Peak-to-average power ratio reduction for multiple resource unit allocation in wireless networks

Abstract

The present disclosure relates to a wireless network, and generally to the allocation of multiple resource units (MRUs) in the wireless network, which may be a wireless local area network (WLAN) according to the WiFi standard. Therefore, embodiments of the present disclosure respectively provide a wireless network device and a corresponding method for MRU allocation. The wireless network device is used to select a training signal for the MRU, wherein the MRU includes two or more RUs arranged in the frequency domain, and the training signal includes a training sequence for each RU. Further, for at least one RU, the wireless network device is used to apply a phase value subset to the training sequence of the at least one RU, wherein the phase value subset is selected for the at least one RU from a phase value set assigned to the MRU.

Description

Technical Field

[0001] The present disclosure relates to a wireless network, and generally to resource unit (RU) allocation in a wireless network. Specifically, the present disclosure relates to multiple resource unit (MRU) allocation in a wireless network, where the wireless network may be a wireless local area network (WLAN) configured according to, for example, a WiFi standard. Embodiments of the present disclosure each provide a wireless network device and corresponding method suitable for MRU allocation. Background Art

[0002] MRU allocation is widely accepted for future implementations in wireless networks, such as in next-generation Wi-Fi standards. MRU allocation in wireless networks provides a method for more efficient channel utilization. MRU allocation implies non-contiguous frequency allocation, i.e., multiple non-contiguous RUs. Because it is a new technology in wireless networks, particularly in Wi-Fi standards, specific implementations of this MRU allocation are still relatively rare.

[0003] Specifically, there is a need to efficiently implement MRU allocation in wireless networks (particularly according to the WiFi standard). However, efficient implementation is not simple. For example, as shown in the following sections of this disclosure, simply implementing MRU allocation in such wireless networks can significantly affect the physical properties of the signals transmitted in the wireless network. Summary of the Invention

[0004] As provided later in this disclosure, embodiments of the present disclosure are based on the following analysis and problems identified by the inventors. Briefly, the inventors discovered that simple MRU allocation in a wireless network can increase the peak-to-average-power-ratio (PAPR), an important metric in wireless network technology.

[0005] The 802.11ax standard introduces the orthogonal frequency division multiple access (OFDMA) format, in which the entire bandwidth (BW) is divided into blocks, and the blocks are defined as RUs. The transmitted signal can be allocated by multiple RUs, where different RUs can be assigned to different stations (i.e., wireless network devices). Therefore, the size of the RU can be defined by a number of frequency tones, which can include 26, 52, 106, 242, 484, or 996 tones. For example, a 20MHz BW can include 9 RUs of 26 tones, 4 RUs of 52 tones, and so on. Figure 1 Depicted.

[0006] Figure 2 and Figure 3 The structure of the RU in 40MHz and 80MHz is depicted separately. Larger bandwidths (including 240MHz and 320MHz in 802.11be) are repetitions of the 80MHz structure. Each RU is referenced using an index notation, where the index starts from the left side of the bandwidth (i.e., the leftmost 26RU is the first 26RU and the rightmost 26RU is the ninth 26RU).

[0007] In 802.11be, MRU allocation is generally foreseen, where more than one RU is allocated to a single station or group of stations (i.e., wireless network devices). This means discontinuous BW allocations (e.g., Figure 4 As shown, multiple RUs (here at least the first RU and the second RU) are set in the frequency domain of an MRU).

[0008] Currently, the 802.11be standard foresees two types of MRU allocations:

[0009] Only large RUs, that is, RUs greater than or equal to 20 MHz (RU242, RU484, RU996, etc.), can be combined into MRUs.

[0010] Only small RUs (RU26, RU52, RU106) can be combined into MRUs within the 20MHz boundary.

[0011] This standard currently does not support the combination of small RU and large RU.

[0012] The transmitted signal typically includes one or more training sequences (e.g., a short training field (STF), a long training field (LTF), a high-efficiency STF (HE-STF), or a high-efficiency LTF (HE-LTF)) preceding the data portion. These training sequences enable the receiving side to synchronize to the transmitted signal and perform wireless channel estimation. Typically, these training sequences are designed to have a low PAPR (specifically, a PAPR lower than that of the data portion of the transmitted signal) to ensure high accuracy in channel estimation. However, in older WiFi standard versions (e.g., 802.11a / n / ac / ax), the design of the training sequences assumes that a continuous bandwidth is allocated for transmission (downlink (DL) and / or uplink (UL)). Therefore, the PAPR is, at best, optimized with respect to this assumption. If current training sequences were to be reused for MRU allocation in a wireless network, this would result in a higher PAPR (specifically, a PAPR higher than the continuous BW).

[0013] Figure 5 An example comparison of the PAPR for continuous BWs and the PAPR for MRU allocation is shown, specifically for an MRU consisting of large RUs and an MRU consisting of small RUs. The HE-LTF sequence defined in the 802.11ax standard is used. This HE-LTF is applied to each RU as it is defined for single RU transmission. Figure 5 The x-axis in the graph represents different combinations of RUs, where the index is aligned with the 802.11be definition (i.e., the first number represents a larger RU index and the second number represents a smaller RU index). It can be seen that the PAPR of HE-LTF increases by 1.5dB to 2dB with a large RU combination (see Figure 5 (a)), increases by 1.5dB to 3dB in the case of small RU combinations (see Figure 5 (b)).

[0014] As mentioned above, the PAPR of the training sequence is designed to be lower than the PAPR of the data portion. Therefore, the impact of MRU on the PAPR of the data portion is also examined. Figure 6 In this respect, the PAPR of the data portion is shown (where, for example, the data in the data portion may be random and thus exemplarily represented here by a cumulative distribution function (CDF)). It can be seen that for large RUs (see Figure 6 (a)) and small RU (see Figure 6(b)), the PAPR of the data portion increases by 0.5 dB to 1 dB, which is less than the PAPR of the HE-LTF. Therefore, it can be understood that there are problems with the design of reusing the current training sequence (such as the HE-LTF sequence). Therefore, in the case of MRU allocation, new or updated training sequences should be considered to reduce the PAPR.

[0015] Figure 7 A theoretical explanation for the PAPR problem described above is shown. In the case of MRUs, the time domain signal can be represented as a combination of multiple domain signals, each generated by a single RU (here, the first and second RUs). The impact of MRU allocation on PAPR is related to the combined peak value of these transmitted signals, where in some samples, the sum of two or more peak values ​​produces a higher total peak value.

[0016] Generally, the PAPR problem has been addressed in early versions of the WiFi standard. For example, the training sequence is designed to minimize the PAPR metric. In addition, WiFi introduced constant phase rotation, which is also believed to reduce PAPR at large bandwidths. Figure 8 Such a phase rotation is shown, as defined for an 80 MHz BW in 802.11ac.

[0017] Applying constant phase rotation can reduce PAPR and is defined for BWs of 40 / 80 / 160 MHz. Extensions of this approach for BWs of 240 MHz and 320 MHz are also provided, with different choices of constant phase rotation given as examples.

[0018] However, the main problem with this approach (including extensions to 240MHz and 320MHz) is that a constant phase rotation is designed to allocate the entire BW:

[0019] • Constant phase results in incoherent combining of multiple peaks but does not change the position of the peaks in the time domain.

[0020] Different MRUs may require different phases to be applied to the same portion of the tone to optimize PAPR. For example, the combination of the first 20 MHz and the third 20 MHz may require a different phase value than the combination of the first 20 MHz and the fourth 20 MHz. Therefore, PAPR optimization cannot be guaranteed by applying a constant phase rotation to the same portion of the BW.

[0021] Another problem is that this method can only be applied to PAPR optimization of large RU combinations, while in the case of MRU with small RU combinations, an efficient implementation method is also needed to optimize PAPR.

[0022] In view of the above-mentioned problems and shortcomings, embodiments of the present disclosure are intended to provide a solution to the problem of MRU allocation affecting PAPR. Specifically, the purpose is to provide a wireless network device and corresponding method that can allocate MRUs in a wireless network (particularly in a wireless network based on the WiFi standard) without any impact on PAPR (or at least significantly reducing the impact).

[0023] This object is achieved by the embodiments of the present disclosure described in the attached independent claims. Advantageous implementations of the embodiments of the present disclosure are further defined in the dependent claims.

[0024] The theoretical considerations underlying the embodiments of the present disclosure are Figure 9 In principle, the chance of peaks combining to higher values ​​can be reduced if two things are achieved: a change in the position of the peaks in the time domain, and avoiding coherent combining of the signals. This can be achieved by applying a cyclic shift to the OFDM symbols in the time domain (see Figure 9 ) and / or by adding a phase offset. Figure 9 It will be appreciated that the peak positions can be shifted, thereby preventing the combination of high peaks. Equivalent to a cyclic shift in the frequency domain is multiplying the frequency pitch of the RU by a phase value, for example, by a linear phase and a phase offset. The phase offset can actually be the initial value of the linear phase.

[0025] A first aspect of the present disclosure provides a wireless network device for MRU allocation, which is used to: select a first training signal for a first MRU, wherein the first MRU includes two or more RUs arranged in the frequency domain, and the first training signal includes a training sequence of each RU of the first MRU; for at least one RU of the first MRU, apply a first phase value subset of the training sequence of at least one RU of the first MRU, wherein the first phase value subset is selected for at least one RU of the first MRU from a first phase value set allocated to the first MRU.

[0026] Specifically, the wireless network device of the first aspect may also provide a training signal thus modified (i.e., a signal including a training sequence modified by applying the first phase value subset) to the receiving device. The wireless network device may also provide data after transmission of the training signal, specifically, the data is allocated to the receiving device on the first MRU. Advantageously, applying the first phase value subset to the training sequence of one or more RUs of the first MRU may significantly reduce the PAPR - this is in line with the above considerations. It should be noted that if this application is performed on more than one RU of the first MRU, each RU may be assigned a different first phase value subset. The "first phase value subset" may be any phase value group included in the "first phase value set".

[0027] Furthermore, each MRU can be assigned a different set of phase values. For example, the first MRU can be assigned a first set of phase values, and the second MRU can be assigned a second set of phase values. Furthermore, for each RU of a particular MRU, a specific subset of phase values ​​can be selected from the set of phase values ​​assigned to that particular MRU. For example, the set or subset of phase values ​​can include {-π, -π / 2, 0, π / 2, π}, i.e., a plurality of phase values.

[0028] In an implementation of the first aspect, the wireless network device is further used to: select a second training signal for a second MRU, wherein the second MRU includes two or more RUs arranged in the frequency domain, and wherein the second training signal includes a training sequence for each RU of the second MRU; for at least one RU of the second MRU, apply a second phase value subset to the training sequence of at least one RU of the second MRU, wherein the second phase value subset is selected for at least one RU of the second MRU from a second phase value set assigned to the second MRU.

[0029] Specifically, the first MRU and the second MRU are different MRUs. Therefore, different MRUs can be assigned different phase value sets. These different phase value sets may include different phase value subsets, but may also have a common specific phase value subset. This implementation method can more efficiently reduce the PAPR. It should be noted that if this application is performed on more than one RU of the second MRU, each RU can be assigned a different second phase value subset. The "second phase value subset" can be any phase value group included in the "second phase value set".

[0030] In an implementation of the first aspect, the first phase value subset consists of a first linear phase and a first phase offset, and the first phase value set consists of a first linear phase set and a first phase offset set; and / or the second phase value subset consists of a second linear phase and a second phase offset, and the second phase value set consists of a second linear phase set and a second phase offset set.

[0031] Any linear phase can be or include a set of phase values ​​with constant gaps between them. Applying a linear phase to a given RU can mean multiplying the frequency tone of that given RU by the phase value of the applied linear phase. For example, the first tone of a given RU can be multiplied by a phase value of 0, the second tone of the given RU can be multiplied by a phase value of π / N, the third tone of the given RU can be multiplied by a phase value of 2*π / N, and so on. Therefore, a linear phase can also be defined as a sequence of phase values.

[0032] For example, if k is represented as the index of a frequency tone within the i-th RU of a particular MRU (eg, the first and / or second MRU), where the RU includes K tones, and where xk is the value of the training sequence defined for the kth tone, then the shifted signal of the i-th RU can be given by:

[0033]

[0034] Here, M is the number of RUs included in a specific MRU.

[0035] This implementation may also include:

[0036] • For any training sequence, a specific linear phase and a specific phase offset can be defined, which can be applied to the tones of one or more or each RU comprised by a specific MRU.

[0037] Linear phase and phase offset can be defined to optimize the PAPR of each MRU, while in case of different MRUs, different subsets of phase values ​​can be applied to the same RU.

[0038] • Multiple RUs within a specific MRU or each RU can be multiplied by a different linear phase and / or a different phase offset.

[0039] For both the transmitting side (eg, at a wireless network device) and the receiving side, specifically for each MRU, the values ​​of the linear phase and the phase offset may be known in advance. However, the actual implementation designs of the transmitting and receiving devices may be different.

[0040] In an implementation manner of the first aspect, the first MRU and the second MRU have one or more common RUs; or, the first MRU and the second MRU have no common RUs.

[0041] In an implementation of the first aspect, the first linear phase set includes one or more linear phases, which are not included in the second linear phase set; and / or the first phase offset set includes one or more phase offsets, which are not included in the second phase offset set.

[0042] In an implementation of the first aspect, the first linear phase set and / or the second linear phase set include linear phases defined in the range of [-π, π], wherein the granularity is the linear phase value n is an integer; and / or the first phase offset set and / or the second phase offset set includes phase offsets defined in the range [-π, π], wherein the granularity is the phase offset m is an integer.

[0043] In an implementation of the first aspect, the wireless network device is further configured to: for each RU of the first MRU and / or the second MRU, apply the first and / or second phase value subsets to the training sequences of the RUs of the first MRU and / or the second MRU.

[0044] In this way, PAPR can be reduced more efficiently.

[0045] In one implementation of the first aspect, the first and / or second phase value subsets are applied to the training sequences of at least one RU of the first MRU and / or the second MRU by multiplying the values ​​of the training sequences by values ​​in the first and / or second phase value subsets.

[0046] In an implementation of the first aspect, the values ​​of the first and / or second linear phases and the first and / or second phase offsets are defined by a single value set; or the values ​​of the first and / or second linear phases and the first and / or second phase offsets are defined by a first value set and a second value set, wherein the first value set defines a constant phase offset value and the second value set defines the values ​​of the first and / or second linear phases, wherein the constant phase offset is added to each value of the first and / or second linear phase, respectively.

[0047] In an implementation of the first aspect, different subsets of first and / or second phase values ​​are selected for at least two RUs of the first MRU and / or the second MRU.

[0048] In an implementation of the first aspect, a different subset of first and / or second phase values ​​is selected for each RU of the first MRU and / or the second MRU.

[0049] In an implementation of the first aspect, a first and / or second phase value subset of zero is selected for at least one RU of the first MRU and / or the second MRU.

[0050] In an implementation of the first aspect, a first and / or second phase value subset is selected for at least one RU of the first MRU and / or the second MRU to minimize the PAPR.

[0051] Furthermore, the first and / or second sets of phase values ​​assigned to the first and / or second MRUs may be selected or created to minimize the PAPR.

[0052] In one implementation of the first aspect, each RU includes multiple frequency tones, and each value of the first and / or second phase value subset selected for at least one RU of the first MRU and / or the second MRU is associated with one of the frequency tones of at least one RU of the first MRU and / or the second MRU.

[0053] In one implementation of the first aspect, the wireless network device is further used to: for at least one RU of the first MRU and / or the second MRU, only apply selected values ​​of the first and / or second phase value subsets selected for at least one RU of the first MRU and / or the second MRU to the training sequence of at least one RU of the first MRU and / or the second MRU, wherein the selected values ​​are values ​​of the first and / or second phase value subsets, which are associated with each frequency tone, each second frequency tone, or each fourth frequency tone of at least one RU of the first MRU and / or the second MRU.

[0054] Thus, the wireless network device of the first aspect is capable of using 1X, 2X and / or 4X formats.

[0055] In one implementation of the first aspect, a first and / or second subset of phase values ​​is selected for at least one RU of the first MRU and / or the second MRU based on whether the selected value is associated with every frequency tone, every second frequency tone, or every fourth frequency tone.

[0056] In one implementation of the first aspect, the first MRU and / or the second MRU only includes larger RUs, each RU having a bandwidth greater than 20 MHz, or the first MRU and / or the second MRU only includes smaller RUs, each RU having a bandwidth less than 20 MHz.

[0057] Therefore, the wireless network device of the first aspect can use all different types of MRUs.

[0058] In an implementation of the first aspect, the training sequence of the first training signal and / or the second training signal includes at least one of the following: a legacy LTF (L-LTF) sequence or a legacy STF (L-STF) sequence or an extreme high throughput STF (EHT-STF) sequence or an EHT-LTF sequence.

[0059] In one implementation of the first aspect, the wireless network device is further used to: provide an indication of a first and / or second phase value subset for multiplying a training sequence of at least one RU of the first MRU and / or the second MRU; or provide an indication of a first and / or second phase value subset for multiplying a training sequence of at least one RU of the first MRU and / or the second MRU.

[0060] Specifically, the indication may be provided to the receiving side. Alternatively, for example, if the phase value is always applied and is known by both the transmitting side (wireless network device) and the receiving side, no indication may be provided. The receiving side may be pre-configured with relevant information about the first and / or second phase value subsets.

[0061] A second aspect of the present disclosure provides a method for allocating multiple resource units (MRUs) in a wireless network, the method comprising: selecting a first training signal for a first MRU, wherein the first MRU includes two or more RUs arranged in a frequency domain, and the first training signal includes a training sequence for each RU of the first MRU; for at least one RU of the first MRU, applying a first phase value subset of the training sequence of at least one RU of the first MRU, wherein the first phase value subset is selected for at least one RU of the first MRU from a first phase value set assigned to the first MRU.

[0062] In an implementation of the second aspect, the method further includes: selecting a second training signal for a second MRU, wherein the second MRU includes two or more RUs arranged in the frequency domain, and wherein the second training signal includes a training sequence for each RU of the second MRU; for at least one RU of the second MRU, applying a second phase value subset to the training sequence of at least one RU of the second MRU, wherein the second phase value subset is selected for at least one RU of the second MRU from a second phase value set assigned to the second MRU.

[0063] In an implementation of the second aspect, the first phase value subset consists of a first linear phase and a first phase offset, and the first phase value set consists of a first linear phase set and a first phase offset set; and / or the second phase value subset consists of a second linear phase and a second phase offset, and the second phase value set consists of a second linear phase set and a second phase offset set.

[0064] In an implementation manner of the second aspect, the first MRU and the second MRU have one or more common RUs; or, the first MRU and the second MRU have no common RUs.

[0065] In an implementation of the second aspect, the first linear phase set includes one or more linear phases, which are not included in the second linear phase set; and / or the first phase offset set includes one or more phase offsets, which are not included in the second phase offset set.

[0066] In an implementation of the second aspect, the first linear phase set and / or the second linear phase set include linear phases defined in the range of [-π, π], wherein the granularity is the linear phase value n is an integer; and / or the first phase offset set and / or the second phase offset set includes phase offsets defined in the range [-π, π], wherein the granularity is the phase offset m is an integer.

[0067] In an implementation of the second aspect, the method further includes: for each RU of the first MRU and / or the second MRU, applying the first and / or second phase value subsets to the training sequences of the RUs of the first MRU and / or the second MRU.

[0068] In one implementation of the second aspect, the first and / or second phase value subsets are applied to the training sequences of at least one RU of the first MRU and / or the second MRU by multiplying the values ​​of the training sequences by values ​​in the first and / or second phase value subsets.

[0069] In an implementation of the second aspect, the values ​​of the first and / or second linear phases and the first and / or second phase offsets are defined by a single value set; or the values ​​of the first and / or second linear phases and the first and / or second phase offsets are defined by a first value set and a second value set, wherein the first value set defines a constant phase offset value and the second value set defines the values ​​of the first and / or second linear phases, wherein the constant phase offset is added to each value of the first and / or second linear phase, respectively.

[0070] In an implementation of the second aspect, different first and / or second phase value subsets are selected for at least two RUs of the first MRU and / or the second MRU.

[0071] In an implementation of the second aspect, a different subset of first and / or second phase values ​​is selected for each RU of the first MRU and / or the second MRU.

[0072] In an implementation of the second aspect, a first and / or second phase value subset of zero is selected for at least one RU of the first MRU and / or the second MRU.

[0073] In an implementation of the second aspect, a first and / or second phase value subset is selected for at least one RU of the first MRU and / or the second MRU to minimize the PAPR.

[0074] In one implementation of the second aspect, each RU includes multiple frequency tones, and each value of the first and / or second phase value subset selected for at least one RU of the first MRU and / or the second MRU is associated with one of the frequency tones of at least one RU of the first MRU and / or the second MRU.

[0075] In an implementation of the second aspect, the method further includes: for at least one RU of the first MRU and / or the second MRU, applying only selected values ​​of the first and / or second phase value subsets selected for at least one RU of the first MRU and / or the second MRU to the training sequence of at least one RU of the first MRU and / or the second MRU, wherein the selected values ​​are values ​​of the first and / or second phase value subsets, which are associated with each frequency tone, each second frequency tone, or each fourth frequency tone of at least one RU of the first MRU and / or the second MRU.

[0076] In one implementation of the second aspect, a first and / or second subset of phase values ​​is selected for at least one RU of the first MRU and / or the second MRU based on whether the selected value is associated with every frequency tone, every second frequency tone, or every fourth frequency tone.

[0077] In one implementation of the second aspect, the first MRU and / or the second MRU only includes larger RUs, each RU having a bandwidth greater than 20 MHz, or the first MRU and / or the second MRU only includes smaller RUs, each RU having a bandwidth less than 20 MHz.

[0078] In an implementation of the second aspect, the training sequence of the first training signal and / or the second training signal includes at least one of the following: a legacy LTF (L-LTF) sequence or a legacy STF (L-STF) sequence or an extreme high throughput STF (EHT-STF) sequence or an EHT-LTF sequence.

[0079] In one implementation of the second aspect, the method further includes: providing an indication of a first and / or second subset of phase values ​​for multiplying a training sequence of at least one RU of the first MRU and / or the second MRU; or providing an indication of a first and / or second subset of phase values ​​for multiplying a training sequence of at least one RU of the first MRU and / or the second MRU.

[0080] A third aspect of the present disclosure provides a computer program, comprising program code. When the program code is executed on a computer, the program code is used to perform the method according to the second aspect or any implementation manner thereof.

[0081] A fourth aspect of the present disclosure provides a non-transitory storage medium storing executable program code. When a processor executes the executable program code, the method according to the third aspect or any one of its implementations is performed.

[0082] It should be noted that all devices, elements, units and modules described in this disclosure can be implemented by software or hardware elements or any type of combination thereof. All steps performed by the various entities described in this disclosure and the functions described to be performed by the various entities are intended to indicate that the corresponding entities are used to perform the corresponding steps and functions. Although in the description of the following specific embodiments, the specific functions or steps performed by external entities are not reflected in the description of the specific detailed elements of the entities that perform the specific steps or functions, it should be clear to the technician that these methods and functions can be implemented by corresponding hardware or software elements or any combination thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] The following description of specific embodiments in conjunction with the accompanying drawings illustrates the above aspects and implementation methods.

[0084] Figure 1 The RU positions at 20 MHz are shown.

[0085] Figure 2 The RU locations for 40 MHz are shown.

[0086] Figure 3 The RU locations for 80 MHz are shown.

[0087] Figure 4 An example of MRU allocation is shown.

[0088] Figure 5 A comparison of PAPR on HE-LTF for MRU allocation is shown.

[0089] Figure 6 A comparison of PAPR on data for MRU allocation is shown.

[0090] Figure 7 The high PAPR theory with MRU allocation is shown.

[0091] Figure 8 An example of phase rotation defined in the 11ac WiFi standard is shown.

[0092] Figure 9 A time domain signal with a cyclic shift is shown.

[0093] Figure 10 A wireless network device according to an embodiment of the present disclosure is shown.

[0094] Figure 11 A wireless network device applying linear phase and phase offset according to an embodiment of the present disclosure is shown.

[0095] Figure 12 A wireless network device that applies linear phase and phase offset according to MRU according to an embodiment of the present disclosure is shown.

[0096] Figure 13 A wireless network device applying relatively linear phase and phase offset according to an embodiment of the present disclosure is shown.

[0097] Figure 14 The PAPR reduction with the embodiment of the present disclosure is shown.

[0098] Figure 15 The PAPR for a specific case is shown.

[0099] Figure 16 A method according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0100] Figure 10 A wireless network device 100 according to an embodiment of the present disclosure is shown. Wireless network device 100 is used for MRU allocation in a wireless network (specifically, in a WLAN, and more specifically, in a wireless network configured according to the WiFi standard). Therefore, wireless network device 100 can be configured according to and conform to the WiFi standard. Wireless network device 100 can be a station or a terminal and can communicate with one or more other wireless network devices (stations or terminals) in a wireless network.

[0101] The wireless network device 100 is configured to select a first training signal 101 for a first MRU 102. Generally, the wireless network device 100 can be configured to select a training signal 101 for each MRU. The first MRU 102 includes two or more RUs 103 arranged in the frequency domain, i.e., the two or more RUs 103 are separated / remote in the frequency direction, for example, they occupy different sets of subcarriers (e.g., in the case of OFDM). The first training signal 101 includes a training sequence 104 for each RU 103 of the first MRU 102 (two RUs 103 and two training sequences 104 are shown here as an example).

[0102] The wireless network device 100 may apply the first phase value subset 105 to at least one RU 103 of the first MRU 102 (specifically, to one or more RUs 103, or each RU 103 of the first MRU 102). For example, for a given RU 103, the first phase value subset 105 may be applied to the training sequence 104 of the given RU 103. Figure 1 , illustratively, a first subset of phase values ​​105 (denoted as θ1 (1 . . . N)) is applied to a first RU 103 of a first MRU 102 , and a different first subset of phase values ​​105 (denoted as θ2 (1 . . . N)) is applied to a second RU 103 of the first MRU 102 .

[0103] Any first subset 105 of phase values ​​may include one or more phase values. The first subset 105 of phase values ​​is selected for at least one RU 103 of the first MRU 102. Specifically, the first subset 105 of phase values ​​is selected from the first set of phase values ​​assigned to the first MRU 102. It should be noted that the set of phase values ​​may include one or more subsets of phase values ​​and / or may include one or more phase values.

[0104] Different first phase value subsets 105 may be applied to multiple or each RU 103 of the first MRU 102. Applying one or more first phase value subsets 105 to one or more training sequences 104 of one or more RUs 103 of the first MRU 102 results in the wireless network device 100 providing / transmitting modified training signals 106.

[0105] The wireless network device 100 may include a processor or processing circuit (not shown) for executing, performing, or initiating the various operations of the wireless network device 100 described herein. The processing circuit may include hardware and / or the processing circuit may be controlled by software. The hardware may include analog circuits or digital circuits, or both. The digital circuit may include components such as an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), or a multi-purpose processor.

[0106] The wireless network device 100 may also include a memory circuit that stores one or more instructions that can be executed by the processor or processing circuit (specifically, executed under the control of software). For example, the memory circuit may include a non-transitory storage medium that stores executable software code that, when executed by the processor or processing circuit, causes the wireless network device 100 to perform various operations.

[0107] In one embodiment, the processing circuit includes one or more processors and non-transitory memory connected to the one or more processors. The non-transitory memory may carry executable program code, which, when executed by the one or more processors, causes the wireless network device 100 to perform, proceed, or initiate the operations or methods described herein.

[0108] Figure 11 The wireless network device 100 according to an embodiment of the present disclosure is shown. Figure 10Based on the embodiment shown. Figure 11 In this embodiment, the first phase value subset 105 consists of a first linear phase and a first phase offset, respectively. Thus, the first phase value set consists of a first linear phase set and a first phase offset set. That is, the first linear phase and the first phase offset can be applied as the first phase value subset 105 to one or more or each RU 103 of the first MRU 102. A different first linear phase and a different first phase offset can be applied to each given RU 103 of the first MRU 102. For example, a different first linear phase and first phase offset can be independently applied to each of a plurality of selected RUs 103 included in the first MRU 102. Figure 11 The example shows two different first linear phases and first phase offsets applied to the training sequence 104 of the first RU 103 and the training sequence 104 of the second RU 103 of the first MRU 102, respectively. It should be noted that the "first linear phase" is any linear phase included in the "first linear phase set." Similarly, the "first phase offset" is any phase offset included in the "first phase offset set."

[0109] First, a first training signal 101 is selected (e.g., based on BW, a specific first MRU, etc.), and then the values ​​of the training signal 101 (specifically, the training sequences 104 for different RUs 103) are multiplied by the values ​​of the first linear phase with a first phase offset, as they can be predefined for each RU 103 within the MRU 102.

[0110] Figure 12 The wireless network device 100 according to the embodiment is shown. Figure 10 and Figure 11 Specifically, Figure 12It is shown that different linear phase sets and different phase offset sets can be applied to the RUs 103 / 203 of different MRUs 102 / 202, specifically for each different MRU used. Accordingly, the wireless network device 100 can also be configured to select a second training signal 201 for a second MRU 202 (different from the first MRU 102), wherein the second MRU 202 includes two or more RUs 203 (the RUs 103 / 203 can be the same or different) arranged in the frequency domain, i.e., they are separated in the frequency direction, for example, they occupy different sets of subcarriers (for example, in the case of OFDM). The second training signal 201 includes a training sequence 204 for each RU 203 of the second MRU 202. Furthermore, the wireless network device 100 is configured to apply, for at least one RU 203 of the second MRU 202 (i.e., for one or more RUs 203 of the second MRU 202, or each RU 203), a specific second linear phase and second phase offset (or generally, a second phase value subset 205) to the training sequence 201 of the at least one RU 203. The second linear phase can be selected from a second linear phase set, and the second phase offset can be selected from a second phase offset set of the at least one RU 203 of the second MRU 203. Therefore, the second linear phase set and the second phase offset set can be assigned to the second MRU 202. It should be noted that the "second linear phase" is any linear phase included in the "second linear phase set." The "second phase offset" is any phase offset included in the "second phase offset set."

[0111] For example, different MRUs (types) 102, 202 including RUs 103, 203 may use different (first / second) linear phases and phase offsets to optimize PAPR. Thus, when the same RU 103 or 203 is allocated in two different MRUs 102, 202, different linear phases and phase offsets may be applied. Figure 12 An example is shown where, in a first case, an MRU 102 includes a first RU and a second RU, and in a second case, a different MRU 202 includes (identical) first and third RUs. In both cases, the linear first / second phases and first / second phase offsets of the training sequence 104 applied to the first RU in the first MRU 102 and the second MRU 202, respectively, are shown to be different.

[0112] Furthermore, the wireless network device 100 can work with all types of MRUs 102, 202. For example, the first MRU 102 and / or the second MRU 103 can include large RUs 103, 203 only for any BW greater than 20 MHz, or can include small RUs 103, 203 only for a BW of 20 MHz.

[0113] Wireless network device 100 can also operate with training signals 101, 201 of different formats. For example, the 802.11be standard uses training sequence designs with different carrier spacings, where the same bandwidth can be sampled with different numbers of frequency tones. Therefore, the maximum number of frequency tones in the training signal format is represented by 4X. If every second tone is used, the format is represented by 2X. If only every fourth tone is used, the format is represented by 1X. The linear phase and phase offset applicable to different formats can be designed in two ways:

[0114] • For the 2X and 1X formats, a subset of the 4X format may be applied (ie, for example, meaning that every second and fourth value of the first and / or second linear phase, respectively, may be used), and the phase offset is the same as for the 4X format.

[0115] Different linear phase and phase offset can be designed for each format.

[0116] It is also possible to combine the two approaches described above, and to design a linear phase or a phase shift specifically for each format.

[0117] The wireless network device 100 may also operate with at least the following training signals 101 / 201 or training sequences 104 / 204: L-LTF; L-STF; EHT-STF; and / or EHT-LTF.

[0118] Furthermore, the first / second linear phase and phase offset can be applied as an absolute or relative linear phase and phase offset. As described above in the theoretical considerations, the embodiments of the present disclosure can be considered to implement cyclic shifts in the time domain, where the goal is to separate the peaks of different signals associated with the RUs 103, 203 within the MRU 102, 202. The offsets in the time domain can be considered as absolute values, where each signal is shifted by a number of time samples greater than zero (e.g., Figure 11 ), or relative shifts can be considered, where one signal is not shifted (zero linear phase) and all others are shifted by a number of time samples greater than zero (e.g. Figure 13 The same situation can also be applied to the phase offset. Any RU 102, 202 can be selected as a RU 102, 202 with zero linear phase and / or zero phase offset.

[0119] Any first / second linear phase and first / second phase offset can be defined in two different ways:

[0120] Defined as a single set of values

[0121] Defined as two sets of values where w defines the constant phase offset applied to all tones within RU 103, 203, and v k Defines the linear phase applied to each tone within the MRU 102, 202.

[0122] The values ​​of the first / second linear phase and the first / second phase offset may be predefined, and for each RU 103, 203 within a particular MRU 102, 202, the values ​​may be selected from a predefined list:

[0123] Any linear phase can be defined in the range θ∈{−π,π}, where the granularity is Where Δ∈{1, 2, ..., N Lin}. N Lin The maximum possible granularity of the linear phase values ​​can be defined.

[0124] Any phase shift can be The granularity is defined within the range of Where Δ∈{1, 2, ..., N Offset}. N Offset The maximum possible granularity of the phase offset values ​​can be defined.

[0125] In addition, the wireless network device 100 may provide an indication of the applied linear phase and phase offset. For example, in order to support the receiving side in successfully detecting the transmitted signal, several indication methods may be defined for use by the transmitting side (wireless network device 100):

[0126] No indication: In this case, linear phase and phase offset are always applied to a given MRU (transmission), and specific values ​​are known in advance to the transmitting side (wireless network device 100) and the receiving side.

[0127] Indication of the use of linear phase and phase offset: In this case, the transmitting side (wireless network device 100) can decide whether to apply the first / second linear phase and phase offset and should indicate this in the transmitted signal. The values ​​of the first / second linear phase and phase offset can be known in advance.

[0128] Instruction to use linear phase and phase offset with specific values: In this case, the transmitting device (wireless network device 100) can decide which values ​​to use for the current transmission. Thus, the instruction can include an instruction to use linear phase and phase offset, as well as an indication of the specific values ​​selected for the current transmission.

[0129] In the following, it is demonstrated that the wireless network device 100 and the corresponding method achieve the desired goal of PAPR reduction. Therefore, the focus is on the difference between the PAPR reduction on the training sequence 104 and the PAPR reduction on the data portion.

[0130] Figure 14 Examples are shown of the PAPR reduction on the training sequence 104 that can be achieved in different cases of the MRU 102, 202. It can be seen that in most cases the PAPR reduction is reduced to a value comparable to the PAPR reduction of the data portion (0.5dB to 1dB).

[0131] Figure 15 PAPR values ​​for specific cases currently under discussion in the 802.11be standard are summarized.

[0132] Figure 16 A method 300 according to an embodiment of the present disclosure is shown. The method 300 can be performed by the wireless network device 100 described above. The method 300 is applicable to MRU allocation in a wireless network, such as MRU allocation in a WLAN. The method 300 includes step 301: selecting a first training signal 101 for a first MRU 102, wherein the first MRU 102 includes two or more RUs 103 arranged in the frequency domain, and wherein the first training signal 101 includes a training sequence 104 for each RU 103 of the first MRU 102. Further, in step 302, for at least one RU 103 of the first MRU 102 (specifically, for one or more or each RU 103 of the first MRU 102), a first phase value subset is applied to the training sequence 104 of the at least one RU 103 of the first MRU 103, wherein the first phase value subset is selected for the at least one RU 103 of the first MRU 102 from a first phase value set allocated to the first MRU 102.

[0133] The embodiments described in the present disclosure are not limited to specific training signals 101, 201. However, they support the reuse of existing sequences defined by older WiFi standards. Further, embodiments of the present disclosure can be applied to 1x, 2x, and 4x signals. 1x and 2x linear phase values ​​can be considered as subsets of 4x (no additional memory is required). Through embodiments of the present disclosure, the impact of MRU allocation on PAPR can be minimized. The ratio between the PAPR on the training signals 101, 202 and the PAPR on the data portion of the transmitted signal may be affected by only 0.5dB. In addition, the implementation of the phase value subset (for example, by linear phase and phase offset), i.e., constant phase, is simple and does not require high computational complexity.

[0134] The present disclosure has been described with reference to various embodiments and implementations of the disclosure as examples. However, those skilled in the art will be able to understand and implement other variations when practicing the disclosed embodiments as claimed, based on a study of the drawings, the present disclosure, and the independent claims. In the claims and the specification, the word "comprising" does not exclude other elements or steps, and "a" does not exclude a plurality. A single element or other unit may fulfil the functions of several entities or items recited in the claims. The recitation of certain measures in different dependent claims does not indicate that a combination of these measures cannot be used in a beneficial implementation.

[0135] Hereinafter, examples are given to help understand the present disclosure.

[0136] Linear Phase RMS Example

[0137] θ∈{-π,π}, where the granularity is That is a total of 129 values

[0138] Phase offset RMS example

[0139] Among them, the particle size is That is, a total of 9 values

[0140] Example of linear phase RMS value of a combined MRU of two 26RUs at 20MHz BW

[0141] Examples of linear phase and phase offsets that result in PAPR reduction relative to the effective values ​​of linear phase and phase offsets given in the examples above are given below.

[0142]

[0143] Example of linear phase RMS value of a combined MRU of two 52RUs at 20MHz BW

[0144] Examples of linear phase and phase offsets that result in PAPR reduction relative to the effective values ​​of linear phase and phase offsets given in the examples above are given below.

[0145]

[0146] Example of linear phase RMS value for a combined MRU of 26RU and 52RU at 20MHz BW

[0147] Examples of linear phase and phase offsets that result in PAPR reduction relative to the effective values ​​of linear phase and phase offsets given in the examples above are given below.

[0148]

[0149] Example of linear phase RMS value for a combined MRU of 26RU and 106RU at 20MHz BW

[0150] Examples of linear phase and phase offsets that result in PAPR reduction relative to the effective values ​​of linear phase and phase offsets given in the examples above are given below.

[0151]

[0152] Example of linear phase RMS value for a combined MRU of 242RU and 484RU at 80MHz BW

[0153] Examples of linear phase and phase offsets that result in PAPR reduction relative to the effective values ​​of linear phase and phase offsets given in the examples above are given below.

[0154]

[0155] Example of linear phase RMS value for a combined MRU of 484RU and 996RU at 160MHz BW

[0156] Examples of linear phase and phase offsets that result in PAPR reduction relative to the effective values ​​of linear phase and phase offsets given in the examples above are given below.

[0157]

[0158] Example of linear phase RMS values ​​for a combined MRU of 242RU, 484RU, and 996RU at 160MHz BW

[0159] Examples of linear phase and phase offsets that result in PAPR reduction relative to the effective values ​​of linear phase and phase offsets given in the examples above are given below.

[0160]

[0161] Example of linear phase RMS value of a combined MRU of three 996RUs at 320MHz BW

[0162] Examples of linear phase and phase offsets that result in PAPR reduction relative to the effective values ​​of linear phase and phase offsets given in the examples above are given below.

[0163]

[0164] Example of linear phase RMS values ​​for a 484RU and a combined MRU of two 996RUs at 240MHz BW

[0165] Examples of linear phase and phase offsets that result in PAPR reduction relative to the effective values ​​of linear phase and phase offsets given in the examples above are given below.

[0166]

Claims

1. A wireless network device for multiple resource unit (MRU) allocation, characterized in that: The wireless network device is used for: Selecting a first training signal for the first MRU, The first MRU includes two or more resource units RU arranged in the frequency domain, Wherein, the first training signal includes a training sequence of each RU of the first MRU; applying a first subset of phase values ​​to the training sequence of the at least one RU of the first MRU, wherein, from a first set of phase values ​​assigned to the first MRU, a first subset of phase values ​​is selected for the at least one RU of the first MRU; Wherein, each RU includes multiple frequency tones; Each value of the first and / or second subset of phase values ​​selected for the at least one RU of the first and / or second MRU is associated with one of the frequency tones of the at least one RU of the first and / or second MRU.

2. The wireless network device according to claim 1, wherein: Also used for: Selecting a second training signal for the second MRU, The second MRU includes two or more RUs arranged in the frequency domain. The second training signal includes a training sequence of each RU of the second MRU; applying a second subset of phase values ​​to the training sequence of the at least one RU of the second MRU, The second phase value subset is selected for the at least one RU of the second MRU from a second set of phase values ​​allocated to the second MRU.

3. The wireless network device according to claim 2, wherein: The first phase value subset consists of a first linear phase and a first phase offset, and the first phase value set consists of a first linear phase set and a first phase offset set; and / or The second phase value subset consists of a second linear phase and a second phase offset, and the second phase value set consists of a second linear phase set and a second phase offset set.

4. The wireless network device according to claim 2, wherein: The first MRU and the second MRU have one or more RUs in common; or The first MRU and the second MRU have no common RU.

5. The wireless network device according to claim 3, wherein: The first linear phase set includes one or more linear phases, and the one or more linear phases are not included in the second linear phase set; and / or The first set of phase offsets includes one or more phase offsets that are not included in the second set of phase offsets.

6. The wireless network device according to claim 3 or claim 5, wherein: The first linear phase set and / or the second linear phase set are included in The linear phase is defined within the range of , n is an integer; and / or The first phase offset set and / or the second phase offset set are included in The phase offset is defined within the range of , m is an integer.

7. The wireless network device according to any one of claims 2 to 5, characterized in that: Used for: For each RU of the first MRU and / or the second MRU, the first and / or second subset of phase values ​​are applied to the training sequence of the RU of the first MRU and / or the second MRU.

8. The wireless network device according to claim 3, wherein: The first and / or second subsets of phase values ​​are applied to the training sequences of the at least one RU of the first MRU and / or the second MRU by multiplying values ​​of the training sequences by values ​​in the first and / or second subsets of phase values.

9. The wireless network device according to claim 8, wherein: The values ​​of the first and / or second linear phase and the first and / or second phase offset are defined by a single set of values; or The values ​​of the first and / or second linear phases and the first and / or second phase offsets are defined by a first value set and a second value set, wherein the first value set defines constant phase offset values ​​and the second value set defines values ​​of the first and / or second linear phases, wherein the constant phase offset is added to each value of the first and / or second linear phase, respectively.

10. The wireless network device according to any one of claims 2 to 5, characterized in that: Different first and / or second phase value subsets are selected for at least two RUs of the first MRU and / or the second MRU.

11. The wireless network device according to any one of claims 1 to 5, characterized in that: A different subset of first and / or second phase values ​​is selected for each RU of the first MRU and / or the second MRU.

12. The wireless network device according to any one of claims 1 to 5, characterized in that: A first and / or second subset of phase values ​​of zero is selected for at least one RU of the first MRU and / or the second MRU.

13. The wireless network device according to any one of claims 1 to 5, characterized in that: The first and / or second phase value subsets are selected for the at least one RU of the first MRU and / or the second MRU to minimize a peak-to-average power ratio (PAPR).

14. The wireless network device according to claim 1, wherein: Also used for: applying, for the at least one RU of the first MRU and / or the second MRU, only selected values ​​of the first and / or second phase value subset selected for the at least one RU of the first MRU and / or the second MRU to the training sequence of the at least one RU of the first MRU and / or the second MRU, The selected values ​​are values ​​of the first and / or second phase value subsets, the values ​​being associated with each frequency tone, each second frequency tone, or each fourth frequency tone of the at least one RU of the first MRU and / or the second MRU.

15. The wireless network device according to claim 14, wherein: The first and / or second subset of phase values ​​is selected for the at least one RU of the first MRU and / or the second MRU based on whether the selected value is associated with every frequency tone, every second frequency tone, or every fourth frequency tone.

16. The wireless network device according to any one of claims 1 to 5, characterized in that: The first MRU and / or the second MRU only include larger RUs, each RU having a bandwidth of more than 20 MHz, or The first MRU and / or the second MRU only includes smaller RUs, each RU having a bandwidth of less than 20 MHz.

17. The wireless network device according to any one of claims 2 to 5, characterized in that: The training sequence of the first training signal and / or the second training signal includes at least one of the following: a legacy long training field L-LTF sequence, a legacy short training field L-STF sequence, an extremely high throughput STF EHT-STF sequence, or an EHT-LTF sequence.

18. The wireless network device according to any one of claims 2 to 5, characterized in that: Also used for: providing an indication of the first and / or second subset of phase values ​​for multiplying the training sequence of the at least one RU of the first MRU and / or the second MRU; or An indication of the first and / or second subset of phase values ​​for multiplying the training sequence of the at least one RU of the first MRU and / or the second MRU is provided.

19. A method for allocating multiple resource units (MRUs) in a wireless network, characterized in that: The method comprises: Selecting a first training signal for the first MRU, The first MRU includes two or more RUs arranged in the frequency domain. Wherein, the first training signal includes a training sequence of each RU of the first MRU; applying a first subset of phase values ​​to the training sequence of the at least one RU of the first MRU, wherein, from a first set of phase values ​​assigned to the first MRU, a first subset of phase values ​​is selected for the at least one RU of the first MRU; Wherein, each RU includes multiple frequency tones; Each value of the first and / or second subset of phase values ​​selected for the at least one RU of the first and / or second MRU is associated with one of the frequency tones of the at least one RU of the first and / or second MRU.

20. A non-transitory computer storage medium storing program code, which, when executed by a processor, performs the method according to claim 19.

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