of the communication device is a problem for the user.

One way of providing a more compact antenna array for a MIMO receiver is disclosed in US Pat. No. 6,870,515. Instead of using spatial diversity antenna elements, polarization diversity is used. Since tightly spaced antenna elements are used, it is possible to provide a compact antenna array to the MIMO receiver.

Although a more compact antenna array has been provided, the performance of a MIMO communication system is still based on the number of antenna elements at the receiver, which is greater than or equal to the number of antenna elements at the transmitter. For example, US Pat. No. 6,870,515 discloses that the number of receive antenna elements is greater than or equal to the number of transmit antenna elements.

In view of the foregoing background, it is an object of the present invention to provide a still powerful MIMO communication system while reducing the number of antenna elements of a MIMO receiver as compared to the number of antenna elements of a MIMO transmitter.

These objects, features and advantages and other objects, features and advantages according to the present invention are directed to a MIMO communication system comprising a transmitter and an antenna array coupled to the transmitter and including an M antenna element for transmitting M source signals. Provided by

At the receiving side, the receiving antenna array includes N antenna elements connected to the receiver and receiving at least M different summations of the M source signals, where N is less than M. The signal separation processor may be coupled to the receiver to form a mixing matrix comprising M or more different summations of the M source signals such that the mixing matrix has at least the same rank as M. The signal separation processor separates the desired source signals from the mixing matrix.

The signal separation processor may be a blind signal separation processor. The blind signal separation processor may separate the desired source signals from the mixing matrix based on at least one of principal component analysis (PCA), independent component analysis (ICA), and eigenvalue decomposition (SVD).

Alternatively, the signal separation processor may separate the desired source signals from the mixing matrix based on the information based processing signal extraction process. The information-based signal separation (extraction) process may separate a desired source signal from the mixing matrix based on at least one of a zero forcing (ZF) process and a minimum mean squared estimation (MMSE) process.

The receiving antenna array preferably receives M different summations of M source signals using N antenna elements, where N < M. The N antenna elements generate M or more different antenna patterns to receive M different summations of the M source signals. M different summations of the M source signals, received by the N antenna elements in the receive antenna array, are used to populate the mixing matrix such that the mixing matrix has at least the same coefficient as M.

The coefficients of the mixing matrix determine how many signals can actually be separated. The larger the coefficient, the more signals can be separated. As a result, a compact antenna array having fewer N antenna elements than M antenna elements in the transmit array can be used by the MIMO receiver, while still providing a powerful MIMO communication system.

There are a plurality of other embodiments of the receiving antenna array. N antenna elements may be correlated to form a phased array. In another embodiment, the N correlated antenna elements may include one or more active antenna elements and up to N-1 passive antenna elements to form a switched beam antenna. In addition, at least two correlated antenna elements of the N correlated antenna elements may have different polarizations.

Another embodiment of the receive antenna array may have a multiplier effect at the received M different summations of the M source signals. This makes it possible to preferably further increase the coefficient of the mixing matrix, without having to increase the number of N antenna elements in the receive antenna array. By increasing the coefficients of the mixing matrix, more signals can be separated by the blind signal separation processor.

The multiplier effect on the number of received M received different summations of the M source signals can be realized using one or a combination of the following. Array deflection involves changing the height of the antenna pattern to receive additional summations of the source signals. Path selection may be performed such that all summations of the source signals used to populate the mixing matrix are correlated and / or statistically independent. Signal segmentation can also be used to further fill the mixing matrix. Different summation signals may be split using spreading codes, or may be split into in-phase (I) components and quadrature phase (Q) components.

M linearly independent summation is the minimum necessary to support a full MIMO implementation of M transmit antenna elements, but has an advantage over M. For example, not all N antenna elements in the receive antenna array can be directed to receive M linear independent summations. Likewise, not all received sums are sufficiently linearly independent.

In addition, if there are interfering interference sources or noise sources, additional mixing matrix coefficients may be needed to separate these signals. Another advantage of isolating interference sources or noise sources results in a reduction in signal-to-noise ratio, resulting in higher data rates, lower error rates, and / or reduced transmit power.

For the above two reasons, it is desirable to increase the coefficient of the mixing matrix to be larger than M, which is related to the number of available channels. This increase in L additional sums of typical Ms can provide a more robust MIMO implementation. Depending on the means available to increase the mixing matrix, the number of receive antenna elements may still be less than M of conventional MIMO, or increase to M or more so that the mixing matrix coefficient may increase to N + L> M Can be.

Another aspect of the invention is directed to a method for operating the above-described MIMO communication system.

1 is a block diagram of a MIMO communication system in accordance with the present invention.

FIG. 2 is a more detailed block diagram of the receiving element of the MIMO communication system as shown in FIG.

3 is a block diagram of a MIMO receiver operating based on array deflection to provide different summation of signals for blind signal separation processing in accordance with the present invention.

4 is a block diagram of a MIMO receiver operating based on path selection to provide different summation of signals for blind signal separation processing in accordance with the present invention.

5 is a block diagram of a MIMO receiver operating based on a spreading code to provide additional summation of signals for blind signal separation processing in accordance with the present invention.

6 is a block diagram of a MIMO receiver operating based on in-phase signal components and quadrature phase signal components to provide additional summation of the signals for blind signal separation processing in accordance with the present invention.

The invention will now be described more fully hereinafter with reference to the accompanying drawings, in which preferred embodiments of the invention are shown. However, the invention may be embodied in many other forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Like numbers refer to like elements throughout the drawings.

First, the MIMO communication system 20 will be described with reference to FIG. 1. The MIMO communication system 20 includes a transmitter 30, a transmit antenna array 32, a receiver 40, and a receive antenna array 42. As will be readily appreciated by those skilled in the art, the transmitter 30 and receiver 40 may be replaced by a transceiver. Thus, each of these antenna arrays 32, 42 supports bidirectional data exchange. However, to explain the present invention, reference will be made to transmitter 30 and receiver 40.

The transmit antenna array 32 includes M antenna elements 33 (1) -33 (M) that transmit M source signals 34 (1) -34 (M). For example, the antenna elements 33 (1)-33 (M) may be spatially correlated. Source signals 34 (1) -34 (M) are generally referred to by reference numeral 34, and antenna elements 33 (1) -33 (M) may generally be referenced by reference numeral 33.

Receive antenna array 42 includes N antenna elements 43 (1) -43 (N) that receive M or more different summations of the M source signals, where N is less than M. Since N <M, while a compact antenna array is used in the receiver 40, it is still possible to obtain a robust MIMO communication system 20, as will be described in more detail later. Antenna elements 43 (1) -43 (N) may generally be referenced with reference numeral 43.

Due to the presence of various scattering objects (buildings, cars, hills, etc.) in a multipath environment, each antenna array 32, 42 is used in an environment where each signal experiences multipath propagation. do. Each path may be considered as a different communication channel. Thus, reference numeral 50 in FIG. 1 denotes a scattering environment resulting in a multipath channel between transmit antenna array 32 and receive antenna array 42. Data is transmitted from the transmit antenna array 32 using a space-time coding (STC) transmission method as known in the art.

In addition to the M source signals, L interfering source signals 35 from the interferer 37 are present in the scattering environment 50, preventing the separation of the desired source signals. Preferably, various means of increasing the mixing matrix can be used to fill the mixing matrix above the coefficient M, as will be described in more detail later.

If receive antenna array 42 captures M different summations of M source signals 34, signal processing techniques are applied to separate the signals. A blind signal separation (BSS) processor 44 is coupled to the receiver 40 to form a mixing matrix 46 comprising M or more different summations of the M source signals such that the mixing matrix has at least the same coefficient as M. The blind signal separation processor 44 separates the desired source signals from the mixing matrix 46.

As described in more detail in this application, three common techniques belonging to blind signal separation techniques are principal component analysis (PCA), independent component analysis (ICA), and eigenvalue decomposition (SVD). As long as the signal is independent of some measurable characteristic, and if the sum of these signals is linearly independent of each other, one or more of these blind signal separation techniques are used to separate the independent source signal or desired source signals from the mix of source signals. Can be used. The measurable characteristic is usually some combination of the first, second, third or fourth moments of the signals.

The PCA whitens the signal, uses the first and second moments, and rotates the data set based on the correlation characteristics. If the signal-to-noise ratio of the source signals is high, the signal separation process can stop with PCA.

If the signal-to-noise ratio of the source signals is low, ICA separates the source signals based on the statistical properties accompanying the third and fourth moments of the source signal. Some source signals are normally distributed and their third and fourth moments depend on the first and second moments. The random noise source may be a normal distribution and spread spectrum signals are designed to exhibit a normal distribution to the decoder by spreading codes other than their specific spreading code. Under certain conditions, the overall signal may exhibit a normal distribution due to the central limit theorem. The ICA scheme can separate one normal distribution signal. In a different way from ICA and PCA, SVD separates source signals from mixed source signals based on eigenvalues of the mixed source signals.

 As an alternative to the blind signal separation processor, a signal separation processor may be used to separate the desired source signals from the mixing matrix based on the information based processing signal extraction process. The information based signal separation (extraction) process separates a desired source signal from the mixing matrix based on at least one of, for example, a zero forcing (ZF) process and a minimum mean squared estimation (MMSE) process.

Different elements on the receiving side of the MIMO communication system 20 will be described in more detail with reference to FIG. Receive antenna array 42 includes N antenna elements 43 (1) -43 (N) that receive M or more different summations of M source signals 34, where N and M are greater than one. Large and N is less than M. Receive antenna array 42 is not limited to any particular configuration. Receive antenna array 42 may include one or more antenna elements 43. Antenna elements 43 may, for example, be configured such that the antenna array forms a phased array or switched beam antenna.

To make the mixing matrix 46, one aims to generate different sums of signals. In fact, in this application, the signal of interest can always be lower than the interferer and can still be separated. Because of this significant difference in purpose, the distance between the antenna elements 43 does not need to be specifically separated as is typically required with an active beamforming antenna array and a passive beamforming antenna array.

Receiver 40 is connected downstream to receive antenna array 42 which receives M or more different summations of the M source signals 34. The blind signal separation processor 44 is connected downstream to the receiver 40. Although the blind signal separation processor 44 is shown separate from the receiver 40, the blind signal separation processor may also be included within the receiver. Different summations of the M source signals 34 received by the receiver 40 are used to populate the mixing matrix 46. The mixing matrix 46 is then processed by one or more blind signal separation processing modules 62, 64, 66 in the blind signal separation processor 44.

The blind signal separation processing modules include a PCA module 62, an ICA module 64, and an SVD module 66. These modules 62, 64, 66 may be configured as part of the blind signal separation processor 44. While the PCA module 62 operates based on the first and second moments of the different summations of the received source signals, the ICA module 64 operates based on the third and fourth moments of the same signals. SVD module 66 performs signal separation based on the eigenvalues of the different summations of the received source signals.

If the correlation processing initially performed by the PCA module 62 determines the initial separation matrix [68 (1)] for the different summation of the source signals, the ICA module 64 separates the source signals in the mixing matrix 46. Determines an improved separation matrix 68 (2). Once the signals are separated by the SVD module 66, a separation matrix 68 (3) is also determined that separates the different summations of the source signals received in the mixing matrix 46.

Signals separated from each separation matrix 68 (1) -68 (3) are indicated by reference numeral 49. The separated signal 49 then undergoes signal analysis by the signal analysis module 70 to determine which signal is the signal of interest and which signal is the interfering signal. Application dependent processing module 72 processes the signal output from signal analysis module 70.

The determination of which signal is the signal of interest is not always accompanied by the final signal to be decoded. For example, the application may identify the interferers and subtract those interferers from the different summations of the received source signals, asking the waveform decoder to provide the reduced signal. In this case, the signal of interest is the signal that ends with the last rejection.

The coefficient of the mixing matrix 46 determines how many signals can actually be separated. For example, a mixing matrix with coefficient 4 means that four source signals can be separated. Ideally, the coefficients of the mixing matrix 46 should be at least equal to the number M of source signals. The larger the coefficient, the more signals can be separated. As the number M of source signals increases, the number N of antenna elements required also increases. US Pat. No. 6,870,515, described in the background art, discloses that the number N of antenna elements of a receiver is greater than or equal to the number M of antenna elements of a transmitter (ie, N ≧ M).

Preferably, receive antenna array 42 receives M different summations of M source signals 34 using N antenna elements 33, where N < M. The N antenna elements 43 produce at least M different antenna patterns that receive M different summations of the M source signals. M different summations of the M source signals 34 received by the N antenna elements 43 in the receive antenna array 42 are used to fill the mixing matrix 46 such that the mixing matrix is at least M and M. Try to have the same coefficient.

As mentioned above, the coefficients of the mixing matrix 46 determine how many signals can actually be separated. The larger the coefficient, the more signals can be separated. Thus, a compact receive antenna array 42 having fewer N antenna elements 43 than the M antenna elements 33 of the transmit antenna array 32 can still be used by the MIMO receiver 40. A powerful MIMO communication system 20 can be provided.

M linearly independent summation is the minimum necessary to support a full MIMO implementation of M transmit antenna elements 34, but there is an advantage to exceeding M. For example, not all N antenna elements 43 in receive antenna array 42 are directed to receive M linearly independent summations. Likewise, not all of the received sums are sufficiently linearly independent. In addition to the M known signal streams to be separated, there may also be L other signals that worsen the signal to noise ratio.

Therefore, it is desirable to take advantage of increasing the coefficients of the mixing matrix by M + L where possible. Another advantage of isolating interference or noise sources is that the signal-to-noise ratio is consequently reduced as a result, which makes it possible to increase the data rate, lower the error rate and / or reduce the transmit power.

For example, there may be L interference source signals 35 that interfere with the separation of the desired source signals 34 from the mixing matrix, where L is greater than one. If increasing the coefficient of the mixing matrix is exhausted without having to add additional antenna elements, adding one or more additional antenna elements will provide additional means to increase the coefficient of the mixing matrix. Adding additional elements may not adhere to the number of elements less than M of conventional MIMO schemes, or may return the number of elements to M, or increase the number of elements to M or more. Depending on the gain obtained by increasing the mixing matrix coefficients, adding additional elements is still valuable, although increasing the number of receiver antenna elements. For example, a mixing matrix of M + L coefficients requiring M elements is usually an implementation superior to M element implementations using conventional processing MIMO receivers. However, to illustrate the present invention, the following discussion will focus on the M source signals.

There are a number of different embodiments of receive antenna array 42. N antenna elements 43 are correlated to form a phased array. In another embodiment, the N correlated antenna elements 43 may include one or more active antenna elements and up to N-1 passive antenna elements to form a switched beam antenna. In addition, at least two of the N correlated antenna elements may have different polarizations.

Other embodiments for receive antenna array 42 may have a multiplier effect in the received M different summations of the M source signals. Preferably, this allows the coefficient of the mixing matrix 46 to be further increased without having to increase the number of N antenna elements 43 in the receive antenna array 42. By increasing the coefficients of the mixing matrix 46, more signals can be separated by the blind signal separation processor 44.

The multiplier effect on the number of received M different summations of the M source signals 34 may be achieved using one or a combination of the following. Array deflection involves varying the height of the antenna pattern to receive additional summation of the source signals 34. Path selection may be performed such that all summations of the source signals 34 used to populate the mixing matrix 46 are correlated and / or statistically independent. In addition, signal division may be used to further fill the mixing matrix 46. Different summation signals may be split using a spreading code, or may be split into an in-phase (I) component and a quadrature phase (Q) component.

Different embodiments for the receive antenna array will now be described in more detail with reference to FIGS. 3 to 6. Array deflection will now be discussed with reference to FIG. 3. Receive antenna array 142 includes N antenna elements 143 to generate N initial antenna patterns to receive N different summations of the M source signals. Receive antenna array 142 also generates one or more additional antenna patterns to selectively change the altitude of one or more of the N initial antenna patterns to thereby receive one or more additional different summations of the M source signals. Altitude controller 141.

Receiver 140 is coupled to receive antenna array 142 and receives N different summations of M source signals using N initial antenna patterns, and also M sources using one or more additional antenna patterns. Receive one or more additional different summations of the signals.

A blind signal separation processor 144 is coupled to the receiver 140 to form a mixing matrix 146 that includes N different summations of the M source signals and one or more additional different summations of the M source signals. The mixing matrix has the same coefficient as N plus the number of additional different summations of the M source signals received using additional antenna patterns. The resulting coefficient of the mixing matrix 146 is at least equal to M. The blind signal separation processor 144 separates the desired signal from the mixing matrix 146.

In general, any antenna array means may be used in the deflection mechanism that provides a signal sum suitable for increasing the coefficient of the mixing matrix. This deflection will produce two separate mixing matrices that can utilize the signal sums for each antenna array means. Therefore, the double multiplier effect is obtained by utilizing this technique.

Array deflection is divided into K separate regions associated with the antenna, each of the K regions may provide two independent deflection regions, and is input to the mixing matrix. For example, if the antenna array can provide N sums by itself and there are K separate deflection regions, the number of signal sums in the mixing matrix can be 2NK.

Separating the source signals provided by the M signal sources based on the path selection will be described with reference to FIG. 4. Receive antenna array 242 includes N elements 243 to form N or more antenna beams that receive N or more different summations of the M source signals, where N and M are greater than two.

Controller 250 is coupled to antenna array 242 to selectively form N or more antenna beams. Receiver assembly 240 is coupled to antenna array 242 to receive at least N different summations of the M source signals. A blind signal separation processor 244 is coupled to the receiver assembly 240 to form a mixing matrix 246 that includes at least N different summations of the M source signals.

The blind signal separation processor 244 also determines whether different summations of the M source signals are correlated or statistically independent, and if not, are not correlated or statistically independent in the mixing matrix 246. In order to replace the different summation of the M source signals, it cooperates with the controller 250 to form a different beam that receives a new different summation of the M source signals. As a result, M or more different summations of the source signals are received such that the mixing matrix has at least the same coefficient as M. The desired source signals are then separated from the mixing matrix 246.

A rake receiver is a wireless receiver designed to counter the effects of multipath fading. This is done using several independent receivers, each delayed slightly to receive individual multipath components. This can be used by most kinds of radio access networks. This has been found to be particularly beneficial for modulation in the form of spreading codes. The ability to select a particular incident signal path is suitable as a means for changing the paths supplied to the blind signal separation processor 244.

Selectively forming the N antenna beams as described above can be applied to all radio access networks as will be readily understood by those skilled in the art. In the case of a CDMA system, receiver assembly 240 includes N rake receivers 256. Each rake receiver 256 includes k fingers and selects k different multipath components for each of the N different summations of the M source signals received by each antenna element connected thereto. In this configuration, the blind signal separation processor 244 is connected to the N rake receivers 256 to form the mixing matrix 246. The mixing matrix 246 includes up to at least kN different multipath components of N or more different summations of the M source signals, the mixing matrix having a coefficient equal to at most kN, where kN is at least equal to M .

In particular, when CDMA waveforms are propagated, CDMA waveforms usually encounter multiple paths from source to destination. Rake receiver 256 is specifically designed to capture many of these individual instances and combine them for more robust signal decoding. While the source signals propagate along each path, the characteristics of the signal are modified due to the unique characteristics of the path. In some situations, modifications to the correlation and / or statistical properties of the received signal may be so large that they can be treated as a separable signal stream. Modified rake receiver 256 may be used to extract each modified stream and supply it as an input unique to mixing matrix 246. This means of increasing the coefficient is not always available, but it is likely to be available in a high multipath environment, perhaps if necessary.

Although rake receiver 256 may use different paths, a more general approach applicable to any modulation technique is beamforming. This is different from rake receiver 256 because beamforming is used to improve the desired signal as well as reject the desired signal. However, the difference is that the rejected signal may be substantially another version of the signal directed to the receiver. However, receiver assembly 240 needs to detect multiple unique propagation path versions of the same signal to make mixing matrix 246 sufficient coefficients.

In addition, signal splitting may be used to further fill the mixing matrix A. FIG. In one scheme, the summation signals are split using a spreading code. In another way, the summation signals are split using in-phase (I) component and quadrature (Q) component module.

Signal division using spreading code will now be described with reference to FIG. Receive antenna array 342 includes N antenna elements 343 to receive N or more different summations of the M source signals. Code despreader 350 is coupled to N antenna elements 343 to decode N or more different summations of the M source signals. Each of the N different summations includes k codes that provide k different summations of the M source signals associated therewith.

Receiver assembly 340 is coupled to code despreader 350 to receive kN or more different summations of the M source signals. A blind signal separation processor 344 is coupled to the receiver assembly 340 to form a mixing matrix 346 containing kN or more different summations of the M source signals. The mixing matrix 346 has a coefficient equal to kN and the resulting coefficient is at least equal to M. The blind signal separation processor 344 separates the desired source signals from the mixing matrix 346.

Depending on the modulation of the received signal, the aforementioned signal division can be used to increase the coefficient of the mixing matrix without increasing the number of N antenna elements. Examples of spread spectrum communication systems in which spreading codes are used are CDMA IS-95, CDMA 2000 and WCDMA. A common thread is to process a unique code into each signal to spread data over a wider frequency band.

The same spreading code is processed with the received signal sum (desired signal, unwanted signal and unknown noise sources). This reconstructs the desired signal back to its original frequency bandwidth while spreading the interferer over a wide frequency band.

The CDMA implementations listed above actually have numerous signal streams using the same frequency band simultaneously. Each signal stream uses a code that is ideally orthogonal to all other signals. If this condition matches the decoder, this means that only the signal of interest is despread.

Usually there is some correlation between the CDMA signals, so that the interfering signals are reconstructed to some extent with the desired signal. This is usually due to the delay experienced by the individual signals and also by the multipath generation of the signals. Some of the unwanted signals, in particular the value of the CDMA signal, will increase. This increase is not as important as the desired signal, but increases the overall noise value, reducing the signal-to-noise ratio.

The form of the despread signal equation and the signal itself meet the criteria of blind signal separation processing. Indeed, if one of the despreading codes is individually applied to each known signal received by receiver assembly 340, a separate sum is obtained that conforms to the ICA model requirements.

Therefore, there are a number of row entries that can be used in a mixing matrix as known code, and of course it is assumed that each row entry produces an important value that is linearly independent. Under normal circumstances, this will allow an increase of the mixing matrix to a value greater than the number of codes. For example, N antenna elements and M codes may provide NM matrix rows.

For illustrative purposes, assume three codes are known, and the three known code signals maintain their orthogonality. In code despreader 350, the mixing matrix A has three rows at the top and three rows at the bottom due to the antenna stream after each stream is despread by three known codes, respectively. Because of the orthogonality of the codes, the value of off diagonal becomes zero. Column entries 4, 5 and 6 are a common case for unknown signals of the same index.

The signals corresponding to column entries 4, 5, 6 may be different path versions of known code, or may be other cell signals of unknown code. In addition, one signal may be a normal distribution signal, and the other signal may be any signal in the CDMA signal group that conforms to the center limit theorem, so that they may appear as a single normal distribution signal (eg, Release 4 channels). In other words, a sufficient amount of non-random signals will be added to the normal distribution signal. The interferers can be at most one normally distributed signal that is unknown to the nonnormally distributed signal source or network.

After despreading known codes in code despreader 350, blind signal separation processor 344 receives mixing matrix 346 of coefficient 6. The coefficient 6 is derived based on two antenna elements multiplied three times because three codes are known.

Six signals are applied to the blind signal separation processor 344, where a mixing matrix 346 having a coefficient of 6 is formed. The blind signal separation processor 344 only determines the separation matrix W from the received signals (x = As) changed by the channel, where A is the mixing matrix. In the example described, six signals may be separated.

The blind signal separation processor 344 selects the signals to be decoded. For example, interfering signals may be dropped and all versions of the desired signals may be selected. The selected signals are applied to the demodulator module for demodulation. The demodulator uses well known equalization techniques that combine multipath versions of the same signal.

In the more general case, the non-diagonal value is shown simply as 0 above, but may not be substantially zero. This is a more common case where the correlation characteristics between coded signals are not perfect. This expresses additional noise into separate signals. However, as shown above, since the coefficients of the matrix are sufficient to separate these signals, the non-diagonal value will be significantly reduced after the blind signal separation process. This leads to a reduction in noise, an increase in the signal-to-noise ratio, and an increase in channel capacity, as indicated by Shannon's law.

Referring to FIG. 6, another way of increasing the coefficient of the mixing matrix A without increasing the number of N antenna elements is to separate the received mixed signal into in-phase (I) and quadrature (Q) components. . The I and Q components of the coherent RF signal are the same in amplitude but 90 degrees out of phase.

Receive antenna array 442 includes N antenna elements 443 to receive N or more different summations of the M source signals. Each in-phase and quadrature phase module 450 separates N different summations of the M source signals received at the antenna element downstream of each antenna element 443 into a set of in-phase and quadrature phase components, respectively.

Receiver assembly 440 receives at least N sets of in-phase and quadrature components for at least N different summations of the M source signals downstream of each in-phase and quadrature phase module 450. The blind signal separation processor 444 forms a mixing matrix 446 that includes at least 2N different summations of the M source signals downstream of the receiver assembly 440. Each in-phase and quadrature phase component set provides two inputs to the mixing matrix 446. The mixing matrix 446 has the same coefficient as 2N, and the blind signal separation processor 444 separates the desired source signals 514 from the mixing matrix 512.

By separating the received mixed signals into I and Q components, the size of the mixing matrix is doubled. As long as the I and Q components are encoded using different data streams, the mixed signal received at any antenna element may be divided into two different mixed signals.

For differential encoding, the nature of the modulation needs to be analyzed to determine whether I and Q meet the linear requirements. For GSM, for example, GMSK encoding can be assumed linear when used for proper filtering and shows that it can be processed at the receiver as if it were BPSK encoding. Since the BPSK meets the requirements for blind signal separation processing, the I and Q processes described can be used.

The I component and the Q component can be used in any of the above described antenna array embodiments to populate the mixing matrix (A). When I and Q are used, the mixing matrix A can be filled as if the number of antenna elements is doubled. The antenna element may be in the form of any diversity such as uncorrelated, correlated or polarized. N antenna elements that divide the signal sum of each element into I and Q components provide 2N independent mixed signal sums. As a result, the coefficient of the mixing matrix is 2N, where 2N is at least equal to or greater than M.

This mechanism can also be used as an antenna array deflection technique to generate more sum of signals. In addition, each of these sums may in turn be separated into I and Q components. The doubled increase due to I and Q, the N antenna elements, and the k deflection regions for the antenna array provide 2kN sums for the mixing matrix.

Those skilled in the art will appreciate that many modifications and other embodiments of the invention will benefit from the techniques presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the invention is not limited to the specific embodiments disclosed and that modifications and other embodiments can be included within the scope of the appended claims.

Claims (25)

A multiple input multiple output (MIMO) communication system, A transmitter; A transmit antenna array coupled to the transmitter and comprising M antenna elements for transmitting M source signals; A receiver; A receiving antenna array coupled to the receiver, the receiving antenna array comprising N antenna elements for receiving M or more different summations of M source signals, where N is less than M; A signal separation processor coupled to the receiver and forming a mixing matrix comprising M or more different summations of the M source signals such that the mixing matrix has a rank equal to at least M Wherein the signal separation processor separates desired source signals from the mixing matrix. The method of claim 1, wherein there are L interferer source signals (L is greater than 1) that prevents separating the desired source signals from the mixing matrix, Wherein the mixing matrix also increases the coefficient of the mixing matrix by L plus M different summations of the M source signals such that the mixing matrix has a coefficient equal to at least M + L. 10. The system of claim 1 wherein the receive antenna array comprises N correlated antenna elements to form a phased array. 2. The antenna of claim 1 wherein the receive antenna array comprises N correlated antenna elements, wherein the N correlated antenna elements comprise at least one active antenna element and up to N-1 to form a switched beam antenna. MIMO communication system comprising a passive antenna element. 2. The system of claim 1 wherein the sum of each of the M source signals is linear. The MIMO communications system of claim 1 wherein the receive antenna array comprises N correlated antenna elements, and at least two antenna elements of the N correlated antenna elements have different polarizations. 7. The system of claim 6 wherein the different polarizations are orthogonal to each other. The method of claim 1, wherein the receive antenna array generates N initial antenna patterns to receive N or more different summations of M source signals, The receive antenna array is connected to the receive antenna array such that one or more additional different antenna patterns are generated to receive one or more additional summations of the M source signals so that at least one of the N initial antenna patterns Further comprising an altitude controller for selectively changing the altitude, The mixing matrix further includes one or more additional different summations of the M source signals, the mixing matrix being the same coefficient as N plus the number of additional different summations of the M source signals received using additional antenna patterns. And the resulting coefficient is at least equal to M. 2. The antenna of claim 1, wherein the receive antenna array generates at least N antenna beams, wherein N and M are greater than 2, to receive at least N different summations of M source signals; The MIMO communication system further includes a controller coupled to the receive antenna array to selectively form N or more antenna beams, The signal separation processor is also Determine whether different summations of the M source signals are correlated or statistically independent, If not correlated or statistically independent, the M sums are replaced to replace different summations of the M source signals that are not correlated or not statistically independent in the mixing matrix such that a coefficient is at least equal to M. And interact with the controller to form different beams to receive new different summations of source signals. 2. The code despreader of claim 1, wherein each sum of N different sums provides k different sums connected to the N antenna elements to decode N or more different sums of M source signals. Contains k codes to- The receiver is coupled to the despreader to receive at least kN different summations of M source signals, And the signal separation processor includes kN or more different summations of M source signals to form a mixing matrix such that the resulting coefficients are at least equal to M. 10. The apparatus of claim 1, connected downstream to each antenna element in the receive antenna array to separate each summation of M different summations of M source signals received by the antenna element into a set of in-phase and quadrature phase components. Each of which further comprises an in-phase and quadrature phase module, The signal separation processor forms a mixing matrix comprising at least 2N different summations of the M source signals, each set of in-phase and quadrature phase components providing two inputs within the mixing matrix such that the resulting coefficient is equal to at least 2N. Wherein the 2N is at least equal to M. 2. The signal separation processor of claim 1, wherein the signal separation processor comprises a blind signal separation processor, the desired source signal from the mixing matrix based on at least one of principal component analysis (PCA), independent component analysis (ICA), and eigenvalue decomposition (SVD). MIMO communication system to separate them. 2. The MIMO communications system of claim 1 wherein the signal separation processor separates the desired source signals from the mixing matrix based on an information based processing signal extraction process. The system of claim 13, wherein the information based signal extraction process separates the desired source signals from the mixing matrix based on at least one of a zero forcing (ZF) process and a minimum mean squared estimation (MMSE) process. 2. The system of claim 1 wherein the signal separation processor separates the desired source signals from the mixing matrix based on a combination of an information based signal extraction process and a blind signal separation process. A method of operating a multiple input multiple output (MIMO) communication system, comprising: Transmitting M source signals from a transmit antenna array coupled to a transmitter, the transmit antenna array including M antenna elements for transmitting M source signals; Receiving at least M different summations of M source signals using a receive antenna array comprising N antenna elements, wherein N is less than M; Providing M or more different summations of M source signals to a receiver; Processing M or more different summations of M source signals by a blind signal separation processor coupled to the receiver It includes, wherein the processing step, Forming a mixing matrix comprising M or more different summations of the M source signals such that the mixing matrix has a coefficient equal to at least M; Separating a desired source signal from the mixing matrix Method of operation of a MIMO communication system comprising a. 17. The method of claim 16, wherein there are L interferer source signals (L is greater than 1) that prevents separating the desired source signals from the mixing matrix, And further including L additional sums in M different summations of the M source signals such that the mixing matrix has a coefficient equal to at least M + L. 17. The method of claim 16 wherein the receive antenna array comprises N correlated antenna elements to form a phased array. 17. The antenna of claim 16 wherein the receive antenna array comprises N correlated antenna elements, wherein the N correlated antenna elements comprise at least one active antenna element and up to N-1 to form a switched beam antenna. And a passive antenna element of the MIMO communication system. 17. The method of claim 16 wherein the receive antenna array comprises N correlated antenna elements, wherein at least two of the N correlated antenna elements have different polarizations. 17. The apparatus of claim 16, wherein the receive antenna array generates N initial antenna patterns to receive N or more different summations of M source signals; The receive antenna array is connected to the receive antenna array such that one or more additional different antenna patterns are generated to receive one or more additional summations of the M source signals so that at least one of the N initial antenna patterns Further comprising an altitude controller for selectively changing the altitude, The mixing matrix further includes one or more additional different summations of the M source signals, the mixing matrix being the same coefficient as N plus the number of additional different summations of the M source signals received using additional antenna patterns. And the resulting coefficient is at least equal to M. The method of operation of a MIMO communication system. 17. The apparatus of claim 16, wherein the receive antenna array generates N or more antenna beams, wherein N and M are greater than 2, to receive N or more different summations of M source signals; The MIMO communication system further includes a controller coupled to the receive antenna array to selectively form N or more antenna beams, The blind signal separation processor, Determine whether different summations of the M source signals are correlated or statistically independent, If not correlated or statistically independent, the M sources are replaced to replace different summations of the M uncorrelated or non-correlated signals in the mixing matrix such that a coefficient is at least equal to M. Operating with the controller to form different beams to receive new different summations of signals. 17. The code despreader of claim 16, coupled to the N antenna elements to decode N or more different summations of M source signals, each sum of N different sums provides k different summations. Contains k codes to- The receiver is coupled to the despreader to receive at least kN different summations of M source signals, And wherein said blind signal separation processor comprises kN or more different summations of M source signals to form a mixing matrix such that the resulting coefficients are at least equal to M. 2. 17. The apparatus of claim 16, connected downstream to each antenna element in the receive antenna array to separate each summation of M different summations of M source signals received by the antenna element into a set of in-phase and quadrature phase components. Each of which further comprises an in-phase and quadrature phase module, The signal separation processor forms a mixing matrix comprising 2N or more different summations of M source signals, each set of in phase and quadrature phase components providing two inputs within the mixing matrix such that the resulting coefficient is equal to at least 2N. Wherein the 2N is at least equal to M. 2. 17. The method of claim 16, wherein separating the desired source signal from the mixing matrix is based on at least one of an information based signal extraction process and a blind signal separation process.

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