DE102006017296A1 - Training sequence production method for use in e.g. code division multiplex system, involves providing quantity of training sequences with members having pre-determined autocorrelation characteristics - Google Patents

Training sequence production method for use in e.g. code division multiplex system, involves providing quantity of training sequences with members having pre-determined autocorrelation characteristics

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Publication number
DE102006017296A1
DE102006017296A1 DE200610017296 DE102006017296A DE102006017296A1 DE 102006017296 A1 DE102006017296 A1 DE 102006017296A1 DE 200610017296 DE200610017296 DE 200610017296 DE 102006017296 A DE102006017296 A DE 102006017296A DE 102006017296 A1 DE102006017296 A1 DE 102006017296A1
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Prior art keywords
training sequences
set
training
communication system
sequences
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DE200610017296
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German (de)
Inventor
Claudiu Krakowski
Hanguang Wu
Wen Dr. Xu
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Qualcomm Inc
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BenQ Mobile GmbH and Co oHG
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Priority to DE200610017296 priority Critical patent/DE102006017296A1/en
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Application status is Withdrawn legal-status Critical

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; Arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/0224Channel estimation using sounding signals
    • H04L25/0226Channel estimation using sounding signals sounding signals per se

Abstract

The invention relates to a method (400) for generating training sequences (402) for use in a communication system (100, 700) comprising the following steps:
Providing a first set of training sequences (104) with members (304) having predetermined autocorrelation properties and
Generating a second set of training sequences based on the first set of training sequences and a transformation matrix, wherein the members of the second set of training sequences have the same autocorrelation properties as the members. the first set of training sequences (104).
The invention further relates to a communication system comprising at least one transmitter and at least one receiver, and a method for using a training sequence in a communication system.

Description

  • The The invention relates to a method for generating training sequences for use in a communication system. The method comprises the steps of providing a first set of training sequences and generating a second set of training sequences on the first set of training sequences. The invention relates further comprising a communication system comprising at least one Transmitter and at least one receiver and a method of using a training sequence in one Communication system.
  • In Communication systems can be a signal transmission between a transmitter and a receiver by interference of other transmitters of the communication system and others Sources of electromagnetic radiation are disturbed.
  • Especially the so-called Gaussian Minimum Shift Keying (GMSK) modulation method of the Global System for Mobile Communication (GSM) and the so-called Phase Shift Keying (8-PSK) Modulation method, the so-called "Enhanced Data Rates for GSM Evolution" (EDGE) method is used causes intersymbol interference (ISI). Inter-symbol interference becomes through multiple transfer effects causes echoes to be transmitted earlier Transmission symbols later transmitted Disturb symbols. In a time-division multiplexing (CDMA) such as GSM means this, that one with a receiver communicating transmitter, which works slit in one time, one Communication in one, for another receiver disturbs reserved reserved time slot.
  • In addition will be the frequencies used for mobile communication in adjacent ones Network cells reused. Therefore, two adjacent transmitters possibly work simultaneously on the same frequency and interfere with each other.
  • Around these and other disorders to overcome the communication channel, should be from the recipient Channel equalization can be made to provide reliable communication performance sure. current Systems use so-called Trellis Code Modulation (TCM) methods for signal detection, such as so-called "Maximum Likelihood Sequence Estimators", for example based on a Viterbi algorithm. Such techniques require the determination an impulse response of the channel to determine a channel model, that the current transmission characteristics of the channel.
  • A Channel impulse response may be based on a training sequence, too called "Midamble", to be determined which is transmitted with a data frame according to the GSM standard. In GSM there There are eight different predetermined training sequences, too Training sequence codes (TSCs) or pilot symbols. one of these TSCs is transmitted with each so-called "normal burst" from a transmitter to a receiver. Similar Techniques are also used in other communication systems, for example, in code division multiple access (CDMA) systems.
  • Around To maximize the channel utilization, it is important to calculate Channel model and the channel compensation based on it. One approach is to use the responses of other broadcasters to the same Use communication channel, called co-channel users, in to include the calculation by having a common channel impulse response from two or more co-channel users is determined. Such methods are for example synchronized TDMA systems applied.
  • The quality the particular channel assessment depends on the cross correlation properties of the different Co-channel users used training sequences like this in the article "Interference Cancellation for EDGE via Two-User Joint Demodulation "by Abdulrauf Hafeez, Dennis Hui and Hueseyin Arslan during The 2003 VTC Autumn Conference was described. Allow current systems not always training sequences with optimal cross-correlation properties for co-channel users to use.
  • It is therefore an object of the present invention, methods and Systems for generating and using training sequences with good ones Describe correlation properties.
  • The The object is achieved by methods and devices according to patent claims 1, 4 and 8 solved.
  • According to a first embodiment of the invention, a method for generating training sequences for use in a communication system is provided. The method comprises the steps of Providing a first set of training sequences with members having predetermined autocorrelation properties and generating a second set of training sequences based on the first set of training sequences and a transformation matrix, the members of the second set of training sequences having the same predetermined autocorrelation properties as the members of the first set of training sequences ,
  • By generating the second set of training sequences There are more training sequences on the first set of training sequences available for communication. Therefore, interfering transmitters have a greater choice when selecting appropriate training sequences for communication with a receiver.
  • Provided a cross-correlation of at least one member of the first set of training sequences with at least one member of the second Amount of training sequences is less than a cross-correlation of the at least one member of the first set of training sequences with any other member of the first set of training sequences, can the assessment the channel properties are improved, resulting in higher data transfer rates results.
  • According to one Second embodiment of the invention is a communication system provided. The communication system includes at least one A transmitter adapted to have data frames comprising a training sequence a first set of training sequences, and at least one receiver, the is set up to have data frames comprising the training sequence to receive and cross-correlate the received training sequence to calculate with a predetermined part of the training sequence, a channel assessment for one Compute channel compensation. The transmitter is further adapted to Data frame having at least one additional training sequence to transmit generated based on the first set of training sequences and the same autocorrelation property as the training sequences having the first set of training sequences. The receiver is further arranged to have data frames comprising the at least an additional Receive training sequence and use it for channel estimation and to use channel equalization.
  • By that available provide a communication system with a transmitter and a receiver that are set up to both a first set of training sequences as well as to use at least one more training sequence the selection of training sequences to be used is increased. Therefore can the transmitter and the receiver choose between more exercise sequences to get the cross-correlation properties optimize the training sequence used.
  • Provided the transmitter is arranged to have a first data frame a first training sequence about to transmit a first antenna and a second data frame having a second training sequence over one to transmit the second antenna, and if the recipient configured to have the first and second data frames to receive the first and second training sequences and one joint channel assessment for one Channel equalization based on the received first and second To calculate training sequences, the channel compensation for the two channels be optimized.
  • According to one Third aspect of the invention is a method of use a training sequence in a communication system according to the second Embodiment of the invention disclosed. The method comprises the steps providing a first and a second set of training sequences according to the first Embodiment of the invention, the selection of a training sequence the first or the second set of training sequences, the generating and transferring a data frame comprising the selected training sequence the transmitter, receiving the transmitted Data frame comprising the selected training sequence the recipient, calculating a cross-correlation of the received training sequence with a predetermined portion of the selected training sequence to compute a channel model and channel equalization for decoding of data frames transmitted by the transmitter based on the calculated channel model.
  • Further Details and embodiments of the invention are specified in the subclaims.
  • The Invention will be described below with reference to an embodiment with reference to the drawings explained in more detail. In show the drawings:
  • 1 a communication system comprising a transmitter, a receiver and a source of interference,
  • 2 a plurality of adjacent cells of a mobile communication network,
  • 3 a data frame comprising a training sequence,
  • 4 a method for generating a second set of training sequences,
  • 5 Autocorrelation properties of a first training sequence of a first set of training sequences,
  • 6 Autocorrelation properties of eight training sequences of a second set of training sequences,
  • 7 a block diagram of a communication system used for common channel estimation and interference cancellation,
  • 8th improved bit error rates for joint channel estimation using two sets of training sequences,
  • 9 improved bit error rates for filter based channel estimation using two sets of training sequences.
  • 1 shows a communication system 100 , The communication system 100 has a transmitter 101 For example, a base station, a receiver 102 , for example a mobile station, and a source of interference 103 on.
  • The transmitter includes a first set of training sequences 104 and a second set of training sequences 105 , A signal modulator 106 the transmitter 101 is adapted to a training sequence of either the first set of training sequences 104 or the second set of training sequences 105 in a data frame and encode the data frame via a transmit antenna 107 transferred to.
  • The recipient 102 also includes the first set of training sequences 104 and the second set of training sequences 105 , The recipient 102 further comprises a signal demodulator 108 who is also a channel assessor 109 and a channel equalizer 110 includes. The signal demodulator 108 is with a receiving antenna 111 for receiving data frames sent by the sender 101 transferred.
  • The channel assessor 109 is adapted to establish a correlation between a training sequence contained in a received data frame and a portion of an associated training sequence of the first set of training sequences 104 or the second set of training sequences 105 to calculate. Based on the result of the cross-correlation, the channel estimator calculates 109 a channel model, that of the channel equalizer 110 used for channel compensation.
  • In practice, the recipient can 102 also with a modulator 106 and the transmitter 102 as well with a demodulator 108 be equipped so that a bidirectional communication is possible. However, such details are not in the interests of simplicity 1 contain.
  • The source of interference 103 indicates the first set of training sequences 104 and a signal modulator 112 which is set up to modulate data frames. Through the signal modulator 112 modulated and via a transmitting antenna 113 transmitted data frames of the source of interference 105 therefore comprise a training sequence from the first set of training sequences 104 ,
  • The source of interference 103 may be another base station or mobile station operating on the same communication channel as the transmitter 101 and the receiver 102 For example, on the same frequency or in the same time slot. Therefore, she is a co-channel user of the recipient 102 and the sender 101 , At the source of interference 103 however, it may also be another source or attenuator for electromagnetic radiation interfering with the communication channel.
  • 2 shows an arrangement of a communication network 200 comprising seven network cells 201 to 207 , The first network cell 201 has a base station that acts as a transmitter 101 acts. A mo Bilstation, as a receiver 102 acts and resides within the first network cell 201 is communicating with the base station on a communication channel.
  • If base stations or mobile stations in one of the six adjacent network cells 202 to 207 work, have to use the same channel for a data transmission, they act as a source of interference 103 for the first network cell 201 , In this case, co-channel users must use the seven network cells 201 to 207 use different training sequences to allow channel equalization.
  • The GSM standard describes eight different, predetermined training sequences. If any of the network cells 201 to 207 a different training sequence of the first set of training sequences 104 used according to the GSM standard, all but one training sequence are used in parallel. Therefore, there is little choice as to which training sequence is selected and used.
  • The upper part of the 3 shows a so-called "normal burst" according to the GSM standard. A data frame 300 has a header 301 followed by a first data part 302 , a first signaling part 303 , a training sequence 304 , a second signaling part 305 , a second data part 306 and a credits 307 on. The data frame 300 is from a protection period 308 followed, which is a separation of subsequent data frames 300 allows.
  • According to the GSM standard, the header includes 301 and the credits 307 always three bits set to the logical value "0". The first signaling part 303 and the second signaling part 305 each comprise a bit which indicates whether those in the first data part 302 and the second data part 306 transmitted data contain user data or signaling data. The first data part 302 and the second data part 306 are each 57 bits long.
  • The training sequence 304 has a length of 26 bits and is in the lower part of the 3 shown in detail. The training sequence 304 has a 16-bit middle part 309 and a leading and a subsequent, each five-bit long, cyclical continuation 310 and 311 of the middle section 309 on.
  • 4 shows a method 400 for generating a second set of training sequences 105 based on a first set of training sequences 104 and a transformation matrix 401 ,
  • The first set of training sequences 104 can, for example, the eight training sequences 304 according to the GSM standard. According to one embodiment of the invention, the training sequences 304 the first set of training sequences 104 Element by element with a 26-bit sequence comprising the second row of a Hadamard matrix of order 16 multiplied by a leading and trailing cyclic continuation of five bits in length at both ends.
  • The second set of training sequences 105 So it's created in two steps:
    • Generation of a 26-bit sequence in which the middle 16 bits from the second row of the Hadamard matrix of order 16 and each five bits at the beginning and at the end of the sequence form the cyclic continuation of the middle 16 bits. Alternatively, one can also invert the sign for each bit of the sequence at the same time. The resulting bit strings are:
      Figure 00110001
    • - An element-by-element multiplication of the 26-bit sequence with a training sequence 304 the first set of training sequences 104 results in an additional newly proposed training sequence 402 ,
  • By doing the same operation for each training sequence 304 the first set of training sequences 104 one obtains an associated second set of training sequences 105 whose members below the proposed training sequences 402 to be named. The second set of training sequences 105 is shown in Table 3:
  • Table 3: The second set of proposed training sequences 105.
    Figure 00110002
  • Figure 00120001
  • 5 shows a correlation between the middle part 309 and an associated complete training sequence 304 , the same middle part 309 the first training sequence 304 the first set of training sequences 304 having.
  • All training sequences 304 the first set of training sequences 104 according to the GSM standard have the property that they have a correlation maximum of 16 in the middle of the correlation function, which in 5 is shown.
  • This maximum is surrounded by five zeroes to each side of the maximum. That means that, provided the middle part 309 by 1 to 5 bits along the time axis with respect to the associated complete training sequence 304 is shifted, all bits are different. These properties are used by conventional GSM and EDGE receivers, respectively, in which a channel estimation based on a cross-correlation between a received training sequence 304 and the known 16-bit middle parts 309 is carried out.
  • According to the article "Optimum and Suboptimal Channel Estimation for the CDMA Mobile Radio System with Joint Detection" by W. Steiner and B. Jung, European Transaction and Telecommunications, Vol. 5, pp. 19-50, January 1994, the degradation of the Signal-to-noise-plus-interference ratio (SNIR) of a common channel estimation by a cross-correlation between the training sequence 304 calculated as follows d CE [dB] = 10log 10 ⌊1 + tr {(G H G) -1 }⌋ (1) where tr {} represents the trace of the template element and G is a training sequence matrix of the following form G = [G 1 G 2 ... G J ] (2)
    Figure 00130001
    where G k (l ≦ k ≦ j) for the k. training sequence 304 stands.
  • N is the length of the training sequence 304 and L is the length of the impulse response of the channel. In the following, the description for channel lengths L = 5 and L = 6 is limited because they are typically used in GSM channel equalization. Table 1 and Table 2 show the SNIR degradation for a common channel estimation of two channels containing different training sequences 304 the first lot of training sequences 104 , hereinafter referred to as GSM TSCs 304 , use. The pair of GSM TSC4 and GSM TSC5 results in the largest SNIR loss (d CE ≈ 6.3 dB for L = 5 and d CE ≈ 11.5 dB for L = 6). For other combinations of GSM TSCs 304 d CE varies from 2.1 dB to 5.4 dB for L = 5 and from 3.1 dB to 6.9 for L = 6.
  • Table 1: SNIR degradation of a common channel estimation of two channels using different GSM TSCs 304 at a maximum channel length of L = 5.
    Figure 00130002
  • Figure 00140001
  • Table 2: SNIR degradation of a common channel estimation of two channels using different GSM TSCs 304 with a maximum channel length of L = 6.
    Figure 00140002
  • Figure 00150001
  • Because of the small number of pairs of GSM TSCs 304 With large SNIR, degradation can not be prevented.
  • The correlation coefficient of the second set of training sequences 105 can be calculated as follows:
    Let S k (i) be the k. GSM TSC 304 (0 ≤ k ≤ 7), where i is the index of the GSM TSC 304 designated. Then the proposed k. TSC 402 are expressed as follows: S k (i) · (-1) i + 1 . The correlation coefficient ρ GSM between the total k. GSM TSC 304 and the middle part 309 is given by
    Figure 00150002
    where n is any displacement of the two sequences. It follows that the correlation coefficient ρ proposed between the total associated k. proposed TSC 402 and its middle part 309 as follows:
    Figure 00160001
  • In the above equation is the term
  • Figure 00160002
  • Therefore:
    Figure 00160003
  • Therefore, the absolute value of the correlation coefficient for the proposed second set of training sequences 105 the same as the standard set of GSM TSCs 104 except the sign reversal for odd indexes.
  • 6 shows the autocorrelation properties of the proposed training sequences 402 the second set of training sequences 105 , Like from the 6 It can be seen that all eight have training sequences 402 the second set of training sequences 104 the same autocorrelation properties as the training sequences 304 the first set of training sequences 104 according to the GSM standard. This means that they have a maximum of 16 for the cross-correlation of the middle 16 bits 309 the training sequence 402 with the entire training sequence 402 which is surrounded by five zeros on each side. Therefore, they can be used for channel estimation in the same way and with the same success as the first set of training sequences 104 be used.
  • By generating a second set of training sequences 105 according to the in 4 A total of 16 training sequences are shown 304 and 402 for channel estimation available. Therefore, own a receiver 102 and a transmitter 101 a greater choice when choosing a particular training sequence 304 or 402 for communication.
  • Furthermore, a common channel estimation based on a training sequences 304 the first set of training sequences 104 and a second training sequences 402 the second set of training sequences 105 lower SNIR losses, resulting in improved channel estimation.
  • Tables 4 and 5 show the SNIR degradation of a common channel estimate of two channels using different standard GSM TSCs 304 and proposed TSCs 402 , It can be seen that d CE ≈ 2.3 dB for the combination of GSM TSC0 304 and the proposed TSC0 402 for the case L = 5 and d CE ≈ 3.0 dB for the case L = 6.
  • Table 4: SNIR degradation of a common channel estimation of two channels using GSM TSCs 304 and a proposed TSCs 402 at a maximum channel length of L = 5.
    Figure 00170001
  • Figure 00180001
  • Table 5: SNIR degradation of a common channel estimation of two channels using a GSM TSCs 304 and a proposed TSCs 402 with a maximum channel length of 6.
    Figure 00180002
  • 7 shows a block diagram for a two-channel communication system 700 for common channel estimation and interference compensation. This in 7 shown system can be used for so-called "single antenna co-channel interference cancellation" (SAIC).
  • A first antenna 701 transmits a first signal on a first communication channel 702 , A second antenna 703 transmits a second signal on a second channel 704 , Both channels are supplemented by white noise (added white gaussian noise - AWGN) 705 disturbed and disturbed on both sides. They are shared by a receptionist 706 receive.
  • A channel assessor 109 determines a common channel estimation for both channels 703 and 704 and controls a channel equalizer 110 accordingly. At the channel equalizer 110 For example, it may be an electronically tunable filter. The received and filtered signals then become a signal detector 707 for example, for the detection and extraction of data parts 302 and 306 forwarded.
  • The two channels 702 and 704 can be from different co-channel receivers 102 be used. However, especially in high-speed data transmission systems such as EDGE, it is also possible to have a single receiver 102 set up to set up data on two channels 702 and 704 receive in parallel, for example, to increase a so-called downlink data rate.
  • The combination of the proposed TSC amount 105 with the standard TSC quantity 104 can either be for a shared detection based receiver 102 or an interference cancellation receiver 102 be used. If the transmitter 101 , ie the desired channel user, and the source of interference 103 two TSCs 304 and 402 Using low SNIR degradation for common channel estimation, signal detection will benefit from the relatively high quality of channel estimation. This results in a better recognition or separation of the desired signal and the source of interference 103 ,
  • 8th shows simulation results for common detection of the transmitter 101 and the source of interference 103 through the receiver 102 for different combinations of TSC 304 and 402 , The combination of GSM TSC4 304 and GSM TSC5 304 corresponds to the worst possible case for joint detection. By using the combination of GSM TSC4 304 and the proposed TSC5 402 a big performance gain can be achieved.
  • If the transmitter 101 and the source of interference 103 the same GSM TSC 104 they can not be separated at all. This can be avoided by including the associated proposed TSC 405 for the source of interference 103 or the transmitter 101 is used as indicated by the illustrated curve for GSM TSC0 304 and the proposed TSC0 402 is shown. Its bit error rate (BER) performance is even slightly better than the best possible combination with the exclusive use of training sequences 304 the first lot 105 (GSM TSC0 and GSM TSC2) according to the GSM standard.
  • In cases where information about the source of interference 103 used TSC 304 or 402 is available, filter-based interference cancellation techniques may be used in conjunction with correlation-based channel estimation techniques by the receiver 102 be used. If a good combination of TSC 304 and 402 as shown in Table 4 or 5 can be used because of the low cross-correlation properties of the TSC 304 and 402 an improvement in low SNIR regions can be observed as in 9 is shown.
  • The second set of training sequences 105 in combination with the first set of training sequences 104 is also suitable for communication systems 700 with so-called "trans mission diversity" transmission systems or so-called Multiple Input Multiple Output (MIMO) capabilities. For example, in a 2 × 1 or 2 × 2 system 700 that is a system 700 with two correlated transmit antennas 701 and 703 and one or two receiver antennas 111 , a transmitter 101 a standardized GSM TSC 304 for transmission with the first antenna 701 use and an associated proposed TSC 402 for the second antenna 703 use. Due to the low cross-correlation properties of the associated TSCs 304 and 402 can be a good quality for channel estimation for each of the individual channels 702 and 703 can be expected, which allows a better signal detection on the receiver side.
  • Of course, the second set of training sequences 105 not be recalculated every time you use it. Instead, both the first and the pre-calculated second set of training sequences may be used 104 and 105 in a memory of the transmitter 101 or the recipient 102 be filed.
  • Although the communication systems 100 and 700 have been described as part of a cellular network, other communication systems using a common communication medium, such as a common cable, may benefit from the methods and systems described in the following claims.

Claims (9)

  1. Procedure ( 400 ) for generating training sequences ( 402 ) for use in a communication system ( 100 . 700 ), comprising the steps: - providing a first set of training sequences ( 104 ) with members ( 304 ) having predetermined autocorrelation properties, and - generating a second set of training sequences ( 105 ) based on the first set of training sequences ( 104 ) and a transformation matrix ( 401 ), the members ( 402 ) of the second set of training sequences ( 105 ) the same autocorrelation properties as the members ( 304 ) of the first set of training sequences ( 104 ).
  2. Method according to claim 1, characterized in that the transformation matrix ( 401 ) based on a Hadamard matrix.
  3. Method according to claim 2, characterized in that a cross-correlation of at least one member ( 304 ) of the first set of training sequences ( 104 ) with at least one member ( 402 ) of the second set of training sequences ( 105 ) is less than a cross-correlation of the at least one member ( 304 ) of the first set of training sequences ( 104 ) with any other member ( 304 ) of the first set of training sequences ( 104 ).
  4. Communication system ( 100 . 700 ), comprising - at least one transmitter ( 101 ), which is adapted to 300 ) comprising a training sequences ( 304 ) a first set of training sequences ( 104 ), and - at least one receiver ( 102 ), which is adapted to 300 ) comprising the training sequences ( 304 ) and a cross-correlation of the received training sequences ( 304 ) with a predetermined part ( 309 ) of the training sequences ( 304 ) to determine channel estimation for channel equalization, characterized in that - the transmitter ( 101 ) is set up to use data frames ( 300 ) comprising at least one additional training sequences ( 402 ), the additional training sequences ( 402 ) based on the ers th amount of training sequences ( 104 ) and the same autocorrelation properties as the training sequences ( 304 ) of the first set of training sequences ( 104 ), and - the recipient ( 102 ) is set up to use data frames ( 300 ) comprising the at least one additional training sequences ( 402 ) and to use for channel estimation for channel equalization.
  5. Communication system ( 700 ) according to claim 4, characterized in that - the transmitter ( 101 ) functional with a first antenna ( 701 ) and a second antenna ( 703 ) and is adapted to a first data frame ( 300 ) comprising a first training sequences ( 304 . 402 ) via the first antenna ( 701 ) and a second data frame ( 300 ) comprising a second training sequences ( 304 . 403 ) via the second antenna ( 703 ) and - the consignee ( 102 ) is adapted to the first and second data frames ( 300 ) comprising the first and the second training sequences ( 304 . 402 ) and based on the received first and second training sequences ( 304 . 402 ) to calculate a common channel estimate for channel equalization.
  6. Communication system ( 700 ) according to claim 5, characterized in that - the first training sequences ( 304 ) on the first set of training sequences ( 104 ) and - the second training sequences ( 402 ) the at least one additional training sequences ( 402 ).
  7. Communication system ( 100 . 700 ) according to one of claims 4 to 6, characterized in that the communication system ( 100 . 700 ) a mobile communication network ( 200 ), in particular a GSM network.
  8. Method for using a training sequence ( 304 ) a first or a second set of training sequences ( 104 . 105 ) according to one of claims 1 to 3 in a communication system ( 100 . 700 ) according to one of claims 4 to 7, comprising the steps of: - selecting a training sequence ( 304 . 402 ) of the first or the second set of training sequences ( 104 . 105 ), - generating and transmitting a data frame ( 300 ) comprising the selected training sequence ( 304 . 402 ) by the transmitter ( 101 ), - receiving the transmitted data frame ( 300 ) comprising the selected training sequence ( 304 . 402 ) by the recipient ( 102 ), - calculating a cross-correlation between the received training sequences ( 304 . 402 ) with a predetermined part ( 309 ) of the selected training sequences ( 304 . 402 ) to perform channel estimation, and - performing channel equalization to decode data frames ( 300 ) transmitted by the transmitter ( 101 ) based on the calculated channel estimate.
  9. Method according to claim 8, characterized in that - the communication system ( 100 . 700 ) a mobile radio network ( 200 ) and - the decoding and encoding of data frames ( 300 ) according to the EDGE standard.
DE200610017296 2006-04-12 2006-04-12 Training sequence production method for use in e.g. code division multiplex system, involves providing quantity of training sequences with members having pre-determined autocorrelation characteristics Withdrawn DE102006017296A1 (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5619503A (en) * 1994-01-11 1997-04-08 Ericsson Inc. Cellular/satellite communications system with improved frequency re-use
WO2002009375A1 (en) * 2000-07-21 2002-01-31 Telit Mobile Terminals S.P.A. Estimation of the downlink channel for umts
US7082159B2 (en) * 2000-11-29 2006-07-25 Telefonaktiebolaget Lm Ericsson (Publ) Methods and arrangements in a telecommunications system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5619503A (en) * 1994-01-11 1997-04-08 Ericsson Inc. Cellular/satellite communications system with improved frequency re-use
WO2002009375A1 (en) * 2000-07-21 2002-01-31 Telit Mobile Terminals S.P.A. Estimation of the downlink channel for umts
US7082159B2 (en) * 2000-11-29 2006-07-25 Telefonaktiebolaget Lm Ericsson (Publ) Methods and arrangements in a telecommunications system

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