JP2013207355A - Receiving device and radio communication control method in ofdm transmission system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method for generating an optimal CQI in an OFDM radio transmission system.SOLUTION: A signal including a data signal and a reference signal is received from a transmission device, channel quality and noise power density are estimated on the basis of the reference signal, and an instantaneous SINR per OFDM subcarrier is calculated from the estimated channel quality and noise power density. The instantaneous SINR is converted into a mutual information quantity (MIB) per encoded bit, and communication quality metric (LQM) based on a mean value in a transport block of the MIB is calculated. A combination of a modulation scheme and a coding rate (MCS) which makes expected throughput the largest is obtained, and an index indicating the obtained MCS is transmitted to the transmission device as a channel quality indicator (CQI). A reference table indicates relation between an LQM and transmission quality of each MCS, or relation between an LQM and the MCS which can obtain the maximum throughput at the LQM.

Description

  The present invention relates to a receiving apparatus and radio communication control method for an OFDM transmission system, and more particularly to a receiving apparatus and radio communication control for generating a channel quality indicator (CQI) in an OFDM transmission system that performs adaptive modulation and coding rate control (AMC). Regarding the method.

  With the recent development and spread of the Internet, it has become possible to easily obtain various information, data such as music and moving images by accessing various sites. This situation is the same in wireless communication, and it is easy to access the Internet and download various multimedia contents and perform streaming playback in mobile wireless communication such as mobile phones. Became.

  In particular, with the recent spread of smartphones, wireless Internet access has increased, and the amount of data traffic has increased rapidly. Along with this, problems such as tight network lines have arisen. To this end, mobile phone operators are working on various attempts to increase wireless capacity, such as speeding up wireless communication and improving frequency utilization efficiency.

  As one of speeding up of data communication in a mobile phone, a long term evolution (LTE) service of a third generation mobile communication system has been started. In LTE, for example, in the downlink, communication with a 20 MHz bandwidth and a peak rate of 100 Mbps or more is assumed. In LTE, various technologies are employed to realize high-speed data communication.

  LTE uses an OFDM (Orthogonal Frequency Division Multiplexing) transmission method, particularly in downlink communication. This OFDM transmission scheme has advantages such as being strong against intersymbol interference and fading accompanying multipath transmission and having high frequency utilization efficiency.

  Further, in the MIMO-ODFM transmission in which the above-mentioned OFDM transmission is combined with multiple-input multiple-output (MIMO) transmission, signal processing is performed in a composite region of a frequency domain and a spatial domain, so communication quality and communication capacity are further improved. It becomes possible to improve. In LTE, MIMO-ODFM transmission with a maximum of four transmission antennas is assumed.

  Further, in LTE, an adaptive modulation and coding rate control (AMC) technique that adaptively changes a transmission rate of a transmission signal according to a link state between a base station and a mobile station is applied. AMC is generally used for data transmission in the downlink with a base station as a transmission device and a mobile station as a reception device.

  In AMC, a receiving apparatus measures a transmission state of a radio propagation path through which a signal is transmitted, and reports it to the transmitting apparatus. The transmission apparatus transmits a data signal at a transmission rate suitable for the reported transmission state. For example, when the transmission state is bad, a low transmission rate is selected so that the reception error at the receiving apparatus is less than or equal to a certain error rate. When the transmission state is good, a high transmission rate is selected to improve the throughput. Thus, by appropriately selecting the most suitable transmission rate for the radio propagation path that changes with time, efficient data transmission is performed and throughput is improved. Here, the wireless propagation path means a wireless connection path between the target transmission apparatus and reception apparatus, and can be represented by a transmission path, a link, a channel, or the like, for example.

  The transmission rate in AMC is determined by a combination of a modulation scheme and a coding rate (MCS: Modulation and Coding rate Set). In the receiving apparatus, as a measurement value of the transmission path quality, a signal-to-interference power ratio (SIR) or a signal-to-interference signal power ratio (SINR) on the receiving side is used. Interference plus Noise power ratio) is used. In addition, instead of reporting the measured SIR or SINR value to the transmitting apparatus, the receiving apparatus selects an MCS suitable for transmission from these measured values, and sets an index representing the appropriate MCS as a channel quality indicator (CQI: Channel Quality Indicator) is fed back to the transmitter.

  The transmitting apparatus receives the CQI from the receiving apparatus, selects an MCS corresponding to the CQI, encodes and modulates transmission data using the newly selected MCS, and transmits the encoded data to the receiving apparatus. Here, for the sake of simplicity, the index representing the MCS and the value of the CQI are described in a completely one-to-one correspondence. However, the optimum MCS indicated by the CQI and the actual MCS that can be transmitted are limited due to restrictions on the block size (transport block size) of information bits that can be selected depending on the specification or implementation of the system as in an actual system such as LTE. May not match exactly. In such a system, since the total number of MCS patterns that can be used in the transmission apparatus is larger than the total number of CQI patterns, it is not always necessary to have a one-to-one correspondence between the MCS index and the CQI. Therefore, the transmitting apparatus may use a method of notifying index information of the actually used MCS to the receiving apparatus using the control channel.

  The receiving apparatus has a relationship between the SINR of the propagation path and the MCS that can obtain the maximum throughput in the form of a reference table. With this reference table, the optimum MCS can be easily selected from the measured SINR.

  The throughput characteristics or block error rate characteristics with respect to SINR, which are required when creating the above reference table, are typically computer simulations assuming typical or specific propagation environments, actual base station apparatuses and mobile stations. Obtained by actual measurement using an apparatus. However, the propagation environment in which the mobile phone is actually used is different from the propagation environment used when creating the reference table. If the propagation environment is different, the obtained throughput may be different even if the average SINR in the propagation path is the same. For example, when frequency selective fading is large, SINR variance between OFDM subcarriers is also large, and the average block error rate is increased.

  Also, in a system using MIMO transmission, the required SINR value for achieving a certain required transmission rate differs depending on the transmission scheme (for example, transmission / reception diversity scheme, spatial multiplexing scheme, precoding scheme, etc.) and the number of antennas used for transmission and reception. Further, in a system to which cooperative MIMO in which a plurality of transmitting stations cooperate to perform MIMO transmission as a transmission method is applied, the number of antennas at the time of single transmitting station MIMO transmission and cooperative MIMO transmission is different (used). Therefore, even if the average SINR per receiving antenna is the same, the throughput obtained depends on the transmission method.

  The measurement accuracy of SINR in the receiving apparatus is also affected by the propagation environment. For example, when the receiving device is in a moving vehicle, the measurement accuracy is expected to deteriorate as the moving speed increases.

  From the above, in order to realize the optimum AMC in the MCS selection criterion method that simply uses the SINR measured on the receiving device side, there is a reference table used for MCS selection for each actually applied environment. It becomes necessary. Assuming the case where the actual propagation environment and the propagation environment assumed in the reference table used for MCS selection are different, or in the case of a system that switches a plurality of transmission methods, the reference table used for MCS selection is the influence of the propagation environment, It is desirable to use an MCS selection criterion that is not influenced in principle by the transmission scheme and antenna configuration in MIMO transmission.

  Further, considering that the measured SINR includes an error, when an MCS is selected from a lookup table based on the measured SINR value, the MCS may not necessarily be optimal. If the selected MCS transmission rate is greater than the appropriate MCS transmission rate, the block error rate is expected to increase. On the other hand, when the transmission rate of the selected MCS is small, the block error rate is almost zero, but high throughput cannot be obtained. In these cases, since the characteristics of AMC deteriorate, a countermeasure is desired.

  As a countermeasure against degradation of AMC characteristics, a method of correcting the CQI value according to the block error rate is known (for example, Patent Document 1). In the above, the target value of the block error rate is compared with the actually measured block error rate. If the actual block error rate is worse than the target value, for example, the CQI value is reduced by 1 and a lower MCS is selected. Like to do. Conversely, when the actual block error rate is higher than the target value, the CQI value is increased by 1, and a higher MCS is selected. That is, a more optimal MCS is selected by controlling the block error rate to be close to the target value.

JP 2009-267441 A

  However, the method of Patent Document 1 is not a fundamental solution for dealing with a situation where the actual propagation environment is different from the propagation environment assumed in the reference table used for MCS selection. In addition, when measuring the block error rate, a certain amount of measurement interval is required, but the propagation state may vary during that time.

  Further, the CQI is a discrete value, and includes cases where the propagation path state is good and bad even with the same CQI. For this reason, if the CQI is directly corrected, there is a possibility that the CQI is corrected even if it is not necessary to be corrected.

  An object of the present invention is to provide a CQI generation method for optimizing throughput characteristics in various antenna configurations and propagation environments in an OFDM wireless transmission system using adaptive modulation / coding rate control.

  It is another object of the present invention to provide a CQI adjustment method for reducing characteristic deterioration due to propagation path estimation error.

  The present invention is a wireless communication control method in a receiving apparatus of an OFDM transmission system, the step of receiving a signal including a data signal and a reference signal from a transmitting apparatus, and channel quality and noise power density based on the reference signal. Estimating the instantaneous SINR for each OFDM subcarrier from the estimated channel quality and noise power density, converting the instantaneous SINR into mutual information (MIB) per coded bit, and Based on the step of calculating the communication quality metric (LQM) based on the average value of the mutual information amount per coded bit within the transport block, and the reference table and the calculated communication quality metric, the predicted throughput is maximized. Acquiring a combination of modulation scheme and coding rate (MCS); Transmitting an index indicating the MCS as a channel quality indicator (CQI) to the transmission device, and the reference table includes a relationship between a communication quality metric and a transmission quality of each MCS, or a communication quality metric and The communication quality metric shows the relationship with the MCS that provides the maximum throughput.

  Further, the present invention provides a step of checking whether or not a block error has occurred for each transport block of the data signal, and if there is no block error in the checking step, the SINR offset value is determined by the first correction value. When there is a block error, the method further includes a step of decreasing the SINR offset value by a second correction value, and a step of correcting the instantaneous SINR by the SINR offset value.

  Furthermore, the present invention is a receiver for an OFDM transmission system, a receiver that receives a signal including a data signal and a reference signal from a transmitter, and estimates channel quality and noise power density based on the reference signal. Channel estimator, SINR calculator for calculating instantaneous SINR for each OFDM subcarrier from the estimated channel quality and noise power density, and converting the instantaneous SINR into mutual information (MIB) per coded bit A communication quality metric calculation unit that calculates a communication quality metric (LQM) based on an average value of the mutual information amount per coded bit in the transport block, a reference table, and the calculated communication quality metric. MC that obtains the combination of modulation scheme and coding rate (MCS) that maximizes the predicted throughput A determination unit, and a CQI generation unit that transmits an index indicating the acquired MCS as a channel quality indicator (CQI) to the transmission device, and the reference table includes a communication quality metric and transmission quality of each MCS. The relationship or the relationship between the communication quality metric and the MCS that can obtain the maximum throughput in the communication quality metric is shown.

  In the receiving apparatus and the radio communication control method for generating the channel quality indicator (CQI) according to the present invention, the average mutual information per bit (MMIB) is used in the OFDM radio transmission system using adaptive modulation / coding rate control. Thus, it is possible to easily generate channel quality indicators suitable for various propagation environments and various antenna configurations for transmission and reception based on transmission characteristics in a specific propagation environment. Furthermore, the adjustment of the channel quality index according to the present invention makes it possible to suppress degradation from the ideal throughput characteristics even when an error is included in the channel estimation.

It is a figure explaining the principle of AMC. It is a figure which shows an example of a MIMO transmission system. It is a figure which shows an example of the cooperation MIMO transmission system between base stations. It is a figure which shows the structure of the master base station in the cooperation MIMO transmission system between base stations. It is a figure which shows the structure of the slave base station in the cooperation MIMO transmission system between base stations. It is a figure which shows the resource element mapping of the radio | wireless frame transmitted from a master base station. It is a figure which shows the resource element mapping of the radio | wireless frame transmitted from a slave base station. It is a figure which shows the structure of the mobile station in the cooperation MIMO transmission system between base stations. It is a figure which shows the relationship between reception SINR and the mutual information amount per bit. It is a figure which shows the relationship between the instantaneous average mutual information content and block error rate in QPSK. It is a figure which shows the relationship between the instantaneous average mutual information content in 16QAM, and a block error rate. It is a figure which shows the relationship between the instantaneous average mutual information content and block error rate in 64QAM. It is a figure which shows the relationship between the reception SINR and throughput in AMC. It is a figure which shows the block error rate characteristic at the time of applying the CQI adjustment method by this invention. It is a figure which shows the throughput characteristic at the time of applying the CQI adjustment method by this invention.

  Hereinafter, a reception apparatus and a radio communication control method for generating a channel quality indicator will be described with reference to the drawings. However, it should be understood that the invention is not limited to the drawings or the embodiments described below.

  First, adaptive modulation / coding rate control (AMC), which is the basis of the present invention, will be described.

  FIG. 1 shows an overview of MCS selection in the receiving apparatus. The horizontal axis in FIG. 1 indicates the SINR of the propagation path measured by the receiving apparatus. The vertical axis indicates the throughput predicted by each MCS with respect to the SINR of the propagation path. Assuming MCS 1-3, the respective throughput characteristics are shown. In each MCS, the lower the SINR, the lower the throughput. On the other hand, the higher the MCS number, the higher the transmission rate at the time of transmission, and thus the higher the throughput and, at the same time, the higher the SINR required in the propagation path.

The transmission rate (or maximum throughput) in MCS 1 is assumed to be Max_tp (MCS 1). On the other hand, the SINR of the propagation path is SINR (k), and the average block error rate of MCS 1 in SINR (k) is BLER (k) _{MCS 1} . Then, the predicted throughput tp (k) _{MCS 1} of _{MCS 1} can be obtained by Max_tp (MCS 1) × (1−BLER (k) _{MCS 1} ). That is, if the block error rate is 0, the throughput is the maximum throughput obtained in MCS 1, which matches the transmission rate. When the block error rate is 1, the throughput is 0.

  As shown in FIG. 1, when the SINR of the propagation path is low, MCS 1 having the lowest transmission rate is selected. When the propagation path state is improved and the SINR becomes high, the MCS is changed to one higher in the number at the position where the predicted throughput characteristics between the MCSs intersect (for example, in SINR (t1), from MCS 1 to MCS 2). ). As described above, by selecting an MCS that provides higher throughput in accordance with the SINR of the propagation path, more efficient wireless data transmission can be performed as indicated by the dotted line A in FIG. If the SINR of the currently used channel is lower than SINR (t1), MCS 1 is selected. Further, when the SINR is between SINR (t1) and SINR (t2), selecting MCS 2 can provide a higher throughput than selecting MCS 1. However, if MCS 3 is selected in this range, the block error rate increases and the throughput deteriorates conversely.

  In the receiving apparatus, for example, when it is determined that MCS 1 is optimal with respect to the current SINR, an index representing MCS 1, for example, 1 is fed back to the transmitting apparatus as CQI. In the transmitting apparatus, based on the CQI transmitted from the receiving apparatus, if the current MCS and the MCS corresponding to the received CQI are different, the MCS is changed.

  If the SINR is very low, even if MCS 1 that is the minimum MCS is selected, the block error rate may increase and good throughput may not be obtained. In such a situation, a technique such as repetition for improving the coding gain by repeatedly transmitting data can be applied, but it is not considered here.

  Next, a system to which the present invention is applied will be described. However, the system described here is one example.

  In a wireless communication system, there is a MIMO (Multiple Input Multiple Output) transmission system that uses a plurality of antennas for transmission between transmitting and receiving apparatuses in order to improve the throughput of the entire cell. In this MIMO transmission method, spatial multiplexing can be performed by transmitting different data from a plurality of antennas on the transmission side. If the number of antennas on the receiving side is greater than or equal to the number of antennas on the transmitting side, spatial multiplexing for the number of antennas on the transmitting side is possible.

  As a technique for improving throughput or improving communication quality in a mobile station existing at a cell boundary (generally, a point farthest from the base station in the cell), a plurality of base stations There is inter-macro diversity technology. In this method, a plurality of base stations transmit the same signal to a mobile station at a cell boundary in synchronization, thereby performing transmission diversity across the plurality of base stations.

  As a technology in which the above-described macro diversity technology between multiple base stations is applied to MIMO transmission, there is multiple base station cooperative MIMO transmission in which a plurality of base stations perform radio transmission in synchronization with each other. In multi-base station cooperative MIMO, a propagation path between a transmission antenna in a plurality of cooperating base stations and a reception antenna of a mobile station near a cell boundary can be regarded as one integrated MIMO radio propagation channel. By using such a MIMO radio propagation path, it is possible to improve downlink channel capacity.

  Here, on the premise of OFDM transmission, consider a multi-base station cooperative MIMO-OFDM transmission system that performs multi-base station cooperative MIMO transmission.

  First, general MIMO transmission will be described with reference to FIG. Reference numeral 11 in FIG. 2 is a base station that is a transmitting station, 12 is a transmitting / receiving device of the base station, 13 is a base station antenna, 14 is a mobile station that is a receiving station, 15 is a transmitting / receiving device of the mobile station, 16 is a mobile station antenna Indicates. Reference numeral 17 denotes a mobile communication network, 18 denotes a core network equipment (CNE), and 19 and 20 denote network relay nodes. Data for downlink transmission is sent from the CNE 18 to the base station 11 via the relay node 20.

  FIG. 2 shows 2 × 2 MIMO in which the number of transmitting antennas in the base station 11 is 2 and the number of receiving antennas in the mobile station 14 is 2. However, the number of transmitting antennas and the number of receiving antennas are not limited to two. For example, in the LTE system, a maximum of 4 × 4 MIMO is assumed. In addition, here, a downlink in which a signal is transmitted from the base station is assumed, but MIMO transmission can also be performed in the uplink.

  First, the signal d (k) is transmitted from the base station antenna 13 and received by the mobile station antenna 16. The channel matrix of the radio propagation path between the base station antenna 13 and the mobile station antenna 16 is denoted by H (k). Here, k represents a subcarrier number in OFDM transmission. The mobile station 14 measures the transmission state of the propagation path from the received signal, and feeds back the result to the base station 11 as CQI.

  Next, a multi-base station cooperative MIMO transmission system will be described with reference to FIG. In FIG. 3, reference numeral 11 is a base station BS # 1, 12 is a transmitting / receiving device of the base station BS # 1, 13 is a base station antenna of the base station BS # 1, 22 is a base station BS # 2, and 23 is a base station BS # 2 is a base station antenna of the base station BS # 2, 14 is a mobile station, 15 is a mobile station transceiver device, and 16 is a mobile station antenna. Reference numeral 17 denotes a network between base stations, 18 denotes a core network device, and 19, 20 and 21 denote network relay nodes.

  In FIG. 3, signals are transmitted from the two base stations 11 and 22 to the mobile station 14 located in the vicinity of the cell boundary. However, the number of base stations performing cooperative MIMO can be more than two. When the number of base stations is 2, one base station is a master base station and the other is a slave base station. Here, the master base station is a base station that has been communicating with the mobile station alone before the mobile station enters the multi-base station cooperative MIMO communication state. The slave base station corresponds to a handoff destination base station when the mobile station is moving. In FIG. 3, base station BS # 1 (11) is a master base station, and base station BS # 2 (22) is a slave base station.

  In FIG. 3, two base stations 11 and 22 and a mobile station 14 each have two antennas. When these two base stations synchronize their transmission timings and perform radio transmission to the mobile station in a coordinated manner, radio propagation paths between the two base station antennas of the two base stations and the two mobile station antennas Can be regarded as one integrated 4 × 2 MIMO propagation path.

A signal d ⁽¹⁾ (k) is transmitted from the base station antenna 13 of the base station BS # 1, and a signal d ⁽²⁾ (k) is transmitted from the base station antenna 24 of the base station BS # 2. Received by antenna 16. In this case, the channel matrix of the radio propagation path between the base station antenna 13 and the mobile station antenna 16 is H ⁽¹⁾ (k), and the channel matrix of the radio propagation path between the base station antenna 24 and the mobile station antenna 16 Are denoted by H ⁽²⁾ (k), respectively.

  The mobile station 14 measures the propagation path quality from the received signal and transmits the result as a CQI to the base station. In coordinated MIMO, the mobile station 14 measures signals from the two base stations 11 and 22 separately and creates a CQI for each base station. The mobile station 14 collectively transmits the CQIs for the two base stations to the master base station 11. The master base station 11 extracts the CQI for the slave base station from the transmitted CQI information and transmits it to the slave base station 22 via the inter-base station network 17. Each base station selects a corresponding MCS based on the notified CQI.

  FIG. 4 shows a block diagram of the transmitter / receiver 12 of the master base station 11. 4, reference numeral 31 is a data signal, 32 is a serial-parallel converter (S / P), 33 is an encoder and modulator, 34 is a downlink control signal generator, 35 is a reference signal generator, and 36 is multiplexed. , 37 is an RF transmitter, 38 is an RF receiver, 39 is a CQI receiver, 40 is an MCS # 1 selector, 41 is an MCS # 2 selector, and 42 is a multiplexer.

  The master base station 11 receives the data signal 31 for the mobile station at the cell boundary from the core network device 18. The data signal 31 includes a data signal transmitted from the master base station and a data signal transmitted from the slave base station. In the serial-parallel converter 32, two transport blocks (TB: Transport Block), TB Disassembled into # 1 and TB # 2. TB # 1, which is a data signal for the master base station, is sent to the encoder / modulator 33. TB # 2, which is the slave base station data signal, is sent to the multiplexing unit.

  In the encoder / modulator 33, a CRC code is assigned to TB # 1. The CRC code is used for block error detection in the mobile station receiver. Further, TB # 1 is subjected to channel error correction coding, modulation, and precoding. Coding and modulation are performed by MCS based on CQI fed back from the mobile station.

  The CQI receiving unit 39 extracts the CQI from the uplink signal received by the RF receiving unit 38. Further, the MCS # 1 selection unit 40 extracts the MCS (MCS # 1) for the master base station (BS # 1), and the MCS # 2 selection unit 41 extracts the MCS (for the slave base station (BS # 2)). MCS # 2) is extracted. The encoder / modulator 33 performs encoding and modulation using the MCS (MCS # 1) sent from the MCS # 1 selector 40.

  The data signal processed by the encoder / modulator 33, the reference signal generated by the reference signal generator 35, and the downlink control signal generated by the downlink control signal generator 34 are multiplexed by the multiplexing unit 36. . The downlink control signal includes MCS (MCS # 2) index information used in the slave base station in addition to MCS (MCS # 1) index information used in the master base station. The signal multiplexed by the multiplexing unit 36 is converted into an RF signal by the RF transmission unit 37 and transmitted from the base station antenna 13.

  The multiplexing unit 42 multiplexes TB # 2 of the two TBs and MCS index information (MCS # 2) used for modulation of the TB # 2. The multiplexed MCS index information for the data signals TB # 2 and TB # 2, and the timing information for inter-base station synchronization with the master base station are transferred to the slave base station 22 through the inter-base station network 17. .

  FIG. 5 shows a block diagram of the transmitting / receiving device 23 of the slave base station 22. In this figure, reference numeral 51 denotes a demultiplexer, 52 denotes an encoder / modulator, 53 denotes a reference signal generator, 54 denotes a multiplexer, and 55 denotes an RF transmitter. The demultiplexer 51 separates the data signal and the control signal transmitted through the inter-base station network 17. The encoder / modulator 52 performs signal processing of the data signal. The signal processing is the same as the processing performed by the encoding and modulator 33 of the master base station. The signal signal subjected to signal processing is transmitted from the base station antenna 24 by multiplexing the reference signal.

  In the system assumed here, the coded and modulated signals in the master and slave base stations are subjected to space frequency block coding (SFBC) and are transmitted from the two antennas of each base station. Sent.

  Each base station transmits a reference signal for performing channel estimation on the receiving side together with the data signal. FIG. 6 illustrates a method of mapping resource elements to reference signals in the master base station. In order to ensure high channel estimation accuracy on the receiving side, cell-specific and antenna-specific reference signals are used, and the reference signals are orthogonal to each other in the time domain and the frequency domain, respectively. FIG. 7 shows a reference signal mapping method in the slave base station. Note that the mapping method shown here is just one example.

  Here, a signal processing method in the mobile station will be described using a block diagram of the transmission / reception device 15 of the mobile station 14 shown in FIG. 8, reference numerals 61 and 62 are demultiplexing units, 63 is a downlink control signal decoder, 64 is a channel estimator, 65 is a spatial filter coefficient generator, 66 is a spatial filter for signal separation and synthesis, and 67 is Post-processing SINR calculator, 68 and 69 are channel log likelihood ratio generators, 70 and 71 are soft decision error correction decoders, 72 is a MMIB (Mean Mutual Information per coded Bit) calculator, 73 is a CQI calculator, 74 75 is a CRC check, 76 and 77 are decoded data, 78 is a lookup table (lookup table), 79 is an uplink control signal generator, 80 is an uplink transmitter, and 81 is a duplexer.

  The two receiving antennas 16 receive signals transmitted from the master base station and the slave base station. The received signals are demultiplexed into data signals, control signals, and reference signals in demultiplexing units 61 and 62, respectively.

  The control signal is decoded by a downlink control signal decoder 63 that performs control symbol decoding, and a control signal including an MCS index is obtained. The MCS index is sent to the spatial filter 66 and the channel log likelihood ratio generators 68 and 69 for separation / combination and demodulation of the received signal. The channel estimation unit 64 performs channel estimation and noise power measurement using the reference signal, and calculates the channel channel matrix represented by the above equation (3) and the noise power represented by the above equation (5). . As shown in FIGS. 6 and 7, since the reference signals are arranged orthogonally between base stations and between antennas, it is not necessary to separate them at the receiving apparatus. The spatial filter coefficient generator 65 calculates a spatial filter coefficient from the calculated channel estimation value. The data signal is transmitted from the master base station and the slave base station by the spatial filter 66 using the spatial filter coefficient to perform signal separation of the mean least squares (MMSE) signal. Signal is separated. Further, the signal separated for each base station is subjected to SFBC (Space Frequency Block Coding) decoding.

  The calculated channel LLR value is sent to soft decision error correction decoders 70 and 71 for error correction decoding. In CRC checks 74 and 75, the CRC added to the decoded data is checked to determine whether there is an error in the data. In this way, the data signal is decoded.

  Several models for abstracting radio link characteristics have been proposed for system level evaluation in OFDM transmission systems. The system level evaluation is an evaluation of the entire wireless system assuming a plurality of cells and a plurality of mobile stations in each cell. The above model is based on a technique for accurately estimating BLER in a frequency selective fading channel using a mapping function of block error rate (BLER) to received SINR level. As mapping functions in these BLER estimation methods, mapping functions based on EESM (Exponential Effective SINR Mapping) and mean mutual information per coded bit (MMIB) have been proposed.

  MMIB has fewer parameters in the mapping function than EESM, and is suitable as a CQI generation method when AMC is applied in an OFDM system. In the present invention, MMIB is used in the AMC CQI generation method.

  Assuming ideal channel estimation, it is known that the MMIB vs. BLER characteristics in a frequency selective fading channel have almost the same characteristics as those in an additive white gaussian noise (AWGN) channel. ing. That is, the MMIB vs. BLER characteristic is hardly affected by the multipath delay in the propagation path. The BLER estimation method based on MMIB uses this property. In the CQI generation method according to the present invention, CQI is generated based on the MMIB-to-BLER characteristic obtained in the AWGN propagation path. At this time, the CQI can be efficiently created by using a reference table (LUT: Look Up Table) in which the MMIB-to-BLER characteristic or the throughput characteristic calculated from the BLER is recorded in advance. MMI (Mean Mutual Information) representing the average of mutual information per modulation symbol in the transmission block may be used instead of MMIB which is a quality index of the radio link used for generating CQI. When the number of encoded bits per modulation symbol is Q, there is a relationship of MMI = MMIB × Q between MMI and MMIB.

  Below, the calculation method of MMIB is demonstrated.

FIG. 9 shows the relationship between received SINR and MIB. The horizontal axis represents the received SINR of the modulation symbol, and the vertical axis represents the mutual information amount (MIB) per coded bit. The modulation method was QPSK, 16QAM, and 64QAM. Each point is the result of calculating the MIB function I _Q (γ) (Q = 2, 4, 6) by the Monte Carlo method using Equation (22). Also, the solid line is the result calculated by approximation of equation (24). From FIG. 9, it can be seen that the result indicated by each point and the result indicated by the solid line are almost the same, and equation (24) approximates equation (22) very well. Therefore, in the following, it is assumed that the MIB is calculated using the approximate expression (24).

Computer simulation was performed on the characteristics of MMIB and BLER. Table 1 shows the basic specifications in the simulation.

Table 2 shows the MCS levels applied in AMC.

  10 to 12 show simulation results of instantaneous MMIB and BLER for each MCS level shown in Table 2. FIG. FIG. 10 shows the result when the modulation method is QPSK, FIG. 11 shows the result of 16QAM, and FIG. 12 shows the result of 64QAM.

  Each solid line in FIG. 10 represents the MMIB-to-BLER characteristic in the AWGN propagation path in SISO (single-input single-output) transmission, where the number of antennas on the transmission side and the reception side is 1. The characteristics of MCS 1 to MCS 6 are shown from the left in the figure. Similarly in FIGS. 11 and 12, each solid line indicates the characteristic in SISO transmission. FIG. 11 shows the results of MCS 7 to MCS 9, and FIG. 12 shows the results of MCS 10 to MCS 15.

  Each mark in FIGS. 10 to 12 indicates the MMIB-to-BLER characteristic at the time of multiple base station cooperative MIMO spatial multiplexing transmission. These are the results obtained by computer simulation. The channel model uses a 3GPP ETU (Extended Typical Urban) model as a frequency selective fading propagation path as shown in Table 1 above. Further, it is assumed that the average channel gain of the downlink from the master base station BS # 1 and the slave base station BS # 2 is equal. Furthermore, the channel estimation in the receiving apparatus is ideal.

The BLER function BLER _AWGN () in the SISO-AWGN propagation path can be easily obtained from the equation (22) and the received SNR vs. BLER curve evaluated by the computer simulation in the SISO-AWGN propagation path or the laboratory experiment.

  In the mobile station receiver 15 shown in FIG. 8, the MMIB calculator 72 uses the received SINR output from the post-processing SINR calculator 67 to calculate the MMIB. The CQI calculator 73 calculates an optimum CQI from the calculated MMIB and the reference table 78. Here, the CQI for each of the master base station and the slave base station is calculated. The calculated CQI is generated as control information in the uplink control signal generator 79, and transmitted to the master base station through the uplink transmitter 80.

Information such as MCS, MMIB, BLER, and throughput can be recorded in the reference table 78 described above, and the processing speed can be increased by adopting a table format. There are several possible formats for the lookup table.
(1) MMIB-to-BLER characteristic of each MCS in SISO-AWGN propagation path (2) MMIB-to-throughput characteristic of each MCS (3) MCS capable of obtaining MMIB and maximum throughput
(4) MMIB threshold or the like for obtaining the maximum throughput MCS. However, it is not limited to these. Further, BLER and SINR can be collectively expressed as a communication quality metric (LQM: Link Quality Metric) in the propagation path.

  In the case of the format (1) or (2), the amount of data to be recorded is large, and a calculation means for calculating the maximum throughput is required. On the other hand, there is an advantage that data calculated by simulation can be used as it is.

  FIG. 13 shows throughput characteristics of multi-base station cooperative MIMO spatial multiplexing using AMC. Here, channel estimation is ideal. Further, it is assumed that there is no feedback delay and control delay of CQI. For each MCS of MCS 1 to MCS 15, the average throughput when AMC is not applied (that is, fixed at that MCS) is indicated by a dotted line. In addition, the throughput characteristics of AMC based on MMIB are shown by a solid line.

  When the MCS is selected based on SINR, which is a conventional AMC, the throughput is a characteristic of tracing the highest point of the throughput characteristic (dotted line) of each MCS in FIG. However, when MCS is selected based on the MMIB according to the present invention (solid line), a higher throughput than the conventional method is obtained. In the conventional method, the MCS is selected using the averaged SINR, whereas in the method according to the present invention, the instantaneous MMIB of the resource element is used.

  As described above, in the generation of CQI in AMC, by using MMIB, CQI suitable for various antenna configurations and propagation environments can be easily generated based on the transmission characteristics in a specific propagation environment. . Furthermore, it has been found that a higher throughput can be obtained compared to the conventional AMC.

  In AMC, when an error is included in channel estimation, there is a possibility of selecting an MCS different from the optimal MCS. For this reason, highly accurate channel estimation is indispensable. This is the same even when AMC using MMIB is performed in the present invention. However, in actual channel estimation, it is difficult to accurately estimate a propagation path that changes with time. In particular, in an environment where frequency selective fading and time selective fading are large, the estimation accuracy is greatly degraded. Further, as shown in FIGS. 6 and 7, the reference signals are discretely arranged, which causes deterioration in channel estimation accuracy. The deterioration of channel estimation accuracy reduces the throughput in AMC.

  Therefore, in order to apply AMC in an actual environment, a method for adjusting CQI is desired. Therefore, the present invention proposes a CQI adjustment method for reducing AMC characteristic degradation caused by channel estimation error. .

  The present invention proposes a method of adjusting the CQI value using the CRC check result. However, the CRC check result is not directly reflected in the CQI value, but the CQI value is indirectly determined by adjusting the post-processing SINR of each substream necessary for calculating the MMIB based on the CRC check result. To correct.

The calculation of the offset value by the above equation (31) is one example. For example, an arbitrary coefficient can be added to each of the equations (31) to adjust the change width. It is also possible to perform different corrections for each MCS. It is also possible to set the BLER _target in equation (31) for each MCS, and to adjust the coefficient for each MCS. It is also possible to control the offset value for each MCS. For example, when a block error occurs when a certain MCS is selected, only the offset value of that MCS is corrected.

  The characteristics of AMC using the CQI adjustment method according to the present invention are evaluated by computer simulation. In the simulation, an interpolation method based on two-dimensional IFFT / FFT is applied as a channel estimation algorithm.

FIG. 14 shows the average BLER in the 3GPP ETU channel model. Each characteristic is shown when the CQI correction according to the present invention is applied (solid line), not applied (W / O CQI adj), and ideally AMC is performed (Ideal AMC). When the CQI correction according to the present invention is applied, the target BLER and BLER _target of AMC are used as parameters, and the values of BLER _target are 0.005, 0.01, 0.05, 0.1 and 0.2.

FIG. 14 shows that when the CQI adjusting method of the present invention is used, a desired BLER characteristic (BLER _target ) is realized in the range of the average received SNR from 0 dB to 25 dB. On the other hand, when the CQI adjustment is not applied, the BLER characteristics are greatly degraded in these received SNR ranges. This degradation occurs due to mismatch between the MMIB-to-BLER characteristic in the frequency selective fading channel and the MMIB-to-BLER curve in the SISO-AWGN channel. This is because the channel estimation accuracy in the frequency selective fading channel has deteriorated.

FIG. 15 shows the throughput characteristics calculated using the results of FIG. When the CQI adjustment method according to the present invention is applied in the region where the average received SNR is 25 dB or less (solid line), compared to the case where CQI adjustment is not applied (W / O CQI adj), the ideal AMC (Ideal AMC) There is little degradation of the throughput characteristics. When BLER _target = 0.01, the degradation of throughput characteristics is minimized. This result shows that the CQI adjustment method proposed by the present invention is effective in an actual frequency selective fading environment.

  As described above, it has been found that by performing CQI adjustment according to the present invention, deterioration from ideal characteristics is reduced as compared with the case where CQI adjustment is not performed.

  In the above description, the cooperative MIMO transmission system between base stations has been described. However, the present invention is not applicable only to such a system, and is a normal MIMO transmission system with one base station, or SISO transmission. The present invention can be applied to antenna configurations with various numbers of transmission / reception antennas including the system.

  In the above description, it is assumed that AMC is applied to the downlink. However, the present invention is also effective when AMC is applied to the uplink. In this case, the device shown in FIG. 4 corresponds to the mobile station side device, and the device shown in FIG. 8 corresponds to the base station side device.

  Furthermore, the present invention can be applied to an OFDMA (Orthogonal Frequency Division Multiple Access) system. In OFDMA in which subcarriers with different OFDM are assigned among a plurality of users, the bit length of the transport block in error correction coding varies depending on the number of subcarriers to be assigned. In general, the larger the code length, the larger the coding gain is obtained. Therefore, in OFDMA, the MMIB-to-BLER characteristic varies depending on the number of assigned subcarriers. Therefore, in order to realize the optimum AMC, it is necessary to prepare a reference table of MMIB vs. BLER characteristics on the receiving side for each candidate number of subcarriers to be allocated.

  However, in an OFDMA system in which hundreds to thousands of subcarriers are used, the number of subcarriers increases, so a large storage area is required. Even in such a situation, the CQI correction method according to the present invention can be applied. First, only the MMIB vs. BLER characteristic for a specific number of assigned subcarriers is prepared. When the number of subcarriers is different from the actual number of used subcarriers, there is a mismatch between the actual BLER characteristics and the BLER characteristics on the lookup table. However, by applying the CQI correction method of the present invention, it is possible to correct the CQI value so as to match the actual BLER characteristic.

11, 22 Base station 14 Mobile station 17 Mobile communication network 33, 52 Encoding and modulator 34 Downlink control signal generator 35, 53 Reference signal generator 39 CQI receiver 40 MCS # 1 selector 41 MCS # 2 selector 63 Downlink control signal decoder 64 Channel estimator 65 Spatial filter coefficient generator 66 Spatial filter 67 Post processing SINR calculator 68, 69 Channel log likelihood ratio generator 70, 71 Soft decision error correction decoder 72 MMIB calculator 73 CQI calculation 74, 75 CRC check 78 Lookup table 79 Uplink control signal generator

Claims (8)

A wireless communication control method in a receiving apparatus of an OFDM transmission system,
Receiving a signal including a data signal and a reference signal from a transmitting device;
Estimating channel quality and noise power density based on the reference signal;
Calculating an instantaneous SINR for each OFDM subcarrier from the estimated channel quality and noise power density;
Converting the instantaneous SINR into mutual information (MIB) per coded bit and calculating a communication quality metric (LQM) based on an average value of the mutual information per coded bit in a transport block;
Based on the reference table and the calculated communication quality metric, obtaining a modulation scheme / coding rate combination (MCS) that maximizes the predicted throughput;
Transmitting the obtained index indicating the MCS as a channel quality indicator (CQI) to the transmitting device,
The reference table shows the relationship between the communication quality metric and the transmission quality of each MCS, or the relationship between the communication quality metric and the MCS that can obtain the maximum throughput in the communication quality metric.
A wireless communication control method.   The wireless communication control method according to claim 1, wherein the reference table is generated based on transmission characteristics of each MCS in a specific wireless propagation environment, and the transmission characteristics are transmission characteristics acquired by computer simulation or actual measurement. Checking for block errors for each transport block of the data signal; and
In the checking step, when there is no block error, the SINR offset value is increased by a first correction value, and when there is a block error, the SINR offset value is decreased by a second correction value;
Correcting the instantaneous SINR with the SINR offset value;
The wireless communication control method according to claim 1, further comprising: The OFDM transmission system is a MIMO transmission system;
The wireless communication control method according to any one of claims 1 to 3, wherein the instantaneous SINR is an instantaneous SINR of a signal separated and combined for each transmission layer. A receiving apparatus in an OFDM transmission system including a transmitting apparatus,
A receiver for receiving a signal including a data signal and a reference signal from the transmitter;
A channel estimation unit that estimates channel quality and noise power density based on the reference signal;
A SINR calculation unit that calculates an instantaneous SINR for each OFDM subcarrier from the estimated channel quality and noise power density;
Communication quality for converting the instantaneous SINR into mutual information (MIB) per coded bit and calculating a communication quality metric (LQM) based on an average value of the mutual information per coded bit in the transport block A metric calculator,
An MCS determination unit that acquires a modulation scheme / coding rate combination (MCS) that maximizes the predicted throughput based on the reference table and the calculated communication quality metric;
A CQI generating unit that transmits an index indicating the acquired MCS as a channel quality indicator (CQI) to the transmission device;
The reference table shows the relationship between the communication quality metric and the transmission quality of each MCS, or the relationship between the communication quality metric and the MCS that can obtain the maximum throughput in the communication quality metric.
A receiving apparatus.   6. The receiving apparatus according to claim 5, wherein the reference table is generated based on transmission characteristics of each MCS in a specific radio propagation environment, and the transmission characteristics are transmission characteristics acquired by computer simulation or actual measurement. A block error detection unit that checks whether a block error has occurred for each transport block of the data signal;
In the checking step, if there is no block error, the SINR offset value is increased by a first correction value, and if there is a block error, the SINR offset value is decreased by a second correction value, and further, the SINR offset value An SINR correction unit for correcting instantaneous SINR;
The receiving device according to claim 5, further comprising: The OFDM transmission system is a MIMO transmission system;
A spatial filter unit that separates and combines the received signals into signals for each transmission layer;
The receiving apparatus according to any one of claims 5 to 7, wherein the instantaneous SINR is an instantaneous SINR of a signal separated and combined for each transmission layer.

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