Link adaptation based on a number of consecutive blank slots

Abstract

A method performed by network node. The method includes scheduling a transmission to a UE, wherein the transmission is scheduled to occur in a target slot, and a number of consecutive DL blanked slots immediately precede the target slot. The also method includes determining the number of consecutive DL blanked slots that immediately precede the target slot. The also method includes selecting a resource for the transmission using the determined number of consecutive DL blanked slots, wherein the selected resource is an MCS or a set of CCEs. The further method includes performing the transmission using the selected resource.

Description

LINK ADAPTATION BASED ON A NUMBER OF CONSECUTIVE BLANK SLOTSTECHNICAL FIELD

[0001] Disclosed are embodiments related to error vector magnitude aware link adaptation.BACKGROUND

[0002] As explained in patent application publication no. US 20210050935 Al, link adaptation (LA) is an important radio resource management (RRM) function in wireless communication systems, such as Long Term Evolution (LTE) and Fifth Generation (5G) New Radio (NR), for reliable communication. One purpose of the LA function is to determine the appropriate modulation and coding scheme (MCS) for an over-the-air (OTA) downlink (DL) transmission. Typically, the OTA DL transmission is from a base station to a user equipment (UE).

[0003] A link adaptation process that results in the selectin of a sub-optimal MCS can lead to, among other things, throughput degradation, an increase in packet latency, poor quality- of-service (QoS), etc. For example, an aggressive link adaptation process that chooses an MCS that cannot be reliably supported by the wireless channel at the UE leads to decoding failures, thereby reducing throughput and potentially increasing delay. On the other hand, a conversative link adaptation process that chooses an MCS that delivers much lower data rate than what the wireless channel can support greatly reduces throughput and potentially increases delay.

[0004] Link adaptation performance is generally governed by the accuracy of channel estimates and interference-plus-noise (IpN) measurements. Even if channel estimation and IpN measurements are perfect, RF impairments such as transmit error vector magnitude (EVM) in a radio can also cause poor link adaptation.

[0005] In 5G time division duplex (TDD) networks where dynamic downlink (DL) blanking is considered, radio frequency (RF) impairments caused by power amplifiers (PAs) can become a bottleneck in determining link adaptation performance. For instance, due to DL blanking, the change in power supply and / or ambient temperature and inaccurate digital predistortion (DPD) calibration can cause a high transmit EVM and hence the previously selectedMCS could no longer be reliably decoded at a receiver. DL blanking has been widely used as one of the 5G features for, among other things, energy saving and remote interference management.

[0006] High EVM has been observed in the DL slot after an uplink (UL) slot (i.e., a blanked DL slot) and is considered normal and expected. It has also been noted that some have implemented an EVM mitigation feature that allows PA warm-up that puts the downlink RE in stable state and reduces the EVM of following PDSCH transmission, the solution of which means more energy is needed and hence potentially more co-channel interference caused to mitigate the EVM issue.SUMMARY

[0007] Certain challenges presently exist. For instance, traditional link adaptation functions do not take into consideration any signal-to-noise ratio (SNR) penalty caused by RF impairments, such as, for example, transmit EVM due to DL blanking.

[0008] Accordingly, in one aspect there is provided a method that is performed by network node. The method includes scheduling a transmission to a UE, wherein the transmission is scheduled to occur in a target slot, and a number of consecutive DL blanked slots immediately precede the target slot (the number of DL blanked slots that immediately precede the target slot may be zero). The also method includes determining the number of consecutive DL blanked slots that immediately precede the target slot. The also method includes selecting a resource for the transmission using the determined number of consecutive DL blanked slots, wherein the selected resource is an MCS or a set of CCEs. The further method includes performing the transmission using the selected resource.

[0009] In another aspect there is provided a computer program comprising instructions which when executed by processing circuitry of an apparatus causes the apparatus to perform any of the methods disclosed herein. In one embodiment, there is provided a carrier containing the computer program wherein the carrier is one of an electronic signal, an optical signal, a radio signal, and a computer readable storage medium. In another aspect there is provided an apparatus that is configured to perform the methods disclosed herein. The apparatus may include memory and processing circuitry coupled to the memory.

[0010] An advantage of the embodiments disclosed herein is that they provide improved link adaptation performance and hence better throughput performance can be obtained in the presence of dynamic blanking in 5G systems. The embodiments also provide a better tradeoff between cost and system performance.BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings, which are incorporated herein and form part of the specification, illustrate various embodiments.

[0012] FIG. 1 illustrates a communication system according to an embodiment.

[0013] FIG. 2 illustrates a network node according to an embodiment.

[0014] FIG. 3 illustrates contents of an example LUT.

[0015] FIG. 4 illustrates contents of an example LUT.

[0016] FIG. 5 illustrates a communication system according to an embodiment.

[0017] FIG. 6 is a flowchart illustrating a process according to an embodiment.

[0018] FIG. 7 is a block diagram of a network node according to an embodiment.DETAILED DESCRIPTION

[0019] FIG. 1 illustrates a communication system 100 according to an embodiment. System 100 includes a UE 102 communicating OTA with a network node 104, such as, for example a 5G base station (gNB). When network node 104 has data to transmit to UE 102, network node 104 selects an MCS for the transmission.

[0020] Accordingly, as shown in FIG. 2, network node 104, includes, in one embodiment, a distributed unit (DU) 204 that includes an LA function 214. Network node 104, in the embodiment shown, also includes a radio unit (RU) 202 and a central unit (CU) 206. In other embodiments, LA function 214 need not be a component of the distributed unit. For example, LA function 214 could be a component of central unit 206. As further shown in FIG. 2, in one embodiment, network node 104 includes an SNR penalty look-up table (LUT) 290. But, in other embodiments, LUT 290 may be external to network node 104, for example, LUT 290 may be hosted in a server in a cloud environment.

[0021] FIG. 3 illustrates a first example of the information that may be stored in LUT 290. In the example shown, LUT 290 has a set of records, where each record includes three fields: 1) number of blank slots, 2) MCS identifier (ID), and 3) SNR penalty. Accordingly, in this example, table 290 maps a 2-tuple consisting of a value specifying a number of blank slots and an MCS ID to a particular SNR penalty. For instance, the 2-tuple [1, MCS_3] maps to an SNR penalty of 3 dB.

[0022] LA function 214 function to select an MCS. In one embodiment, when LA function 214 needs to select an MCS from a set of candidate MCSs, such as, for example, when network node 104 is in the process of scheduling an OTA transmission to UE 102, LA function 214 computes an estimated SNR value for each candidate MCS. Then, for each candidate MCS, LA function 214 uses the estimated SNR value for the candidate MCS to assign a score to the MCS. The score assigned to an MCS may represent the spectral efficiency of the candidate MCS. Then, based on the scores, LA function 214 selects the MCS with the best score, such as, for example, the MCS that will provide the best estimated spectral efficiency.

[0023] Advantageously, in one embodiment, prior to LA function 214 computing an estimated SNR value for a particular candidate MCS, LA function: (1) determines the number of consecutive DL blank slots that immediately precede the scheduled OTA transmission and (2) obtains from table 290 an SNR penalty value that is mapped to the 2-tuple consisting of the determined number of DL blank slots and the ID of the particular candidate MCS. As a specific example, referring to FIG. 3, if the determined number of consecutive DL blank slots is 3 and the MCS ID for the particular candidate MCS is QAM 16, then LA function 214 will obtain an SNR penalty value of 1 dB from table 290. As explained above, this obtained SNR penalty value will then be used to compute the estimated SNR for the particular candidate MCS, and the estimated SNR for the candidate MCS can then be used to assign a score to the candidate MCS. The candidate MCS with the best score is then chosen as the MCS for the OTA transmission.

[0024] In one embodiment, LA function 214 determines the estimated SNR (E-SNR) by considering the following inputs: estimated SNR from channel quality indicator (CQI) reports, Outer-loop adjustments from historical ACKs / NACKs, and the SNR penalty caused by EVM due to blanked slots. For instance, in one embodiment, LA function computes the E-SNR using the following formula: E-SNR = CQLSNR + OL_Adj - a(SNR_p) - AO, where CQLSNR is anestimated SNR value that is determined based on one or more CQI reports from UE 102, O_Adj is the outer-loop adjustment value, SNR_p is the SNR penalty value obtained from LUT 290, a is a scaling factor due to cross-stream interference (if the OTA will be a MIMO transmission and there is a per-layer MCS selection), and AO is any additional SNR offset, which could be configured manually or automatically.

[0025] Accordingly, to fetch from LUT 290 an SNR penalty caused by EVM due to DL blanked slots, LA function 214 determines the number of consecutive DL blanked slots immediately preceding the target OTA transmission slot and then determines an EVM-aware SNR penalty from the lookup table per candidate MCS. Lor multi-layer MCS selection as in MIMO transmissions, one can further consider a scaling factor that can be applied to the EVM- aware SNR penalty in per-layer MCS selection.

[0026] Similarly, the selection of control channel elements (CCEs) for PDCCH transmission can be made EVM-aware by considering an SNR penalty caused by EVM. One option is to reuse the same SNR penalty used in MCS selection. Another option is to consider a scaled version of the SNR penalty since the BLER targets for PDCCH receptions and PDSCH receptions are often different.

[0027] In some PAs, the higher the PRB utilization, the higher the EVMs. Hence, to calculate a more accurate an SNR penalty caused by EVM, LUT 290 can be extended to include the PRB utilization. More specifically, instead of each record of LUT containing three fields (number of blanked slots, MCS ID, SNR penalty), each record of LUT may contain four fields (PRB utilization value, number of blanked slots, MCS ID, SNR penalty). This is illustrated in FIG. 4.

[0028] Generating LUT 290

[0029] A first step in generating LUT 290 includes obtaining baseline SNR values. That is, for each candidate MCS, a baseline SNR value for the candidate MCS is obtained. In one embodiment, obtaining the baseline SNR values includes using a transmitter (e.g., network node 104) to transmit a known signal, such as a reference signal (RS), using a selected one of the candidate MCSs (e.g., QPSK (modulation order 2bits), QAM16 (4 bits), QAM64 (6bits), QAM256 (8 bits), QAM1024 (10 bits), etc). The transmitted signal is received at a receiver (e.g., UE 102). Next, using a convention method, the EVM of the received signal is computedover an observation window (e.g., lOseconds) and then the average SNR at the receiver is computed using the EVM. This average SNR is the baseline SNR for the selected candidate MCS. The above steps are repeated for each other candidate MCS so that each candidate MCS will have a baseline SNR value.

[0030] After the baseline SNR is obtained for a candidate MCS (e.g., QPSK), a set of EVM-aware SNR penalty values can be determined for the candidate MCS, wherein each SNR penalty value corresponds to a different number of DL blanks. For example, the following steps can be performed to obtain a set of N SNR penalty values for any given selected MCS.

[0031] Step 1: Set n=l.

[0032] Step 2: Blank n DL slot(s) and then transmit a known signal of the selected candidate MCS in the next slot and repeat this transmission pattern.

[0033] Step 3: Compute EVM of the received signals over the observation window (e.g., 10 seconds) and compute the average SNR at the receiver.

[0034] Step 4: Compute the difference between this average SNR and the baseline SNR, and this difference is the SNR penalty for N-slot blanking.

[0035] Step 5: If n is not equal to N, then set n = n + 1 and go back to step 2, otherwise end.

[0036] These steps above are then repeated for each other candidate MCS. In this way, each candidate MCS will be associated with a set of SNR penalty values, where each SNR penalty value is associated with a different number of DL blank slots (see e.g., FIG. 3). The above steps can also be modified to obtain, for any given candidate MCS, M number of sets of SNR penalty values wherein each set of SNR penalty values is associated with a different PRB utilization, and, within any of these sets, each SNR penalty value is associated with a different number of DL blanks slots (see e.g., FIG. 4). It is noted that that UL slots in an TDD pattern are also considered DL blanked slots.

[0037] Transmit EVMs can be different from one transmitter to another. For example, transmit EVMs may be influenced by: the vendor that made the PAs in the transmitter, the ambient temperatures, etc. Accordingly, in one embodiment, each transmitter may have its own LUT 290. However, characterizing SNR penalties due to transmit EVM for every transmitter atevery temperature is not practical. Accordingly, in one embodiment, a number of transmitters are sampled and an average SINR penalty is calculated. In this way, several different transmitters may use the same LUT.

[0038] Also, due to aging and other nonlinear effects in PAs, the EVM and hence the SNR penalty may become inaccurate after some time. To validate the accuracy of the LUT, one may conduct measurements on the first non-blanked slot with the new link adaptation algorithm over time. If the first non-blanked slot starts experiencing higher ACKs or NACKs than other DL slots, it may indicate that the existing lookup table is no longer accurate and retraining is needed.

[0039] Accordingly, FIG. 5 illustrates an embodiment in which a computation module (CM) 502 that may be running on a server 504 in a network 510 remote from a set of network nodes 511, 512, 513, provides to each network node configuration parameters, such as, for example, information indicating a set of candidate MCSs (e.g., QPSK, QAM16, QAM64, ...), a set of PRB utilizations (e.g., 100%, 75%, ...), and a set of DL blank slots (e.g., n=l, 2, 3, 4). Each network node 511, 512, 513, then uses the configuration parameters to perform the steps described above for obtaining the set(s) of SNR penalty values and then transmits the SNR penalty values to the centralized computation module 502. The centralized computation module 502 then may compute a set of average SNR penalty values and generate LUT 290. The generated LUT 290 may then be distributed to the network nodes 511, 512, and 513 (and possibly other network nodes) to be used by the network nodes LA function 214.

[0040] FIG. 6 is a flow chart illustrating a process 600, according to an embodiment, that is performed by network node 104. Process 600 may begin in step s602. Step s602 comprises scheduling a transmission to UE 102, wherein the transmission is scheduled to occur in a target slot, and a number of consecutive DL blanked slots immediately precede the target slot (the number of DL blanked slots that immediately precede the target slot may be zero). Step s604 comprises determining the number of consecutive DL blanked slots that immediately precede the target slot. Step s606 comprises selecting a resource for the transmission using the determined number of consecutive DL blanked slots, wherein the selected resource is an MCS or a set of CCEs. Step s606 comprises performing the transmission using the selected resource.

[0041] In one embodiment, selecting a resource for the transmission using the determined number of consecutive DL blanked slots comprises using the determined number of consecutiveDL blanked slots to select a candidate MCS from a set of candidate MCSs comprising a first candidate MCS and a second candidate MCS.

[0042] In one embodiment, using the determined number of consecutive DL blanked slots to select a candidate MCS from the set of candidate MCSs comprises: using the determined number of consecutive DL blanked slots to determine a first penalty value for the first candidate MCS; determining, for the first candidate MCS, a first estimated SNR using the first penalty value; assigning a first score to the first candidate MCS based on the first estimated SNR; using the determined number of consecutive DL blanked slots to determine a second penalty value for the second candidate MCS; determining, for the second candidate MCS, a second estimated SNR using the second penalty value; assigning a second score to the second candidate MCS based on the second estimated SNR; and comparing the first score with the second score.

[0043] In one embodiment, the first score associated to the first candidate MCS indicates an estimated spectral efficiency of the first candidate MCS, and the second score associated to the second candidate MCS indicates an estimated spectral efficiency of the second candidate MCS.

[0044] In one embodiment, selecting the MCS comprises selecting the first candidate MCS as a result of determining that the estimated spectral efficiency for the first candidate MCS is higher than an estimated spectral efficiency for each other candidate MCS.

[0045] In one embodiment, using the determined number of consecutive DL blanked slots to determine a first penalty value for the first candidate MCS comprises obtaining the first penalty value from a LUT, such as LUT 290, where the LUT maps an n-tuple to the first penalty value, and the n-tuple comprises an identifier identifying the first candidate MCS and a value specifying the determined number of consecutive DL blanked slots.

[0046] In one embodiment, the n-tuple further comprises a physical resource block, PRB, utilization value. For example, as shown in FIG. 4, the n-tuple may be a 3-tuple consisting of a PRB utilization value, an MCS ID, and a value specifying the determined number of consecutive DL blanked slots.

[0047] FIG. 7 is a block diagram of network node 104, according to some embodiments. As shown in FIG. 7, network node 104 may comprise: processing circuitry (PC) 702, whichcomprises one or more processors (P) 755 (e.g., a general purpose microprocessor and / or one or more other processors, such as an application specific integrated circuit (ASIC), field- programmable gate arrays (FPGAs), and the like), which processors may be co-located in a single housing or in a single data center or may be geographically distributed (e.g., network node 104 may be a distributed, cloud computing system comprising two or more computers or a monolithic computing system consisting of a single computer); a network interface 768 comprising a transmitter (Tx) 765 and a receiver (Rx) 767 for enabling network node 104 to transmit data to and receive data from other nodes connected to a network 110 (e.g., an Internet Protocol (IP) network) to which network interface 768 is connected; radio unit 202 (e.g., radio transceiver circuitry comprising an Rx 747 and a Tx 745) coupled to an antenna system 749 for wireless communication with UEs or other nodes; and a storage unit (a.k.a., “data storage system”) 708, which may include one or more non-volatile storage devices and / or one or more volatile storage devices. In embodiments where PC 702 includes a programmable processor, a computer readable storage medium (CRSM) 742 may be provided. CRSM 742 may store a computer program (CP) 743 comprising computer readable instructions (CRI) 744. CRSM 742 may be a non-transitory computer readable medium, such as, magnetic media (e.g., a hard disk), optical media, memory devices (e.g., random access memory, flash memory), and the like. In some embodiments, the CRI 744 of computer program 743 is configured such that when executed by PC 702, the CRI causes network node 104 to perform steps described herein (e.g., steps described herein with reference to one or more flow charts). In other embodiments, network node 104 may be configured to perform steps described herein without the need for code. That is, for example, PC 702 may consist merely of one or more ASICs. Hence, the features of the embodiments described herein may be implemented in hardware and / or software.

[0048] While various embodiments are described herein, it should be understood that they have been presented by way of example only, and not limitation. Thus, the breadth and scope of this disclosure should not be limited by any of the above-described exemplary embodiments. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the disclosure unless otherwise indicated herein or otherwise clearly contradicted by context.

[0049] As used herein transmitting a message “to” or “toward” an intended recipient encompasses transmitting the message directly to the intended recipient or transmitting themessage indirectly to the intended recipient (i.e., one or more other nodes are used to relay the message from the source node to the intended recipient). Likewise, as used herein receiving a message “from” a sender encompasses receiving the message directly from the sender or indirectly from the sender (i.e., one or more nodes are used to relay the message from the sender to the receiving node). Further, as used herein “a” means “at least one” or “one or more.”

[0050] Additionally, while the processes described above and illustrated in the drawings are shown as a sequence of steps, this was done solely for the sake of illustration. Accordingly, it is contemplated that some steps may be added, some steps may be omitted, the order of the steps may be re-arranged, and some steps may be performed in parallel.

Claims

CLAIMS1. A method (600) performed by a network node (104), the method comprising: scheduling (s602) a transmission to a user equipment, UE (102), wherein the transmission is scheduled to occur in a target slot, and a number of consecutive downlink, DL, blanked slots immediately precede the target slot; determining (s604) the number of consecutive DL blanked slots that immediately precede the target slot; selecting (s606) a resource for the transmission using the determined number of consecutive DL blanked slots; and performing (s608) the transmission using the selected resource, wherein the selected resource is a modulation and coding scheme, MCS, or a set of control channel elements, CCEs.

2. The method of claim 1 , wherein selecting a resource for the transmission using the determined number of consecutive DL blanked slots comprises using the determined number of consecutive DL blanked slots to select a candidate MCS from a set of candidate MCSs comprising a first candidate MCS and a second candidate MCS.

3. The method of claim 2, wherein using the determined number of consecutive DL blanked slots to select a candidate MCS from the set of candidate MCSs comprises: using the determined number of consecutive DL blanked slots to determine a first penalty value for the first candidate MCS; determining, for the first candidate MCS, a first estimated signal-to-noise ratio, SNR, using the first penalty value; assigning a first score to the first candidate MCS based on the first estimated SNR; using the determined number of consecutive DL blanked slots to determine a second penalty value for the second candidate MCS; determining, for the second candidate MCS, a second estimated SNR using the second penalty value;assigning a second score to the second candidate MCS based on the second estimated SNR; and comparing the first score with the second score.

4. The method of claim 3, wherein the first score associated to the first candidate MCS indicates an estimated spectral efficiency of the first candidate MCS, and the second score associated to the second candidate MCS indicates an estimated spectral efficiency of the second candidate MCS.

5. The method of claim 4, wherein selecting the MCS comprises selecting the first candidate MCS as a result of determining that the estimated spectral efficiency for the first candidate MCS is higher than an estimated spectral efficiency for each other candidate MCS.

6. The method of any one of claims 3-5, wherein using the determined number of consecutive DL blanked slots to determine a first penalty value for the first candidate MCS comprises obtaining the first penalty value from a look-up- table, LUT (290).

7. The method of claim 6, wherein the LUT maps an n-tuple to the first penalty value, and the n-tuple comprises an identifier identifying the first candidate MCS and a value specifying the determined number of consecutive DL blanked slots.

8. The method of claim 7, wherein the n-tuple further comprises a physical resource block, PRB, utilization value.

9. A computer program (743) comprising instructions (744) which when executed by processing circuitry (702) of a network node (104) causes the network node to perform the method of any one of claims 1-7.

10. A carrier containing the computer program of claim 9, wherein the carrier is one of an electronic signal, an optical signal, a radio signal, and a computer readable storage medium (742).

11. A network node (104), the network node being configured to perform a method comprising: scheduling (s602) a transmission to a user equipment, UE (102), wherein the transmission is scheduled to occur in a target slot, and a number of consecutive downlink, DL, blanked slots immediately precede the target slot; determining (s604) the number of consecutive DL blanked slots that immediately precede the target slot; selecting (s606) a resource for the transmission using the determined number of consecutive DL blanked slots; and performing (s608) the transmission using the selected resource, wherein the selected resource is a modulation and coding scheme, MCS, or a set of control channel elements, CCEs.

12. The network node of claim 11, wherein selecting a resource for the transmission using the determined number of consecutive DL blanked slots comprises using the determined number of consecutive DL blanked slots to select a candidate MCS from a set of candidate MCSs comprising a first candidate MCS and a second candidate MCS.

13. The network node of claim 12, wherein using the determined number of consecutive DL blanked slots to select a candidate MCS from the set of candidate MCSs comprises: using the determined number of consecutive DL blanked slots to determine a first penalty value for the first candidate MCS; determining, for the first candidate MCS, a first estimated signal-to-noise ratio, SNR, using the first penalty value; assigning a first score to the first candidate MCS based on the first estimated SNR; using the determined number of consecutive DL blanked slots to determine a second penalty value for the second candidate MCS;determining, for the second candidate MCS, a second estimated SNR using the second penalty value; assigning a second score to the second candidate MCS based on the second estimated SNR; and comparing the first score with the second score.

14. The network node of claim 13, wherein the first score associated to the first candidate MCS indicates an estimated spectral efficiency of the first candidate MCS, and the second score associated to the second candidate MCS indicates an estimated spectral efficiency of the second candidate MCS.

15. The network node of claim 14, wherein selecting the MCS comprises selecting the first candidate MCS as a result of determining that the estimated spectral efficiency for the first candidate MCS is higher than an estimated spectral efficiency for each other candidate MCS.

16. The network node of any one of claims 13-15, wherein using the determined number of consecutive DL blanked slots to determine a first penalty value for the first candidate MCS comprises obtaining the first penalty value from a look-up- table, LUT (290).

17. The network node of claim 16, wherein the LUT maps an n-tuple to the first penalty value, and the n-tuple comprises an identifier identifying the first candidate MCS and a value specifying the determined number of consecutive DL blanked slots.

18. The network node of claim 17, wherein the n-tuple further comprises a physical resource block, PRB, utilization value.

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