WO2017063682A1 - Dispositif de filtrage et son procédé - Google Patents

Dispositif de filtrage et son procédé Download PDF

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Publication number
WO2017063682A1
WO2017063682A1 PCT/EP2015/073731 EP2015073731W WO2017063682A1 WO 2017063682 A1 WO2017063682 A1 WO 2017063682A1 EP 2015073731 W EP2015073731 W EP 2015073731W WO 2017063682 A1 WO2017063682 A1 WO 2017063682A1
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WO
WIPO (PCT)
Prior art keywords
sample
filtering device
filter
weight
filtered
Prior art date
Application number
PCT/EP2015/073731
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English (en)
Inventor
Baicheng Xu
Jianjun Chen
Peter Almers
Junshi Chen
Original Assignee
Huawei Technologies Co., Ltd.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Huawei Technologies Co., Ltd. filed Critical Huawei Technologies Co., Ltd.
Priority to EP15780844.5A priority Critical patent/EP3210304A1/fr
Priority to PCT/EP2015/073731 priority patent/WO2017063682A1/fr
Publication of WO2017063682A1 publication Critical patent/WO2017063682A1/fr

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Classifications

    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H17/00—Networks using digital techniques
    • H03H17/02—Frequency selective networks
    • H03H17/04—Recursive filters

Definitions

  • the present invention relates to a filtering device. Furthermore, the present invention also relates to a corresponding method, a user device, a computer program, and a computer program product.
  • a conventional Infinite Impulse Response (MR) filter is widely used in signal processing. Especially, the MR filter is used for the post-processing of coarse estimates to reduce the variance and improve the accuracy of such estimates.
  • An example is in Automatic Frequency Control (AFC) in which the coarse frequency offsets estimating in a received signal shall be filtered before frequency correction in wireless communication systems.
  • AFC Automatic Frequency Control
  • conventional first-order MR filter has one potential assumption that all the input samples have the same signal quality, such as Signal-to-Noise Ratio (SNR) or Signal-to-Noise and Interference Ratio (SINR).
  • SNR Signal-to-Noise Ratio
  • SINR Signal-to-Noise and Interference Ratio
  • DMRS DeModulation Reference Signal
  • the Resource Block (RB) number for Physical Downlink Shared Channel (PDSCH) may vary from sub frame to sub frame and the DMRS is transmitted only on the RBs upon which the corresponding PDSCH is mapped. This means that the number of RBs containing DMRS will also vary from sub frame to sub frame. Therefore, some estimates (e.g., timing/frequency offset) based on DMRS in Coordinated Multi-Point (CoMP) scenario may have different signal qualities from sub frame to sub frame.
  • CoMP Coordinated Multi-Point
  • An objective of embodiments of the present invention is to provide a solution which mitigates or solves the drawbacks and problems of conventional solutions.
  • Another objective is to provide improved performance when different input samples have different qualities.
  • a filtering device comprising:
  • a multiplier configured to multiply each sample x n of a plurality of input samples with a corresponding weight w n corresponding to the sample x n so as to provide a weighted sample
  • a first Infinite Impulse Response, MR, filter configured to filter each weighted sample so as to provide a filtered weighted sample x n ;
  • a second MR filter configured to filter each corresponding weight w n so as to provide a corresponding filtered weight w n ;
  • a divider configured to divide each filtered weighted sample x n with its corresponding filtered weight w n so as to provide a normalized filtered weighted sample.
  • a number of advantages are provided by the present filtering device according to the first aspect. By filtering each corresponding weight w n and dividing each filtered weighted sample x n with its corresponding filtered weight w n the case of samples having different qualities can be handled. Therefore, the performance of the filtering device is improved, such as accuracy performance. This also means that improved estimates can be provided by the present solution.
  • the first MR filter and the second MR filter are first-order MR filters.
  • any of the first MR filter and the second MR filter are configured to adapt its filter coefficient a and a 2 , respectively, based on the sample index n of the sample x n .
  • a dynamic filter solution is provided which may mitigate the fluctuation of filter transients.
  • any of the filter coefficients a and a 2 are given by
  • a 0 is the stable filter coefficient of the first-order MR filter.
  • a a 2 .
  • the filtered weighted sample x n is given by
  • a is the filter coefficient of the first MR filter.
  • the fifth possible implementation form gives a straight forward expression for computing the filtered weight of the first MR filter.
  • the filtered weight w n is given by
  • a 2 is the filter coefficient of the second MR filter.
  • the sixth possible implementation form gives a straight forward expression for computing the filtered weight of the second MR filter.
  • the filtering device is configured to provide the weight w n for each sample x n based on the signal quality of the corresponding sample x n .
  • the different qualities of the different samples are mitigated or at least taken into account. As an example, the worse the quality of the sample the less the weight for the corresponding sample may be chosen.
  • the filtering device is configured to provide the weights w n such that each corresponding weight w n has a value related to any of the signal-to-noise ratio (SNR) and the signal-to-interference-plus-noise ratio (SINR) of its corresponding sample x n .
  • SNR signal-to-noise ratio
  • SINR signal-to-interference-plus-noise ratio
  • each corresponding weight w n has a value related the SNR, SINR, or SNR and SINR.
  • the SNR and SINR are good and convenient quality "metrics" for determining the corresponding weight, as SNR and SINR can be easily determined using known algorithms.
  • each sample x n represents an estimate of a parameter based on a reference signal of a wireless communication system.
  • Using the filtering device of the present solution for filtering of parameter estimates of a reference signal provides more reliable estimates than compared to conventional solutions in which the weights corresponding to the samples are not filtered.
  • the filtering device is configured to provide the weight w n for each sample x n based on the number of Resource Blocks, RBs, used for transmission of the reference signal.
  • the filtering device is configured to provide a higher weight for a higher number of RBs used and a lower weight for a lower number of RBs used. This possible implementation form provides improved performance since higher number of RBs yields higher quality and vice versa.
  • a user device for a wireless communication system comprising at least one filtering device according to any of the preceding claims, and further comprising: a receiver configured to
  • a processor configured to
  • the second aspect of the present invention provides the same advantages as the first aspect of the invention. According to a third aspect of the invention, the above mentioned and other objectives are achieved with a method comprising the steps of:
  • each weighted sample is filtered by a first MR filter and each corresponding weight w n is filtered by a second MR filter; wherein the first MR filter and the second MR filter are first-order MR filters.
  • the method further comprises
  • any of the filter coefficients a and a 2 are calculated by
  • a 0 is the stable filter coefficient of the first-order MR filter.
  • the filtered weighted sample x n is given by
  • a is the filter coefficient of the first MR filter.
  • the filtered weight w n is given by
  • a 2 is the filter coefficient of the second MR filter.
  • the method further comprises
  • the method further comprises
  • each sample x n represents an estimate of a parameter based on a reference signal of a wireless communication system.
  • the method further comprises
  • the method further comprises
  • the present invention also relates to a computer program, characterized in code means, which when run by processing means causes said processing means to execute any method according to the present invention. Further, the invention also relates to a computer program product comprising a computer readable medium and said mentioned computer program, wherein said computer program is included in the computer readable medium, and comprises of one or more from the group: ROM (Read-Only Memory), PROM (Programmable ROM), EPROM (Erasable PROM), Flash memory, EEPROM (Electrically EPROM) and hard disk drive.
  • ROM Read-Only Memory
  • PROM Programmable ROM
  • EPROM Erasable PROM
  • Flash memory Flash memory
  • EEPROM Electrically EPROM
  • FIG. 1 shows a filtering device according to an embodiment of the present invention
  • FIG. 2 shows a method according to an embodiment of the present invention
  • - Fig. 3 shows a user device according to an embodiment of the present invention
  • - Fig. 4 shows a wireless communication system according to an embodiment of the present invention
  • Fig. 5 shows simulation results for an embodiment of the present invention.
  • Fig. 1 shows a filtering device 100 according to an embodiment of the present invention.
  • the filtering device 100 comprises a multiplier 102, a first MR filter 104a, a second MR filter 104b, and a divider 106. It should be realised that the mentioned parts of the filtering device 100 are suitably connected to each other by means of communication means which are illustrated with the arrows in Fig. 1.
  • the multiplier 102 of the filtering device 100 is configured to receive a sample x n and its corresponding weight w n , where n denotes the sample index.
  • the sample x n and its corresponding weight w n may be received via an input which is not shown in Fig. 1 .
  • the sample x n belongs to a plurality of input samples fed to the present filtering device 100 for filtering.
  • the multiplier 102 is further configured to multiply each sample x n with its corresponding weight w n so as to provide a weighted sample to the first MR filter 104a.
  • the weighted sample is filtered by the first MR filter 104a which provides a filtered weighted sample xicide to the divider 106.
  • the second MR filter 104b of the filtering device 100 is configured to filter the corresponding weight w n so as to provide a corresponding filtered weight w n to the divider 106.
  • the divider 106 receives both the filtered weighted sample x n and the corresponding filtered weight w n form the first MR filter 104a and the second MR filter 104b, respectively, and is configured to divide the filtered weighted sample x n with the corresponding filtered weight w n . Thereby a normalized filtered weighted sample is providing as an output.
  • the normalized filtered weighted sample may be outputted via an output of the filtering device 100 (not shown in Fig.
  • Fig. 2 shows a corresponding method 200 which may be implemented in a filtering device 100, such as the one shown in Fig. 1 .
  • the present method 200 comprises the step 202 of multiplying (202) each sample x n of a plurality of input samples with a corresponding weight w n corresponding to the sample x n so as to provide a weighted sample.
  • the method 200 further comprises the step 204 of filtering each weighted sample so as to provide a filtered weighted sample x n .
  • the method 200 further comprises the step 206 of filtering each corresponding weight w n so as to provide a corresponding filtered weight w n .
  • the method 200 further comprises the step 208 of dividing each filtered weighted sample x n with its corresponding filtered weight w n so as to provide a normalized filtered weighted sample. It should be understood that the order of steps as shown in Fig. 2 is not binding. For example could step 206 performed also before step 204 or in parallel with step 204.
  • the operation of the present filtering device 100 may be described by the following three equations corresponding to three different embodiments of the present invention.
  • the first equation, Eq. 1 (corresponding to the upper branch of the filtering device 100 in Fig. 1 ), is given by where a is the filter coefficient of the first MR filter 104a, w n is the weight of sample x n and x n is the filtered weighted sample.
  • the x n is the output from the first MR filter 104a of the filtering device 100.
  • a 2 is the filter coefficient of the second MR filter 104b
  • w n is the filtered weight output from the second MR filter 104b of the filtering device 100.
  • x n is the final normalised weighted output sample.
  • the x n is the output from the divider 106 of the filtering device 100.
  • the first MR filter 104a and the second MR filter 104b are conventional first-order MR filters well known in the art.
  • the filter coefficient can be adaptively adjusted based on the sample index n.
  • the filter coefficients a a
  • Stable filter coefficient means the filter coefficient after the transition state of the first-order MR filter.
  • Fig. 3 shows a user device 300 according to an embodiment of the present invention.
  • the user device 300 comprises at least one filtering device 100 coupled to a processor 304 by means of communication means illustrated with the arrow between the filtering device 100 and the processor 304. Furthermore, the filtering device can 100 also be implemented in the processor 304 itself.
  • the user device 300 further comprises a receiver 302 configured to receive a reference signal and to forward the reference signal to the processor 304 of the user device 300 via the communication means between the processor 304 and the receiver 302.
  • the processor 304 is configured to receive the reference signal and is further configured to determine at least one estimate of a parameter based on the reference signal.
  • the processor 304 is further configured to provide a plurality of input samples representing the at least one estimate and corresponding weights corresponding to the plurality of input samples, and to feed the filtering device 100 with the plurality of input samples and the corresponding weights.
  • the filtering device 100 is configured to filter and process the plurality of input samples and the corresponding weights according to embodiments of the present invention. Thereafter, the filtering device 100 outputs normalized filtered weighted samples to the processor 304 which determines an improved estimate of the parameter based on the normalized filtered weighted samples.
  • the present user device 300 discussed in the present disclosure may be any of a User Equipment (UE), mobile station (MS), wireless terminal or mobile terminal which is enabled to communicate wirelessly in a wireless communication system, sometimes also referred to as a cellular radio system.
  • the UE may further be referred to as mobile telephones, cellular telephones, computer tablets or laptops with wireless capability.
  • the UEs in the present context may be, for example, portable, pocket-storable, hand-held, computer-comprised, or vehicle-mounted mobile devices, enabled to communicate voice or data, via the radio access network, with another entity, such as another receiver or a server.
  • the UE can be a Station (STA), which is any device that contains an IEEE 802.1 1 -conformant Media Access Control (MAC) and Physical Layer (PHY) interface to the Wireless Medium (WM).
  • STA Station
  • MAC Media Access Control
  • PHY Physical Layer
  • the present filtering device 100 may also be implemented in a base station, such as the one shown in Fig. 4, when the base station 502 operates in receiving mode.
  • the present filtering device 100 and corresponding method may be implemented or used in a communication device able to operate in receiving mode, such as user devices and base stations.
  • the present base station 502 may be a (radio) network node or an access node or an access point or a base station, e.g., a Radio Base Station (RBS), which in some networks may be referred to as transmitter, "eNB", “eNodeB”, “NodeB” or “B node”, depending on the technology and terminology used.
  • the radio network nodes may be of different classes such as, e.g., macro eNodeB, home eNodeB or pico base station, based on transmission power and thereby also cell size.
  • the radio network node can be a Station (STA), which is any device that contains an IEEE 802.1 1 -conformant Media Access Control (MAC) and Physical Layer (PHY) interface to the Wireless Medium (WM).
  • STA Station
  • MAC Media Access Control
  • PHY Physical Layer
  • Other aspects of the present filtering device 100 relate to the values of the corresponding weights.
  • the filtering device 100 is configured to provide the weight w n for each sample x n based on the signal quality of the corresponding sample x n . For example, higher signal quality result in higher weight and lower signal quality result in lower weight.
  • the corresponding weight w n has a value related to the SNR and/or the SINR of its corresponding sample x n .
  • the SNR and SINR are good measures of the signal quality and therefore indirectly also good measures of the quality of the samples.
  • each sample x n of the plurality of the input samples represents an estimate of a parameter based on a reference signal of a wireless communication system.
  • the input samples can e.g. represent a parameter estimate such as a frequency offset estimate, Doppler estimate, etc., but it is not limited to be these mentioned parameter estimates.
  • the input samples can also relate to or represent all different kinds of "data/information" such as audio, voice, video, etc.
  • Fig. 4 illustrates a wireless communication system 500 according to an embodiment of the present invention.
  • a base station 502 transmits one or more reference signals in the wireless communication system 500.
  • a user device 300 receives the reference signals. It is known that reference signals often are transmitted on different number of RBs in conventional wireless communication systems.
  • the filtering device 100 of the user device 300 is configured to provide the weight w n for each sample x n based on the number of RBs used for the transmission of the reference signal in the wireless communication system 500.
  • Fig. 4 The reverse case is also illustrated in Fig. 4 in which the user device 300 transmits a reference signal (dotted arrow) in the uplink to the base station 502.
  • the base station 502 receives the reference signal and the filtering device 100 of the base station 502 processes input samples as explained above.
  • a typical application for the present filtering device 100 is CoMP in which the timing or frequency offset, or Doppler delay spread shall be estimated based on DMRS. Such estimation may be done for each sub frame.
  • the filtering performed by the filtering device 100 can be used to post-process the estimates for obtaining more accurate estimates. Since the DMRS allocation may be different from sub frame to sub frame, it may be better to use the number of RBs used for DMRS allocation for each sub frame when computing the corresponding weights used in the filtering device 100. It may be noted that the number of RBs used for DMRS allocation determines the quality of the estimates indirectly. For the PDSCH based on the DMRS, the corresponding DMRS only exists in the RBs for the PDSCH transmission.
  • the filtering device 100 may therefore be configured to provide a higher weight for a higher number of RBs used and a lower weight for a lower number of RBs used. This means that e.g. a reference signal using 4 RBs imply a higher weight than if the reference signal uses 2 RBs.
  • SI NR SI NR
  • Embodiments of the present invention improve the performance of input samples when they have different signal qualities. Compared with conventional MR filters, the bigger quality deviation, the bigger performance improvement can be achieved by embodiments of the present invention.
  • Simulation results for embodiments of the present invention are given in Fig. 5 which shows the variance ratio of outputs from the present filtering device 100 and from conventional first-order MR filters according to conventional solutions.
  • the variance indicates the accuracy performance, and a smaller level of variance means higher performance, and larger level of variance means lower performance.
  • the variance ratio less than one, i.e. variance ratio ⁇ 1 means that the present solution provides smaller variance than conventional solutions meaning better performance.
  • the x-axis in Fig. 5 shows the number of variance levels for the input samples and the y-axis in Fig.
  • FIG. 5 shows the variance ratio for the present solution over conventional solution, i.e. variance ratio for present solution/conventional solution.
  • any method according to the present invention may be implemented in a computer program, having code means, which when run by processing means causes the processing means to execute the steps of the method.
  • the computer program is included in a computer readable medium of a computer program product.
  • the computer readable medium may comprises of essentially any memory, such as a ROM (Read-Only Memory), a PROM (Programmable Read-Only Memory), an EPROM (Erasable PROM), a Flash memory, an EEPROM (Electrically Erasable PROM), or a hard disk drive.
  • the present user device and base station comprise the necessary communication capabilities in the form of e.g., functions, means, units, elements, etc., for performing the present solution.
  • means, units, elements and functions are: processors, memory, buffers, control logic, encoders, decoders, rate matchers, de-rate matchers, mapping units, multipliers, decision units, selecting units, switches, interleavers, de-interleavers, modulators, demodulators, inputs, outputs, antennas, amplifiers, receiver units, transmitter units, DSPs, MSDs, TCM encoder, TCM decoder, power supply units, power feeders, communication interfaces, communication protocols, etc. which are suitably arranged together for performing the present solution.
  • the processors of the present user device and base station may comprise, e.g., one or more instances of a Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, or other processing logic that may interpret and execute instructions.
  • CPU Central Processing Unit
  • ASIC Application Specific Integrated Circuit
  • microprocessor may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones mentioned above.
  • the processing circuitry may further perform data processing functions for inputting, outputting, and processing of data comprising data buffering and device control functions, such as call processing control, user interface control, or the like.

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Mathematical Physics (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

La présente invention concerne un dispositif de filtrage comprenant : un multiplicateur (102) configuré pour multiplier chaque échantillon (a) d'une pluralité d'échantillons d'entrée avec un poids correspondant w n correspondant à l'échantillon (a) de manière à fournir un échantillon pondéré ; un premier filtre à réponse infinie à une impulsion, IIR, (104a) configuré pour filtrer chaque échantillon pondéré de manière à fournir un échantillon pondéré filtré (b) ; un second filtre IIR (104b) configuré pour filtrer chaque poids correspondant w n de manière à fournir un poids filtré correspondant (c) ; un diviseur (106) configuré pour diviser chaque échantillon pondéré filtré (b) avec son poids filtré correspondant (c) de manière à fournir un échantillon pondéré filtré normalisé. En outre, la présente invention concerne également un procédé correspondant, un dispositif utilisateur, un programme informatique et un produit-programme informatique.
PCT/EP2015/073731 2015-10-14 2015-10-14 Dispositif de filtrage et son procédé WO2017063682A1 (fr)

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EP15780844.5A EP3210304A1 (fr) 2015-10-14 2015-10-14 Dispositif de filtrage et son procédé
PCT/EP2015/073731 WO2017063682A1 (fr) 2015-10-14 2015-10-14 Dispositif de filtrage et son procédé

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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050105657A1 (en) * 2003-11-18 2005-05-19 Ibiquity Digital Corporation Coherent track for FM IBOC receiver using a switch diversity antenna system
US20070110201A1 (en) * 2005-11-15 2007-05-17 Gokhan Mergen Method and apparatus for filtering noisy estimates to reduce estimation errors

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050105657A1 (en) * 2003-11-18 2005-05-19 Ibiquity Digital Corporation Coherent track for FM IBOC receiver using a switch diversity antenna system
US20070110201A1 (en) * 2005-11-15 2007-05-17 Gokhan Mergen Method and apparatus for filtering noisy estimates to reduce estimation errors

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