US-20260128832-A1 - TECHNIQUES FOR SRS ESTIMATION IN WIRELESS SYSTEMS

US20260128832A1US 20260128832 A1US20260128832 A1US 20260128832A1US-20260128832-A1

Abstract

An apparatus for use in a base station includes processing circuitry to perform SRS sequence de-mapping of OFDM symbols to generate a de-mapped sequence. The OFDM symbols correspond to a UL stream with SRS transmissions from a plurality of UEs. A first least square (LS) estimation is performed based on the de-mapped sequence to obtain a first LS sequence. A time domain (TD) transformation and a frequency domain (FD) transformation is applied to the first LS sequence to generate a first partial SRS channel estimate sequence. A second LS estimation is performed based on the de-mapped sequence to obtain a second LS sequence. The second LS sequence is filtered to generate a second partial SRS channel estimate sequence. A full SRS channel estimate sequence corresponding to the SRS transmissions is generated based on the first and second partial SRS channel estimate sequences.

Inventors

Yi Liang
Wenquan Zhang
Thushara Hewavithana

Assignees

INTEL CORPORATION

Dates

Publication Date: 20260507
Application Date: 20221115

Claims (20)

1 - 20 . (canceled)
21 . An apparatus for use in a base station, the apparatus comprising: processing circuitry, wherein to configure the base station for sounding reference signal (SRS) estimation in a Fifth Generation New Radio (5G NR) and beyond wireless network, the processing circuitry is to: perform SRS sequence de-mapping of orthogonal frequency division multiplexing (OFDM) symbols to generate a de-mapped sequence, the OFDM symbols corresponding to an uplink (UL) stream with SRS transmissions from a plurality of user equipments (UEs); perform a first least square (LS) estimation based on the de-mapped sequence to obtain a first LS sequence; apply a time domain (TD) transformation and a frequency domain (FD) transformation to the first LS sequence to generate a first partial SRS channel estimate sequence; perform a second LS estimation based on the de-mapped sequence to obtain a second LS sequence; filter the second LS sequence to generate a second partial SRS channel estimate sequence; and generate a full SRS channel estimate sequence corresponding to the SRS transmissions, based on the first partial SRS channel estimate sequence and the second partial SRS channel estimate sequence; and memory coupled to the processing circuitry and configured to store the OFDM symbols.
22 . The apparatus of claim 21 , wherein the processing circuitry is to: apply FD windowing to the first LS sequence to obtain a first windowed LS sequence.
23 . The apparatus of claim 22 , wherein to apply the TD transformation, the processing circuitry is to: apply an inverse discrete Fourier transformation (IDFT) on the first windowed LS sequence to generate a TD sequence; and perform signal-to-noise ratio (SNR) estimation to determine SNR associated with the TD sequence.
24 . The apparatus of claim 23 , wherein the processing circuitry is to: perform TD windowing per transmission port using the TD sequence to obtain a windowed TD sequence.
25 . The apparatus of claim 24 , wherein to perform the FD transformation, the processing circuitry is to: apply a discrete Fourier transformation (DFT) on the windowed TD sequence to generate a second windowed LS sequence.
26 . The apparatus of claim 25 , wherein the processing circuitry is to: remove the FD windowing from the second windowed LS sequence to generate a first channel estimate sequence; and remove a subset of sub-carriers from both edges of the first channel estimate sequence to generate the first partial SRS channel estimate sequence.
27 . The apparatus of claim 23 , wherein the processing circuitry is to: perform the second LS estimation based on the de-mapped sequence and the SNR to obtain the second LS sequence.
28 . The apparatus of claim 27 , wherein the processing circuitry is to: perform the second LS estimation for a pre-selected cyclic shift associated with an SRS transmission of the SRS transmissions, the SRS transmission originating from one of the plurality of UEs.
29 . The apparatus of claim 28 , wherein the processing circuitry is to: filter edge portions of the second LS sequence to generate the second partial SRS channel estimate sequence, each of the edge portions comprising a subset of sub-carriers associated with the pre-selected cyclic shift.
30 . A computer-readable storage medium that stores instructions for execution by one or more processors of a base station, the instructions to configure the base station for sounding reference signal (SRS) estimation in a Fifth Generation New Radio (5G NR) and beyond wireless network, and to cause the base station to perform operations comprising: performing SRS sequence de-mapping of orthogonal frequency division multiplexing (OFDM) symbols to generate a de-mapped sequence, the OFDM symbols corresponding to an uplink (UL) stream with SRS transmissions from a plurality of user equipments (UEs); performing a first least square (LS) estimation based on the de-mapped sequence to obtain a first LS sequence; applying a time domain (TD) transformation and a frequency domain (FD) transformation to the first LS sequence to generate a first partial SRS channel estimate sequence; performing a second LS estimation based on the de-mapped sequence to obtain a second LS sequence; filtering the second LS sequence to generate a second partial SRS channel estimate sequence; and generating a full SRS channel estimate sequence corresponding to the SRS transmissions, based on the first partial SRS channel estimate sequence and the second partial SRS channel estimate sequence.
31 . The computer-readable storage medium of claim 30 , the operations further comprising: applying FD windowing to the first LS sequence to obtain a first windowed LS sequence.
32 . The computer-readable storage medium of claim 31 , wherein the instructions for applying the TD transformation further comprise: applying an inverse discrete Fourier transformation (IDFT) on the first windowed LS sequence to generate a TD sequence; and performing signal-to-noise ratio (SNR) estimation to determine SNR associated with the TD sequence.
33 . The computer-readable storage medium of claim 32 , the operations further comprising: performing TD windowing per transmission port using the TD sequence to obtain a windowed TD sequence.
34 . The computer-readable storage medium of claim 33 , wherein the instructions for performing the FD transformation further comprise: applying a discrete Fourier transformation (DFT) on the windowed TD sequence to generate a second windowed LS sequence.
35 . The computer-readable storage medium of claim 34 , the operations further comprising: removing the FD windowing from the second windowed LS sequence to generate a first channel estimate sequence; and removing a subset of sub-carriers from both edges of the first channel estimate sequence to generate the first partial SRS channel estimate sequence.
36 . The computer-readable storage medium of claim 32 , the operations further comprising: performing the second LS estimation based on the de-mapped sequence and the SNR to obtain the second LS sequence.
37 . The computer-readable storage medium of claim 36 , the operations further comprising: performing the second LS estimation for a pre-selected cyclic shift associated with an SRS transmission of the SRS transmissions, the SRS transmission originating from one of the plurality of UEs.
38 . The computer-readable storage medium of claim 37 , the operations further comprising: filtering edge portions of the second LS sequence to generate the second partial SRS channel estimate sequence, each of the edge portions comprising a subset of sub-carriers associated with the pre-selected cyclic shift.
39 . A method for sounding reference signal (SRS) estimation in a Fifth Generation New Radio (5G NR) and beyond wireless network, the method comprising: performing SRS sequence de-mapping of orthogonal frequency division multiplexing (OFDM) symbols to generate a de-mapped sequence, the OFDM symbols corresponding to an uplink (UL) stream with SRS transmissions from a plurality of user equipments (UEs); performing a discrete Fourier transformation (DFT)-based signal processing sequence using the OFDM symbols to obtain a first partial SRS channel estimate sequence corresponding to the SRS transmissions; performing a minimum mean square error (MMSE)-based signal processing sequence using the OFDM symbols to obtain a second partial SRS channel estimate sequence corresponding to the SRS transmissions; concatenating the first partial SRS channel estimate sequence and the second partial SRS channel estimate sequence to generate a full SRS channel estimate sequence corresponding to the SRS transmissions; and estimating a UL channel associated with the plurality of UEs based on the full SRS channel estimate sequence.

Description

TECHNICAL FIELD Aspects pertain to wireless communications. Some aspects relate to wireless networks including 3GPP (Third Generation Partnership Project) networks, 3GPP LTE (Long Term Evolution) networks, 3GPP LTE-A (LTE Advanced) networks, (MulteFire, LTE-U), and fifth-generation (5G) networks including 5G new radio (NR) (or 5G-NR) networks, 5G-LTE networks such as 5G NR unlicensed spectrum (NR-U) networks, Integrated Access and Backhaul (IAB) networks, and other unlicensed networks including Wi-Fi, CBRS (OnGo), etc. Other aspects are directed to techniques for sounding reference signal (SRS) estimation in wireless systems including 5G-NR and beyond wireless networks. BACKGROUND Mobile communications have evolved significantly from early voice systems to today's highly sophisticated integrated communication platform. With the increase in different types of devices communicating with various network devices, the usage of 3GPP LTE systems has increased. The penetration of mobile devices (user equipment or UEs) in modern society has continued to drive demand for a wide variety of networked devices in many disparate environments. Fifth-generation (5G) wireless systems are forthcoming and are expected to enable even greater speed, connectivity, and usability. Next-generation 5G networks (or NR networks) are expected to increase throughput, coverage, and robustness and reduce latency and operational and capital expenditures. 5G-NR networks will continue to evolve based on 3GPP LTE-Advanced with additional potential new radio access technologies (RATs) to enrich people's lives with seamless wireless connectivity solutions delivering fast, rich content and services. As the current cellular network frequency is saturated, higher frequencies, such as millimeter wave (mmWave) frequency, can be beneficial due to their high bandwidth. Potential LTE operation in the unlicensed spectrum includes (and is not limited to) the LTE operation in the unlicensed spectrum via dual connectivity (DC), or DC-based LAA, and the standalone LTE system in the unlicensed spectrum, according to which LTE-based technology solely operates in the unlicensed spectrum without requiring an “anchor” in the licensed spectrum, called MulteFire. Further enhanced operation of LTE and NR systems in the licensed, as well as unlicensed spectrum, is expected in future releases and 5G systems. Such enhanced operations can include techniques for SRS estimation in wireless systems including 5G-NR and beyond wireless networks. BRIEF DESCRIPTION OF THE FIGURES In the figures, which are not necessarily drawn to scale, like numerals may describe similar components in different views. Like numerals having different letter suffixes may represent different instances of similar components. The figures illustrate generally, by way of example, but not by way of limitation, various aspects discussed in the present document. FIG. 1A illustrates an architecture of a network, in accordance with some aspects. FIG. 1B and FIG. 1C illustrate a non-roaming 5G system architecture in accordance with some aspects. FIG. 2, FIG. 3, and FIG. 4 illustrate various systems, devices, and components that may implement aspects of disclosed embodiments. FIG. 5 illustrates graphs of mean square error (MSE) performance of discrete Fourier transform (DFT)-based SRS channel estimation, in accordance with some aspects. FIG. 6 is a flow diagram showing techniques for SRS estimation, in accordance with some aspects. FIG. 7 illustrates graphs of SRS estimation performance based on the disclosed techniques of FIG. 6, in accordance with some aspects. FIG. 8, FIG. 9, and FIG. 10 illustrate example processing in the DFT processing branch used during the SRS estimation of FIG. 6, in accordance with some aspects. FIG. 11 illustrates an example processing in the minimum mean square error (MMSE) processing branch used during the SRS estimation of FIG. 6, in accordance with some aspects. FIG. 12 illustrates an example concatenation processing used during the SRS estimation of FIG. 6, in accordance with some aspects. FIG. 13 is a flow diagram illustrating a method for SRS estimation in a wireless system, in accordance with some aspects. FIG. 14 illustrates a block diagram of a communication device such as an evolved Node-B (eNB), a new generation Node-B (gNB) (or another RAN node), an access point (AP), a wireless station (STA), a mobile station (MS), or a user equipment (UE), in accordance with some aspects. DETAILED DESCRIPTION The following description and the drawings sufficiently illustrate aspects to enable those skilled in the art to practice them. Other aspects may incorporate structural, logical, electrical, process, and other changes. Portions and features of some aspects may be included in or substituted for, those of other aspects. Aspects outlined in the claims encompass all available equivalents of those claims. FIG. 1A illustrates an architecture of a network in accordance with some aspec