METHOD AND APPARATUS FOR DETERMINING UE MOBILITY STATUS |
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申请号 | EP11751637.7 | 申请日 | 2011-06-29 | 公开(公告)号 | EP2594032B1 | 公开(公告)日 | 2014-06-04 |
申请人 | Telefonaktiebolaget LM Ericsson (publ); | 发明人 | ZHUANG, Jiandong; CHEN, Xixian; | ||||
摘要 | A radio user equipment (UE) mobility status is determined in a communications node. UE mobility status measurements associated with the UE communicating over a radio channel are performed. The UE mobility status corresponds to a degree of variation of the radio channel over time. Channel characteristics of the radio channel at a first time and at a second later time are determined. Based on the determined channel characteristics, a channel characteristic error metric is determined and compared to a predetermined threshold. The UE mobility status is determined based on one or more iterations of the threshold comparison. | ||||||
权利要求 | |||||||
说明书全文 | The technology relates to radio communications, and in particular, detecting radio channel variations. In this application, the term "UE mobility status," for a user equipment (UE) communicating in some fashion via a radio channel, corresponds to a degree of variation of the radio channel over time. In a cellular communications system, (LTE is one non-limiting example), the mobility status of a UE can provide useful information for the design of many technologies employed by the system, such as uplink channel estimation, closed-loop MIMO, multi-user MIMO (v-MIMO), adaptive antenna beamforming, radio resource scheduling, interference management, etc. For example, these technologies can be designed to be more effective and efficient if the UE mobility status is known. USPA 20070147533 employs an array of transmit antennas to transmit beamformed signal with antenna weights computed based on knowledge of a plurality of channels forming an aggregate channel. A set of characteristics for the aggregate channel, such as a power delay profile, a frequency correlation, an expected beamforming gain of the aggregate channel, a number of transmit antennas, a beamforming weight application delay value, an expected Doppler profile, or an expected delay profile of the propagation channel, is computed. A channel estimated is based on the computed set of characteristics. The document The problem addressed in this application is how to determine UE mobility status for wide use in a variety of applications and technologies effectively, efficiently, and in a real-time manner. For example, in the downlink closed-loop MIMO application, UEs measure downlink channel quality information (CQI) and report it to a serving base station via an uplink control channel that forms the closed loop. These UEs must move slowly so that the downlink channel variation caused by the UE mobility is small enough over the time of the CQI reporting period to ensure that the reported CQI represents the actual channel quality more closely and accurately. As such, a mechanism which can effectively and in a real-time manner determine the UE mobility status is important for the downlink closed-loop MIMO technology to achieve its desired design gain. For this type of application, the uplink channel estimation procedure to determine the UE mobility status on a 1-millisecond time scale may need to be extended to a hundreds-of-milliseconds in order to cover new scenarios. A radio user equipment (UE) mobility status is determined in a radio communications node , as disclosed in the appended claims.
The following description sets forth specific details, such as particular embodiments for purposes of explanation and not limitation. But it will be appreciated by one skilled in the art that other embodiments may be employed apart from these specific details. In some instances, detailed descriptions of well known methods, interfaces, circuits, and devices are omitted so as not obscure the description with unnecessary detail. Individual blocks are shown in the figures corresponding to various nodes. Those skilled in the art will appreciate that the functions of those blocks may be implemented using individual hardware circuits, using software programs and data in conjunction with a suitably programmed digital microprocessor or general purpose computer, and/or using applications specific integrated circuitry (ASIC), and/or using one or more digital signal processors (DSPs). Nodes that communicate using the air interface also have suitable radio communications circuitry. The software program instructions and data may be stored on computer-readable storage medium, and when the instructions are executed by a computer or other suitable processor control, the computer or processor performs the functions. Thus, for example, it will be appreciated by those skilled in the art that diagrams herein can represent conceptual views of illustrative circuitry or other functional units. Similarly, it will be appreciated that any flow charts, state transition diagrams, pseudocode, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computer or processor, whether or not such computer or processor is explicitly shown. The functions of the various illustrated elements may be provided through the use of hardware such as circuit hardware and/or hardware capable of executing software in the form of coded instructions stored on computer-readable medium. Thus, such functions and illustrated functional blocks are to be understood as being either hardware-implemented and/or computer-implemented, and thus machine-implemented. In terms of hardware implementation, the functional blocks may include or encompass, without limitation, digital signal processor (DSP) hardware, reduced instruction set processor, hardware (e.g., digital or analog) circuitry including but not limited to application specific integrated circuit(s) (ASIC) and/or field programmable gate array(s) (FPGA(s)), and (where appropriate) state machines capable of performing such functions. In terms of computer implementation, a computer is generally understood to comprise one or more processors or one or more controllers, and the terms computer. processor, and controller may be employed interchangeably. When provided by a computer, processor, or controller, the functions may be provided by a single dedicated computer or processor or controller, by a single shared computer or processor or controller, or by a plurality of individual computers or processors or controllers, some of which may be shared or distributed. Moreover, the term "processor" or "controller" also refers to other hardware capable of performing such functions and/or executing software, such as the example hardware recited above. The technology may be applied to any cellular communications system and/or network. Herein, a radio user equipment (UE) is understood to be any type of mobile radio node, e.g., mobile station (MS), terminal, laptop, PDAs, small base station, sensor, relay, etc. A network node can be any node that can communicate with a UE to access the network such as a base station node, relay node, pico cell, femto cell, Personal Area Network node, UE functioning as an eNodeB, WiFi Access Point and the like. UE mobility causes wireless channel fading phenomenon that strongly affects radio channel characteristics in both the frequency domain and the time domain, resulting in a channel characteristic response that varies in frequency and time. Different UE mobility speeds generate different Doppler effects which may reflect different degrees of channel variation in time and frequency given other channel conditions. Although the speed or velocity of the UE is usually the most significant factor affecting UE mobility status, it is not always the most significant and there are often other factors. Regardless of the factors involved, UE mobility status is a metric of a degree of variation in radio channel characteristic response over a certain period of time, e.g., when a UE (moving or stationary) sends measurement signals to its serving eNodeB. UE mobility status depends on the definition of one or more metrics used to reflect the degree of channel variation and one or more design parameters which may he determined by the performance of the system in which the technology is used. One type of systems includes cellular communication systems. Many cellular communication systems use some form of Orthogonal Frequency Division Multiple Access (OFDMA) technology where the data transmission is split into several sub-streams, and each sub-stream is modulated on a separate sub-carrier. OFDMA-based systems sub-divide the available bandwidth into radio resource blocks (RBs) defined in both time, frequency, code, and/or any combination thereof. As one non-limiting LTE-based example, a resource block could be 180 KHz and 0.5 ms in the frequency and time domains, respectively. The overall/available uplink and downlink transmission bandwidth can be very large, e.g., 20 MHz, 100 MHz, etc. As an overview, a network node receives UE mobility status measurements relating to the variation of a radio channel characteristic response caused by UE mobility and other factors to estimate magnitude of channel variation between two fixed time instants. This may be done, in one non-limiting example embodiment, by using received known reference signals such as demodulation reference signals (DMRS) sent by the concerned UE over a physical uplink shared channel (PUSCH) or sounding reference signals (SRS) sent over a sounding reference channel. In another non-limiting example embodiment, decoded, cyclic redundancy checked (CRC) UE data received on the PUSCH or the physical uplink control channel (PUCCH) may also be used to improve the accuracy of UE mobility status measurements in order to achieve more accurate channel estimation. In both example embodiments, the magnitude of the channel characteristic response variation between two time instants is compared with a predetermined magnitude threshold to initially decide an associated UE mobility status for the UE, e.g., a HIGH status or a LOW status in a two mode status implementation. This initial decision is preferably followed one or more additional decision iterations of the associated UE mobility status to make a final decision based on a rate of a certain UE mobility status event happening within a specified number of UE mobility status determination iterations. Techniques for determining a suitable magnitude threshold, number of iterations, and rate threshold are described below, but concrete values for these design parameters are preferably determined depending on the particular application. In addition, the metrics used for UE mobility status determination may be processed per UE, per radio resource block (RB), or per a group of multiple RBs. The processing per RB or group of RBs may be performed independently of a particular UE. The per RB or group of RBs approaches may be advantageous (1) in situations where different RBs might experience different channel variation in the frequency domain, even if the UE movement remains constant, (2) to reduce implementation costs because there is no need to identify each particular UE, (3) to enable independent parallel processing of channel estimation and maximum likelihood combining (MRC)/ interference reduction combining (IRC), and (4) to generate more measurement events for calculating the rate measurement for the final determination. To estimate and determine the mobility status of a UE, some type of measurement on the UE mobility must be obtained that reflects the UE mobility status effectively and preferably in a real-time manner. The measurement on a UE's uplink radio channel characteristic variation over time is preferred. On the other hand, it may be that the reference signals and two parameters just described may be determined by a standard. For example, for the LTE application of PUSCH channel estimation with a dual UE mobility status mode estimation algorithm, two demodulation reference sequence symbols (DMRS) may be used in the place of the two general reference sequences of the model. In this case, the time interval between the two DMRSs is seven (7) SC-FDMA symbols, if a normal cyclic prefix (CP) is used in a subframe, and the number of subcarriers of each DMRS is an integer multiple of a resource block (RB) depending on how many RBs are assigned to the UE for this subframe. In this example, a RB contains 12 subcarriers if the subcarrier spacing is 15 KHz apart. Likewise, if SRS is used in this model for some application, two consecutive SRS symbols in time may be used, and the relevant time interval and the number of subcarriers may be given by a standard. Table 1 below gives some non-limiting examples for using the UE mobility measurement model in some typical applications. Figure is a non-limiting flowchart illustrating example procedures followed by a network node, e.g., the base station in In reality, H1 and H2 could be mixed with noise and interference during the transmission and thus they need to be further processed by noise suppression filtering before they are used to determine the LIE mobility status. In general, this noise suppression filtering can be done either in the frequency domain or in the time domain. A splitter unit 22 splits the two, time domain-filtered complex sequences H1 and H2 representing the two channel frequency response sequences corresponding to x1 and x2. These two frequency domain complex sequences are the inputs to the UE mobility status determination procedures. To generate an error between the channel frequency response sequences at two different times, the splitter 22 routes H1 and H2 to two different paths. For example, H1 is delayed in a delay unit 24. The delay unit compensates for a timing difference between H1 and H2. The amount of delay may be determined based on the time interval between the two reference sequences and is also preferably dependent on the application of the technology. An error determination unit 26 determines an error between H1 and H2, e.g., a difference by subtracting H1 from H2 sample-by-sample, which corresponds to signal on a subcarrier in a RB. The mathematical details for accomplishing this are set forth in the formulas below. The error is processed by error processing unit 28 based on one or more criteria. The error processing algorithm can be any form that provides a meaningful metric that permits an effective determination of the UE mobility status based on the metric. Non-limiting example metric candidates are now described. One example metric may be a mean error metric. The mean error of H1 and H2 may be calculated, for example, as follows where N is the number of subcarriers contained by H1 and H2: where and and Another example metric is a mean square error that calculates the mean squared error of H1 and H2. An example calculation is provided below with the same definitions of H1 and H2. A third example is a normalized correlation metric that calculates the correlation between H1 and H2 normalized by the product of their magnitudes. The calculation below uses the same definitions of H1 and H2. where ( )* stands for its complex conjugate. As mentioned earlier, the metric(s) can be any form as long as it is meaningful and effective to reflect the channel characteristic variation due to the UE mobility. A general error metric(s) form may be written as a function of the error between H1 and H2 denoted by g(H2,H1) which is a measure of the UE mobility status in terms of a limited number of discrete UE mobility states defined and determined by a set of thresholds. With one threshold, two UE mobility states are defined: LOW status and HIGH status. Such two-state information about UE mobility is sufficient for many applications. But the number of UE mobility states could be more than two depending on which may be useful for applications that would benefit from further granularity of UE mobility status. For example, three UE mobility states could be defined using two thresholds, four UE mobility states could be defined using three thresholds, etc. The error processing in unit 28 may be performed "per UE," "per RB," or a group of RBs. Reference sequence processing handled on a per-UE basis means that the processing is with respect to each UE. But the entire occupied frequency band may also be treated as a whole regardless of whether it is being used by one UE or multiple UEs. In this case, the error metric(s) is determined RB-by-RB (instead of UE-by-UE) showing how much the channel characteristic response varies over each particular RB according to one or more suitably designed thresholds. As compared to processing per UE, this type of handling may produce additional benefits for some application such as unlink channel estimation. Consider, for example, an application with PUSCH channel estimation and a dual-UE mobility status (HIGH/LOW) algorithm. The goal is to leverage the fact that different RBs may experience different channel variation in the frequency domain even if the UE moves at a constant speed. This allows the channel estimation to account for different RBs to exploit frequency diversity from channel variation. Another benefit of processing per RB is reduced implementation costs because there is no longer a need to identify each particular UE. Eliminating UE identification frees up processing resources for other tasks. Another processing per RB benefit is the enablement of parallel processing of channel estimation and MRC/IRC combining. Because MRC/IRC combining can be done per RB, there is no need to wait until the entire band channel estimation is completed. Another benefit with processing per RB is that more measurement events can be generated to improve the rate measurement statistically. The following non-limiting example steps may be used to perform error processing per RB by the unit 28, taking uplink channel estimation as an example. First, set the number of subcarriers parameter N to 12 for each RB with respect to a frequency spacing of 15 KHz (in this example). Second, calculate the error metric RB-by-RB and independently of those UEs which occupy different portions of the frequency band concerned by the uplink channel estimation. Third, determine the channel variation over each RB across two different time instants by comparing the error metric of each RB with a predefined magnitude threshold. Finally, apply either an averaging algorithm if the UE mobility status is LOW or an interpolation algorithm if the UE mobility status is HIGH to each RB for channel estimation. As mentioned earlier, the value of the parameter N is preferably sufficiently large with respect to noise suppression. If N is too small, then the noise suppression filtering may be too weak leaving considerable residual noise in the calculated metric that could adversely affect the accuracy of the metric. For error processing per RB or group of RBs. this is not an issue because a RB containing 12 subcarriers for example ensures that the parameter N is not too small with respect to noise suppression, and the remaining effect can be further reduced by properly selecting the magnitude threshold. Therefore, the sufficient accuracy of the UE mobility status determination can be attained for the error processing per RB. On the other hand, a single RB in a LTE system has a bandwidth of 180 KHz, which is less than the coherence bandwidth of most of fading channels at frequency carriers in many applications. As a result, the variation of channel frequency response within an RB is normally small. Noise suppression can be further enhanced by performing a moving averaging on the channel characteristic response of each RB before calculating the metric without suffering significant distortion generated by the moving averaging on the channel characteristic response. Returning to An example of this thresholding process is graphically depicted in A rating and final determination unit 34 receives the decision from the thresholding unit 32. Although one error may be sufficient for the UE mobility determination, better results may be obtained if the error determination and thresholding process is performed for multiple iterations over multiple different time instants. The rating and final determination unit 34 can then count the number of iterations that resulted in each UE mobility status, e.g., a LOW UE mobility status or a HIGH UE mobility status (assuming only two UE mobility states in this example), is determined by the initial UE mobility determination along with the subsequent iterations over M times, where M is an integer. The rate r may be defined in the two-state example as Several non-limiting example methods for "event counting" by unit 34 are now described for the non-limiting two UE mobility state (HIG/LOW) situation. In one example, the event may be counted per RB using two reference symbols per transmission time intervals (TTIs). If the calculated metric for each RB per TTI is greater than the threshold, then a HIGH event is counted. Otherwise, a LOW event is counted. Another example counts events per UE using two reference symbols per TTI. If the calculated metric for each UE per TTI is greater than the threshold, then a HIGH event is counted. Otherwise, a LOW event is counted. A third method uses a sounding reference signal (SRS) for calculating the LOW or HIGH events. Two adjacent SRS symbols separated by at least two milliseconds are used to calculate the metrics. If the calculated metrics is greater than the threshold, then a HIGH event is counted. Otherwise, a LOW event is counted. Another method uses the channel responses estimated using decoded data, e.g., from the PUSCH or PUCCH, after passing CRC check or the like. Two correctly-decoded data symbols separated by a pre-defined interval are first used to estimate their corresponding channel responses, which are then used to calculate the metric in a similar way as the previous methods. If the calculated metric is greater than the threshold, then a HIGH event is counted. Otherwise, a LOW event is counted. The design parameters, M and R, like the threshold(s) used in thresholding unit 32 may be any suitable values. One non-limiting example method for determining suitable values is through performance simulations and lab testing in terms of the applications to be used. Step 1: An appropriate reference sequence type (e.g., DMRS, SRS, PUSCH, or PUCCH), time interval, and the error processing operation mode (processing per UE, per RB, or a group of RBs) are determined and may be based on a particular technology application which needs to know UE mobility status as well as on design tradeoffs between performance and implementation complexity. This in turn determines the number of subcarriers used in the metrics calculation. As one non-limiting example, N could be 12 if error processing per RB is used. Step 2: The number of states and the corresponding number of thresholds which can identify each state are determined for the application. Step 3: The metrics type to be used in the calculation may be selected based on design tradeoffs between performance and implementation complexity. Step 4: A performance simulator is created for the system, e.g., a LTE system, and the application requirements. The simulator simulates the reference sequence transmission with the reference signal model, the SRS signal transmission, the PUSCH transmission or the PUCCH transmission for UE uplink channel estimation, UE mobility measurement and the functionalities for the units shown in Although various embodiments have been shown and described in detail, the claims are not limited to any particular embodiment or example. None of the above description should be read as implying that any particular element, step, range, or function is essential such that it must be included in the claims scope. The scope of patented subject matter is defined only by the claims. The extent of legal protection is defined by the words recited in the allowed claims. All structural and functional equivalents to the elements of the above-described preferred embodiment that are known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the present claims. Moreover, it is not necessary for a device or method to address each and every problem sought to be solved by the technology described, for it to be encompassed by the present claims. Furthermore, no embodiment, feature, component, or step in this specification is intended to be dedicated to the public regardless of whether the embodiment, feature, component, or step is recited in the claims. |