The present disclosure relates to a wireless communication system, and more particularly, to a method and apparatus for receiving information at a receiver.
Wireless communication systems have been widely deployed to provide various kinds of communication services such as voice and data services. Generally, these communication systems are multiple access systems capable of supporting communication with multiple users by sharing available system resources (e.g., bandwidth and transmission power). Examples of multiple access systems include a code division multiple access (CDMA) system, a frequency division multiple access (FDMA) system, a time division multiple access (TDMA) system, an orthogonal frequency division multiple access (OFDMA) system, a single carrier frequency-division multiple access (SC-FDMA) system, and a multi-carrier frequency division multiple access (MC-FDMA) system.
An aspect of the present disclosure is to provide a method of receiving information at a receiver in a wireless communication system.
Another aspect of the present disclosure is to provide a method of reducing the amount of transmitted information in consideration of a relationship between pieces of information transmitted by transmitters.
Another aspect of the present disclosure is to provide a method of performing practical encoding and decoding to reduce the amount of transmitted information.
In an aspect of the present disclosure, a method of receiving information by a base station (BS) in a wireless communication system includes obtaining minimum transmission rate information for a function value of a first function, determining a parameter minimizing distortion between a plurality of user equipments (UEs), transmitting information about the first function based on the determined parameter to the plurality of UEs, receiving feedback information encoded based on the function value from the plurality of UEs, and decoding the encoded feedback information.
In another aspect of the present disclosure, a BS for receiving information in a wireless communication system includes a reception module configured to receive a signal, a transmission module configured to transmit a signal, and a processor configured to control the reception module and the transmission module. The processor is configured to obtain minimum transmission rate information for a function value of a first function, determine a parameter minimizing distortion between a plurality of UEs, transmit information about the first function based on the determined parameter to the plurality of UEs, receive feedback information encoded based on the function value from the plurality of UEs, and decode the encoded feedback information.
The following may be applied commonly to the method and apparatus for receiving information in a wireless communication system.
The minimum transmission rate information may be determined based on a rate distortion curve.
When the plurality of UEs transmit the feedback information, the rate distortion curve may be information indicating a minimum transmission rate for the function value of the first function in consideration of the distortion between the plurality of UEs.
The distortion between the plurality of UEs may be minimized through a functional distributed quantizer.
When the functional distributed quantizer is applied, a quantizer may be configured for use in each of the plurality of UEs, and the distortion may be minimized in consideration of an interval of the quantizer configured in each of the plurality of UEs.
The feedback information may be encoded based on the quantizer, and the encoded feedback information may be decoded based on a Bayes detector.
The parameter may be determined based on the quantizer.
The information about the first function may include at least one of a function index or an encoding index.
Encoding and decoding configuration information for the first function may be transmitted in system information to the plurality of UEs.
The feedback information may be channel quality indicator (CQI) feedback information, and the first function may be an argmax function.
The present disclosure may provide a method of receiving information at a receiver in a wireless communication system.
The present disclosure may provide a method of reducing the amount of transmitted information in consideration of a relationship between pieces of information transmitted by transmitters.
The present disclosure may provide a method of performing encoding and decoding to reduce the amount of transmitted information.
It will be appreciated by persons skilled in the art that the effects that can be achieved with the present disclosure are not limited to what has been particularly described hereinabove and other advantages of the present disclosure will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings.
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate embodiments of the disclosure and together with the description serve to explain the principle of the disclosure. In the drawings:
Reference will now be made in detail to the preferred embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings. In the following detailed description of the disclosure includes details to help the full understanding of the present disclosure. However, it is apparent to those skilled in the art that the present disclosure can be implemented without these details. For instance, although the following descriptions are made in detail on the assumption that a mobile communication system is the 3rd generation partnership project (3GPP) long term evolution (LTE) system or long term evolution-advanced (LTE-A) system, the following descriptions are applicable to other random mobile communication systems by excluding unique features of the 3GPP LTE and LTE-A systems.
Occasionally, to prevent the present disclosure from getting vaguer, structures and/or devices known to the public are skipped or can be represented as block diagrams centering on the core functions of the structures and/or devices. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts.
Besides, in the following description, assume that a terminal is a common name of such a mobile or fixed user stage device as a user equipment (UE), a mobile station (MS), an advanced mobile station (AMS) and the like. In addition, assume that a base station (BS) is a common name of such a random node of a network stage communicating with a terminal as a Node B (NB), an eNode B (eNB), an access point (AP) and the like.
In a mobile communication system, a UE can receive information from a BS in downlink and transmit information in uplink. The UE can transmit or receive various data and control information and use various physical channels depending types and uses of information transmitted or received thereby.
The following descriptions are applicable to various wireless access systems including a code division multiple access (CDMA) system, a frequency division multiple access (FDMA) system, a time division multiple access (TDMA) system, an orthogonal frequency division multiple access (OFDMA) system, a single carrier-frequency division multiple access (SC-FDMA) system, etc. CDMA can be implemented by radio technology such as universal terrestrial radio access (UTRA), CDMA 2000, etc. TDMA can be implemented with radio technology such as global system for mobile communications/general packet radio service/enhanced data rates for GSM evolution (GSM/GPRS/EDGE). OFDMA can be implemented with radio technology such as IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, evolved UTRA (E-UTRA), etc. UTRA is a part of universal mobile telecommunications system (UMTS).
3GPP LTE is a part of evolved UMTS (E-UMTS) using E-UTRA. The 3GPP LTE employs OFDMA in downlink (DL) and SC-FDMA in uplink (UL). In addition, LTE-A is an evolved version of the 3GPP LTE.
Moreover, in the following description, specific terminologies are provided to help the understanding of the present disclosure. In addition, the use of the specific terminology can be modified into another form within the scope of the technical idea of the present disclosure.
Regarding wireless transmission between a BS and a UE, transmission from a BS to a UE is defined as DL transmission, and transmission from a UE to a BS is defined as UL transmission. A mode where radio resources for DL transmission are different from those for UL transmission is referred to as ‘duplex mode’. In particular, a mode of performing transmission and reception bidirectionally by dividing time resources into DL transmission time resources and UL transmission time resources is referred to as ‘time division duplex (TDD) mode’, and a mode of performing transmission and reception bidirectionally by dividing frequency bands into DL transmission bands and UL transmission bands is referred to as ‘frequency division duplex (FDD) mode’. It is apparent that the technology proposed in the present disclosure may operate not only in the FDD mode but also in the TDD mode.
Although one BS 105 and one UE 110 are shown in the drawing to schematically represent the wireless communication system 100, the wireless communication system 100 may include at least one BSn and/or at least one UE.
Referring to
The UE 110 may include a Tx data processor 165, a symbol modulator 170, a transmitter 175, a transmitting and receiving antenna 135, a processor 155, a memory 160, a receiver 140, a symbol demodulator 155, and an Rx data processor 150. Although
For DL transmission, the Tx data processor 115 receives traffic data, formats the received traffic data, codes the formatted traffic data, interleaves and modulates (or perform symbol mapping on) the coded traffic data, and provides modulated symbols (data symbols). The symbol modulator 120 provides a stream of symbols by receiving and processing the data symbols and pilot symbols.
The symbol modulator 120 performs multiplexing of the data and pilot symbols and transmits the multiplexed symbols to the transmitter 125. In this case, each of the transmitted symbols may be a data symbol, a pilot symbol or a zero value signal. In each symbol period, pilot symbols may be continuously transmitted. In this case, each of the pilot symbols may be a frequency division multiplexing (FDM) symbol, an orthogonal frequency division multiplexing (01-DM) symbol, or a code division multiplexing (CDM) symbol.
The transmitter 125 receives the symbol stream, converts the received symbol stream into one or more analog signals, adjusts the analog signals (e.g., amplification, filtering, frequency upconverting, etc.), and generates a DL signal suitable for transmission on a radio channel. Thereafter, the transmitting antenna 130 transmits the DL signal to the UE.
Hereinafter, the configuration of the UE 110 is described. The receiving antenna 135 receives the DL signal from the BS and forwards the received signal to the receiver 140. The receiver 140 adjusts the received signal (e.g., filtering, amplification, frequency downconversion, etc.) and obtains samples by digitizing the adjusted signal. The symbol demodulator 145 demodulates the received pilot symbols and forwards the demodulated pilot symbols to the processor 155 for channel estimation.
The symbol demodulator 145 receives a frequency response estimation value for DL from the processor 155, performs data demodulation on the received data symbols, obtains data symbol estimation values (i.e., estimation values of transmitted data symbols), and provides the data symbols estimation values to the Rx data processor 150. The Rx data processor 150 reconstructs the transmitted traffic data by demodulating (i.e., performing symbol demapping on), deinterleaving and decoding the data symbol estimated values. The processing performed by the symbol demodulator 145 and the Rx data processor 150 are complementary to that performed by the symbol modulator 120 and the transmission data processor 115 of the BS 105, respectively.
For UL transmission, the Tx data processor 165 of the UE 110 processes the traffic data and provides data symbols. The symbol modulator 170 receives the data symbols, performs multiplexing of the received data symbols, modulates the multiplexed symbols, and provides a stream of symbols to the transmitter 175. The transmitter 175 receives the symbol stream, processes the received stream, and generates an UL signal. The transmitting antenna 135 transmits the generated UL signal to the BS 105.
The BS 105 receives the UL signal from the UE 110 through the receiving antenna 130. The receiver 190 obtains samples by processing the received UL signal. Subsequently, the symbol demodulator 195 processes the samples and provides pilot symbols received in UL and data symbol estimation values. The Rx data processor 197 reconstructs the traffic data transmitted from the UE 110 by processing the data symbol estimation values.
The processor 155 of the UE 110 controls operations (e.g., control, adjustment, management, etc.) of the UE 110, and the processor 180 of the BS 105 controls operations (e.g., control, adjustment, management, etc.) of the BS 105. The processors 155 and 180 may be connected to the memory units 160 and 185 configured to store program codes and data, respectively. Specifically, the memory units 160 and 185, which are connected to the processors 155 and 180, respectively, store operating systems, applications, and general files.
Each of the processors 155 and 180 can be called a controller, a microcontroller, a microprocessor, a microcomputer or the like. In addition, the processors 155 and 180 can be implemented using hardware, firmware, software and/or any combinations thereof.
When the embodiments of the present disclosure are implemented using hardware, the processors 155 and 180 may be provided with application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), etc.
Meanwhile, when the embodiments of the present disclosure are implemented using firmware or software, the firmware or software may be configured to include modules, procedures, and/or functions for performing the above-explained functions or operations of the present disclosure. In addition, the firmware or software configured to implement the present disclosure is provided within the processors 155 and 180. Alternatively, the firmware or software may be saved in the memories 160 and 185 and then driven by the processors 155 and 180.
Radio protocol layers between a UE and a BS in a wireless communication system (network) may be classified as Layer 1 (L1), Layer 2 (L2), and Layer 3 (L3) based on three lower layers of the open system interconnection (OSI) model well known in communication systems. A physical layer belongs to the L1 layer and provides an information transfer service via a physical channel A radio resource control (RRC) layer belongs to the L3 layer and provides control radio resources between a UE and a network. That is, a BS and a UE may exchange RRC messages through RRC layers in a wireless communication network.
In the present specification, since it is apparent that the UE processor 155 and the BS processor 180 are in charge of processing data and signals except transmission, reception, and storage functions, they are not mentioned specifically for convenience of description. In other words, even if the processors 155 and 180 are not mentioned, a series of data processing operations except the transmission, reception, and storage functions can be assumed to be performed by the processors 155 and 180.
Referring to
A conventional source coding scheme may limit a compression rate in a source encoder based on the Shannon's source coding theorem. When a receiver is to perfectly recover information transmitted by a transmitter, like lossless source coding, the source encoder of the transmitter needs to encode the information at or above at least the entropy rate of the transmitted information.
For example, in addition to point-to-point communication involving one transmitter and one receiver, a communication system including a plurality of transmitters and a single receiver may be considered. Because information transmitted from each transmitter to the single receiver is regarded as an independent source, correlational/mutual information between the sources may be zero. Therefore, a transmission rate may not be reduced despite joint decoding of information related to distributed encoding.
However, when UL transmission involving a plurality of UEs and a single evolved Node B (eNB) is considered, distributed encoding and joint decoding of a function of interest at the eNB may be applied even to independent sources. Thus, only specific information related to the specific function may be transmitted and the transmission rate may be reduced. Herein, the transmission rate may be reduced by the above-described distributed function computation. However, a suitable encoding method for approaching a boundary region may become an issue even to distributed function computation, which will be described below.
For example, when an eNB receives channel information from each UE and performs resource allocation based on the received channel information in mobile communication, the above-described method of reducing a transmission rate may be applied. For example, when an individual UE is located at a cell edge, the method of reducing a transmission rate may also be applied in a coordinated multi-point (CoMP) scenario for interference management between eNBs. More specifically, the method of reducing a transmission rate may be applied, when feedbacks are received from a coordinate eNB and a center eNB and resource allocation is performed based on the feedbacks. An entity responsible for the resource allocation has only to estimate a function value for performing resource allocation as necessary information, rather than recover all of the received feedback information. That is, since transmission of only a specific function value of a resource allocation-related function is sufficient, the transmission rate may be reduced as described before.
For example, the receiver may provide achievable rate distortion information according to a function of interest. However, even though the achievable rate distortion information is known, there is a need for configuring an efficient encoding/decoding method for approaching a boundary region.
Now, a description will be given of an encoding/decoding scheme which is applied when the above-described boundary region is approached, in consideration of a communication system to which a feedback mechanism involving a plurality of transmitters and one receiver is applied.
When a plurality of transmitters and a single receiver exist, the lower bound of information transmitted by the transmitters is determined according to the relationship between the information transmitted by the transmitters, as illustrated in
In a legacy communication system, however, because information sources of a plurality of transmitters are regarded as having independent features, I(X, Y)=0 all the time, which means no correlation, and thus the resulting saving of transmitted information may not be considered. That is, when the communication system transmits information of independent sources and the receiver wants to perfectly recover all of the information, the amount of the transmitted information may not be reduced. When independent sources are assumed, the receiver may accurately recover signals transmitted from the plurality of transmitters based on individual encodings and joint decoding.
However, when only a specific function value for information sources is calculated without the need for recovering all of raw data as transmitted data, transmission may be performed based on an Orlitsky-Roch bound, as illustrated in
Referring to
Referring to
A typical feedback-based overhead-performance tradeoff may be evaluated by a rate distortion curve in lossy source coding. When the boundary of the rate distortion curve is approached, the transmission rate may be increased. That is, the amount of information to be transmitted may be reduced most at the boundary of the rate distortion curve. Accordingly, there may be a need for a source coding/decoding scheme for approaching the boundary of a rate distortion curve.
Referring to
For example, a Bayes estimator may be used to minimize distortion. More specifically, distortion may be analyzed by analyzing a specific function as a given function. An appropriate parameter of a quantizer that approaches an achievable bound on a curve in which the analyzed distortion is considered may be configured. Further, an encoding rule for the appropriate parameter may be applied. As such, a practical encoding method may be configured by analyzing the given function only once.
The effect of reducing feedback overhead may be achieved by setting a legacy feedback scheme in a given method.
For example, source coding suitable for distributed function computation may be layered architecture for multi-terminal source coding. Layered architecture for multi-terminal source coding is a mere appellation which should not be construed as limiting the present disclosure. The same configuration may be applied to the same method, and the present disclosure may not be limited to the foregoing embodiment.
Layered architecture for multi-terminal source coding (hereinafter, referred to as layered architecture) may include a fundamental limit for setting a boundary based on the information theory of distributed function computation in a search step. More specifically, as described above, it is necessary to determine a specific function in order to set an information theory bound. In this case, given a distributed function of interest to the receiver, the achievable bound of feedback transmission information, which represents a corresponding function value as minimal sufficient information may be analyzed.
For example, when the receiver recovers a function value represented as information sources transmitted by the independent transmitters, minimum encoding rates of the transmitters may be represented as a rate distortion region. In this case, the rate distortion curve may represent a minimum transmission rate required when the independent sources transmit information to the one receiver (e.g., central estimation officer). Therefore, how close the practical coding scheme is to the information theory boundary may be determined.
However, to obtain the achievable bound, it is necessary to minimize distortion according to a distortion measurement that is actually applied. For example, the distortion may be minimized through a B ayes detector.
An optimal distributed functional scalar quantizer may then be designed in consideration of the distortion.
For example, basically, a functional distributed quantizer that performs quantization at K levels based on continuous sources uniformly distributed between [0, 1] may be considered. In this case, a quantizer to be used in each UE may be configured based on a distortion measurement according to a given function. Intervals of the quantizers that minimize an applied average distortion may be obtained according to the relationship between the intervals of the quantizers of the UEs.
As described before, the distortion may be defined as loss caused by the difference between a given function value Z and an estimated value {circumflex over (Z)} at the receiver. To this end, the quantizers for transmitters i may be divided into K intervals based on Equation 1 below.
The transmitters are K disjoint intervals, given as [li,0,li,1), [li,1,li,2), . . . , [li,K-1,li,K]. Because continuous sources between [0, 1] are considered, li,0=inf Xi=0 and li,K=sup Xi=1 may be set. For them, the decision boundary is {lk}k=0K and the reconstruction level is {uk}k=1K. Each quantizer is used as an encoder, and the encoding rule may be given by Equation 2.
Q
i(xi)=uk li,k-1≤xi<li,k [Equation 2]
The decoder may perform decoding based on a Bayes detector. Considering a Bayes estimator that minimizes an average distortion, there is a need for considering distributed quantizers in a plurality of transmitters. Accordingly, the Bayes estimator may be configured according to Equation 3 by setting the plurality of transmitters and given indices to k=[k1, . . . , kM] and assuming interval thresholds l=[li,k|k∈{1, . . . , K}].
{circumflex over (z)}(k,l)=argmin{circumflex over (z)}E[d(Z,{circumflex over (z)})|X1∈Ik
The distortion of a distributed quantizer for a given interval threshold may not be observed in all regions. That is, distortion may be observed in a part overlapped between the intervals of the transmitters.
For example, it may be noted from
It may be concluded that considering a K-level distributed function quantizer, Equation 5 should be satisfied to achieve minimized distortion.
Since a K-level distributed functional quantizer minimizing the distortion of continuous sources uniformly distributed between [0, 1] has been considered, there is a need for scaling-based parameter remapping by reflecting statistics of information sources to be actually applied.
In this case, in consideration of a parameter configuration, the above calculated parameters may be applied to a feedback mechanism. For example, when the receiver is assumed to be an eNB and the transmitters are assumed to be individual UEs, an encoding/decoding configuration for each function of interest may be broadcast in system information by the eNB or preconfigured for the UEs. Thereafter, when distributed function computation is triggered according to a feedback mechanism, the eNB may broadcast a function index to be applied to the UEs in system information. When a heterogeneous distributed quantizer with a different encoding rule for each UE is applied, an encoding index for each UE may be transmitted by an additionally designated method, and the present disclosure is not limited to the above-described embodiment.
Thereafter, when a UE receives information about a function index and an encoding rule from the eNB, the UE transmits feedback information to the eNB by applying an encoding scheme for a corresponding function. When the eNB receives the feedback information from each UE, it may perform function value computation by applying a joint decoding rule.
In other words, after obtaining a rate distortion curve for a specific value of a given function and obtaining a distributed functional scalar quantizer for minimizing distortion, a signal may be transmitted by performing parameter configuration for a feedback mechanism.
For a more specific embodiment, reference may be made to
Further, an adaptive modulation and coding scheme (MCS) may be applied, in which an MCS index is allocated based on a CQI. That is, a given function may be set in the CQI feedback mechanism, and the present disclosure is not limited to the above embodiment. While the following description is given in the context of distributed function computation based on the argmax function that allocates resources offering the best channel to the UEs 810 and 820, it should not be construed as limiting the present disclosure.
Further, a different specific value may also be configured for the given function. For example, while the best channel is given as the specific value in the above description, a best CQI may be given as the specific value. Further, a best UE may be given as the specific value. That is, even the specific value may be set differently based on the given function, and the present disclosure is not limited to the above embodiment.
The eNB 830 may receive 4-bit CQIs measured by the UEs from the UEs in order to allocate DL resources to the UEs. Subsequently, the eNB 830 may allocate the resources to a UE having the best channel based on the CQIs. When the eNB 830 checks only the best channel, the eNB 830 has only to calculate an argmax value as a function for checking the UE having the best channel without recovering all of the CQIs which are raw data. That is, the eNB 830 has only to check values of the argmax function as the given function, and thus the afore-described distributed function computation scheme may be applied.
To apply distributed function computation as described before, a rate distortion region should be calculated. For example, feedback mechanism information for 4-bit CQIs may be listed in Table 1 below.
In Table 1, efficiency is a channel capacity (spectral efficiency), and for every CQI index X, information sources may be assumed to be uniformly distributed across 16 levels. When resources are allocated to a UE having the best channel based on the above table, distortion measurement may be defined as channel capacity loss (spectral efficiency loss) in consideration of efficiency by Equation 6 and Table 2.
d(Z,{circumflex over (Z)})=C[XZ]−C[X{circumflex over (Z)}] [Equation 6]
Referring to
The argmax function may minimize distortion according to the above Bayes detector. As a result, the rate distortion curve may be produced as illustrated in
Then, a K-level distributed functional quantizer that minimizes the distortion of continuous sources uniformly distributed between [0, 1] may first be considered. For the quantizer, a parameter may be obtained by scaling in a procedure for remapping to statistics of the information sources, and the above Bayes detector may be considered. Herein, a Bayes detector for a Z=Argmax(X1,X2) may be given by Equation 8.
Herein, z*0 is a detector that minimizes distortion in an overlapped part, as illustrated in
When this Bayes detector is used, the expected distortion occurs only in an overlapped part between I1,k
Accordingly, the expected distortion in the given intervals may be given by Equation 10, and cases of respective overlapped intervals may be represented as illustrated in
Referring to
Further, the probability density function (PDF) of Event {t|X1∈I1,k
Further, in consideration of {t1T≥{circumflex over (T)}|X1∈I1,k
The average distortion may be obtained based on
Likewise, in case 2 of region Z02, when intervals are determined, the average distortion may be obtained by Equation 16 and the expected distortion may be obtained by Equation 17. The distorted distortion may be numerically optimized to obtain optimal quantized levels, as illustrated in
The above result may be the result of matching performed in consideration of distortion through continuous sources between [0, 1] and scaling based on CQI statistics defined as 16-level spectral efficiencies. A distributed functional quantizer may be configured from quantizer levels at lossless points, as illustrated in
Subsequently, a CQI feedback mechanism may be performed based on parameters derived based on the above description. When the eNB is to trigger resource allocation by argmax function computation, the eNB may designate the index of a preconfigured argmax function and a distributed quantizer encoding index for each UE or transmit the indexes to the UE in system information. Upon receipt of the function index and encoding index from the eNB, the UE may transmit a signal to the eNB by applying an encoding scheme for the function. When receiving a feedback mechanism from each UE, the eNB may perform function value computation by applying a joint decoding rule, and the present disclosure is not limited to the above embodiment.
In another example,
Upon receipt of metrics for each PRB from the eNBs 1510 and 1520, the coordinate eNB 1530 may determine an eNB to which a corresponding PRB is actually to be allocated by the argmax function. The coordinate eNB 1530 may transmit a PRB-wise bitmap to the eNBs 1510 and 1520. As in the foregoing embodiment, the coordinate eNB 1530 may calculate a rate distortion curve based on the argmax function. Then, distortion may be minimized by a suitable distributed functional quantizer. As described before, the quantizer may be obtained based on a Bayes detector, as illustrated in
The individual eNBs 1510 and 1520 transmit feedback information to the coordinate eNB 1530 by applying a corresponding encoding scheme for the argmax function. Upon receipt of the feedback information from the respective eNBs 1510 and 1520, the coordinate eNB 1530 may perform argmax function value computation by applying a joint decoding rule.
Referring to
For example, 16-level sensing values may be defined as in the above-described LTE CQI reporting. However, other numbers of levels may be determined in another reporting method, and the present disclosure is not limited thereto. The plurality of sensors 1710, 1720, and 1730 may report sensing values periodically to the reported device 1740. The reported device 1740 may detect sensed information from the reported values and transmit minimum information for this.
For example, when a given function is an argmax function and a sensing value is set as a specific value based on the argmax function, a rate distortion curve for the plurality of sensors 1710, 1720, and 1730 may be calculated. Subsequently, distortion may be minimized by a suitable distributed functional quantizer. As described before, a quantizer may be obtained based on a Bayes detector, as illustrated in
The parameter configuration may be performed by a reporting mechanism procedure based on the above-described parameters. The reported device 1740 may set and indicate the index of a sensing value and a distributed quantizer encoding index for each of the sensors 1710, 1720, and 1730. The individual sensors 1710, 1720, and 1730 may transmit information to the reported device 1750 by applying a corresponding encoding scheme for the argmax function, and the present disclosure is not limited to the foregoing embodiment.
As described before, when the eNB estimates only a specific value of a given function without recovering all of raw data received from UEs, the amount of transmitted information may be reduced based on suitable source coding.
More specifically, referring to
The rate distortion curve may be determined based on distortion, as described before. To minimize transmitted information based on the rate distortion curve, it is necessary to set an encoding rate in a boundary region. That is, a suitable source coding scheme may be applied to represent a minimum transmission rate in consideration of distortion, as described before.
The eNB 1910 may obtain and apply a Bayes detector to minimize distortion according to a distortion measurement. For example, quantizers may be configured for use in UEs 1920 and 1930 that transmit information to the eNB 1910. Distortion information may be obtained in consideration of the relationship between the intervals of the quantizers of the UEs 1920 and 1930, and the distortion may be minimized accordingly, as described before. Subsequently, the eNB 1910 may determine a parameter that minimizes distortion. That is, a parameter applied to encoding may be determined in consideration of the function value of the first function.
The eNB 1910 may transmit function index information and encoding index information as information about the first function to the first UE 1920 and the second UE 1930. While two UEs and one eNB are shown in
Subsequently, the eNB 1910 may receive feedback information encoded based on the function value from the first UE 1920 and the second UE 1930. The UEs 1910 and 1920 may encode the feedback information through the above-descried quantizers. The eNB 1910 may decode the encoded feedback information based on the Bayes detector. That is, the eNB 1910 may control a parameter such that the quantizers may be decoded based on the Bayes detector, and indicate the controlled parameter to the UEs 1920 and 1930. Thus, the UEs 1920 and 1930 may reduce the amounts of transmitted information based on the parameter.
The layered architecture for multi-terminal source coding may include detecting a fundamental limit for setting an information theory bound of distributed function computation (S2010). More specifically, a specific function may be determined to set the bound, as described before. Once a function of interest for the receiver is determined, an achievable bound of feedback transmission information represented as minimal sufficient information that minimizes a corresponding function value may be analyzed. For example, when the receiver recovers a function value expressed as information sources transmitted by independent transmitters, minimum encoding rates of the receivers may be shown as a rate distortion region. Because a rate distortion curve represents minimum transmission rates required for independent sources to transmit information to one receiver (e.g., central estimation officer), the rate distortion curve may show how close a suitable coding scheme is to a bound. However, to obtain an achievable rate region, it is necessary to minimize distortion according to an actually applied distortion measurement. For example, the distortion may be minimized by the afore-described Bayes detector.
A suitable distributed functional scalar quantizer may then be designed in consideration of the distortion (S2020). As described before, the distortion may be minimized in consideration of the relationship between the intervals of the quantizers at the transmitters. The quantizer may be configured based on the Bayes detector.
Subsequently, parameter information for a feedback mechanism may be configured (S2030). The parameter information may be transmitted to each UE, as described before. After the eNB transmits the parameter information to each transmitter, the transmitter may transmit feedback information encoded based on a parameter value to the eNB. The eNB may then decode the encoded feedback information, as described before.
Referring to
The receiver may then determine a parameter that minimizes the distortion between the plurality of UEs (S2120). As described before with reference to
The receiver may then transmit information about the first function based on the determined parameter to the receiver (S2130). For example, the receiver may be a UE. Further, as described before with reference to
The receiver may then receive feedback information encoded based on a function value from the plurality of transmitters (S2140). The plurality of transmitters may be UEs. As described before with reference to
The receiver may decode the encoded feedback information (S2150). As described before with reference to
In the above, a transmitter may be a UE, an eNB, a sensor, or any other device. A receiver may also be an eNB, a UE, or any other device. That is, when a plurality of devices transmit signals to one device, one of the two parties may be configured as a transmitter and the other party may be configured as a receiver, and the present disclosure is not limited to the foregoing embodiment.
The embodiments of the present disclosure may be implemented through various means. For example, the embodiments may be implemented by hardware, firmware, software, or a combination thereof.
When implemented by hardware, a method according to examples of the present disclosure may be embodied as one or more application specific integrated circuits (ASICs), one or more digital signal processors (DSPs), one or more digital signal processing devices (DSPDs), one or more programmable logic devices (PLDs), one or more field programmable gate arrays (FPGAs), a processor, a controller, a microcontroller, a microprocessor, etc.
When implemented by firmware or software, a method according to examples of the present disclosure may be embodied as an apparatus, a procedure, or a function that performs the functions or operations described above. Software code may be stored in a memory unit and executed by a processor. The memory unit is located at the interior or exterior of the processor and may transmit and receive data to and from the processor via various known means.
As described above, the detailed description of the preferred examples of the present disclosure has been given to enable those skilled in the art to implement and practice the disclosure. Although the disclosure has been described with reference to exemplary embodiments, those skilled in the art will appreciate that various modifications and variations can be made in the present disclosure without departing from the spirit or scope of the disclosure described in the appended claims. Accordingly, the disclosure should not be limited to the specific examples described herein, but should be accorded the broadest scope consistent with the principles and novel features disclosed herein.
Reference is made herein to both apparatus and method inventions, and the descriptions of both apparatus and method inventions may be complementary to each other.
The present disclosure is applicable to various wireless communication systems including systems conforming to IEEE 802.16x and IEEE 802.11x as well as 3GPP LTE and LTE-A systems.
Filing Document | Filing Date | Country | Kind |
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PCT/KR2017/010174 | 9/18/2017 | WO | 00 |
Number | Date | Country | |
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62503904 | May 2017 | US |