System and method for decoding in wireless communications

Abstract

A system and method for decoding in wireless communications is disclosed. In some embodiments, a method includes receiving a reference signal; generating a channel estimate based on the reference signal; determining a channel estimation error metric for channel estimation; receiving a transmission; calculating a log-likelihood ratio for each of a plurality of bit positions of the transmission based on the channel estimation error metric; and decoding the transmission based on the log-likelihood ratio. Calculating the log-likelihood ratio may include calculating a corrected log-likelihood ratio based at least on an uncorrected log-likelihood ratio.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of priority to U.S. Provisional Application No. 63 / 547,298, filed on November 3, 2023, the disclosure of which is incorporated herein by reference in its entirety as if fully set forth herein. Technical Field

[0003] The present disclosure relates generally to wireless communications. More specifically, the subject matter disclosed herein relates to improvements to systems and methods for decoding in wireless communications. Background Art

[0004] When a digital signal is received over a wireless channel, soft decision decoding may be employed to decode the received data in units that may be referred to as code blocks. Decoding may involve calculating the likelihood that each transmitted bit is either 0 or 1. The likelihood may be expressed as a log likelihood ratio. However, the estimate may be based on an estimate of the channel (e.g., an estimate of the channel response (e.g., an impulse response or frequency response of the channel)), which may not be known a priori. For example, a channel estimate may be generated by taking the ratio of the Fourier transform of the received signal to the Fourier transform of the transmitted signal (which may be a known reference signal).

[0005] To address this issue, a channel estimate can be generated.

[0006] One problem with the above approach is that the channel estimate may not be perfect, and errors in the channel estimate may lead to biases in the calculated log-likelihood ratios. Summary of the invention

[0007] To overcome these problems, systems and methods are described herein for log-likelihood computation in the presence of channel estimation errors.

[0008] The above methods improve the performance of systems using such methods because they provide improved log-likelihood values ​​(e.g., values ​​with reduced bias) in the presence of channel estimation errors compared to methods that do not account for channel estimation errors. In addition, the above methods can result in improved log-likelihood ratios, which can be used to improve decoding performance.

[0009] According to an embodiment of the present disclosure, a method is provided, comprising: receiving a reference signal; generating a channel estimate based on the reference signal; determining a channel estimation error metric for the channel estimate; receiving a transmission; calculating a log-likelihood ratio for each of a plurality of bit positions of the transmission based on the channel estimation error metric; and decoding the transmission based on the log-likelihood ratio, wherein calculating the log-likelihood ratio comprises: calculating a corrected log-likelihood ratio based at least on an uncorrected log-likelihood ratio.

[0010] In some embodiments, the corrected log-likelihood ratio is also equal to the uncorrected log-likelihood ratio further adjusted by one or more correction maps.

[0011] In some embodiments, a first one of the correction maps is based on a multiplication correction map.

[0012] In some embodiments, a first one of the correction maps comprises multiplication by an integer power of two.

[0013] In some embodiments, the method further comprises storing the log-likelihood ratio in a fixed point representation having a binary point location calculated based on the first term and a second term, the second term being an integer.

[0014] In some embodiments, the first correction mapping is based on a rank of transmission.

[0015] In some embodiments, the first correction mapping is based on a channel estimation error metric.

[0016] In some embodiments, the channel estimation error metric is based on a ratio of channel estimation error power to noise power.

[0017] In some embodiments, determining the channel estimation error metric comprises determining a channel estimation error power based on a weight of the time domain interpolation.

[0018] In some embodiments, determining the channel estimation error metric comprises determining a channel estimation error power further based on a correlation time of a channel response of a channel corresponding to the channel estimation error.

[0019] According to an embodiment of the present disclosure, a system is provided, comprising: one or more processors; and a memory storing instructions, which, when executed by the one or more processors, causes the following operations to be performed: receiving a reference signal; generating a channel estimate based on the reference signal; determining a channel estimation error metric for the channel estimate; receiving a transmission; calculating a log-likelihood ratio for each of a plurality of bit positions of the transmission based on the channel estimation error metric; and decoding the transmission based on the log-likelihood ratio, wherein calculating the log-likelihood ratio comprises calculating a corrected log-likelihood ratio based at least on an uncorrected log-likelihood ratio.

[0020] In some embodiments, the corrected log-likelihood ratio is also equal to the uncorrected log-likelihood ratio further adjusted by one or more correction maps.

[0021] In some embodiments, a first one of the correction maps is based on a multiplication correction map.

[0022] In some embodiments: a first correction map in the correction maps comprises multiplication by an integer power of 2; and the instructions, when executed by one or more processors, further cause the following operations to be performed: storing the log-likelihood ratio in a fixed-point representation having a binary point position calculated based on a first term and a second term, the second term being an integer.

[0023] In some embodiments, the first correction mapping is based on a rank of transmission.

[0024] In some embodiments, the first correction mapping is based on a channel estimation error metric.

[0025] In some embodiments, the channel estimation error metric is based on a ratio of channel estimation error power to noise power.

[0026] In some embodiments, determining the channel estimation error metric comprises determining a channel estimation error power based on a weight of the time domain interpolation.

[0027] In some embodiments, determining the channel estimation error metric comprises determining a channel estimation error power further based on a correlation time of a channel response of a channel corresponding to the channel estimation error.

[0028] According to an embodiment of the present disclosure, a system is provided, comprising: a component for processing; and a memory storing instructions, which, when executed by the component for processing, causes the following operations to be performed: receiving a reference signal; generating a channel estimate based on the reference signal; determining a channel estimation error metric for the channel estimate; receiving a transmission; calculating a log-likelihood ratio for each of a plurality of bit positions of the transmission based on the channel estimation error metric; and decoding the transmission based on the log-likelihood ratio, wherein calculating the log-likelihood ratio comprises calculating a corrected log-likelihood ratio based at least on an uncorrected log-likelihood ratio. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In the following sections, various aspects of the subject matter disclosed herein will be described with reference to exemplary embodiments shown in the accompanying drawings, in which:

[0030] Figure 1 A system including a user equipment (UE) and a network node (gNB) communicating with each other according to an embodiment is shown.

[0031] Figure 2 is a flow chart according to an embodiment.

[0032] Figure 3 is a block diagram of an electronic device in a network environment according to an embodiment. DETAILED DESCRIPTION

[0033] In the following detailed description, many specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be appreciated by those skilled in the art that the disclosed aspects can be practiced without these specific details. In other instances, well-known methods, processes, components, and circuits are not described in detail to avoid obscuring the subject matter disclosed herein.

[0034] References throughout this specification to "one embodiment" or "embodiment" mean that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment disclosed herein. Therefore, the phrases "in one embodiment" or "in an embodiment" or "according to an embodiment" (or other phrases with similar meanings) that appear in various places throughout this specification may not necessarily all indicate the same embodiment. In addition, specific features, structures or characteristics may be combined in any suitable manner in one or more embodiments. In this regard, as used herein, the word "exemplary" means "used as an example, instance or illustration". Any embodiment described herein as "exemplary" should not be interpreted as necessarily being preferred or advantageous over other embodiments. In addition, specific features, structures or characteristics may be combined in any suitable manner in one or more embodiments. In addition, depending on the context discussed herein, a singular term may include a corresponding plural form, and a plural term may include a corresponding singular form. Similarly, hyphenated terms (e.g., "two-dimensional", "predetermined", "pixel-specific", etc.) may occasionally be used interchangeably with corresponding non-hyphenated versions (e.g., "two-dimensional", "predetermined", "pixel-specific", etc.), and capitalized terms (e.g., "Counter Clock", "Row Select", "PIXOUT", etc.) may be used interchangeably with corresponding non-capitalized versions (e.g., "counter clock", "row select", "pixout", etc.). Such occasionally interchangeable usages should not be considered inconsistent with each other.

[0035] In addition, depending on the context discussed herein, singular terms may include corresponding plural forms, and plural terms may include corresponding singular forms. It should also be noted that the various drawings (including component drawings) shown and discussed herein are for illustrative purposes only and are not drawn to scale. For example, for clarity, the size of some elements may be exaggerated relative to other elements. In addition, if deemed appropriate, reference numerals are repeated in the drawings to indicate corresponding and / or similar elements.

[0036] The terms used herein are for the purpose of describing some example embodiments only and are not intended to limit the claimed subject matter. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprise" and / or "comprising", when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0037] It will be understood that when an element or layer is referred to as being on, "connected to" or "coupled to" another element or layer, it may be directly on, connected to or coupled to another element or layer, or there may be intermediate elements or layers. Conversely, when an element is referred to as being "directly on," "directly connected to" or "directly coupled to" another element or layer, there are no intermediate elements or layers. The same reference numerals always indicate the same element. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0038] As used herein, the terms "first," "second," and the like are used as labels for the nouns that follow them and do not imply any type of ordering (e.g., spatial, temporal, logical, etc.) unless explicitly so defined. In addition, the same reference numerals may be used across two or more figures to indicate parts, components, blocks, circuits, units, or modules having the same or similar functions. However, this usage is only for simplicity of illustration and ease of discussion; it does not mean that the construction or architectural details of such components or units are the same across all embodiments, or that such commonly referenced components / modules are the only way to implement some example embodiments disclosed herein.

[0039] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the subject matter belongs. It will be further understood that terms (such as those defined in commonly used dictionaries) should be interpreted as having a meaning consistent with their meaning in the context of the relevant art, and will not be interpreted in an idealized or overly formal sense unless explicitly so defined herein.

[0040] As used herein, the term "module" indicates any combination of software, firmware, and / or hardware configured to provide the functionality described herein in conjunction with the module. For example, software may be embodied as a software package, code, and / or instruction set or instructions, and the term "hardware" as used in any embodiment described herein may include, for example, individually or in any combination, components, hardwired circuits, programmable circuits, state machine circuits, and / or firmware storing instructions executed by programmable circuits. Modules may be collectively or individually embodied as circuits forming part of a larger system, such as, but not limited to, an integrated circuit (IC), a system on a chip (SoC), a component, and the like.

[0041] Figure 1 A system including a user equipment (UE) 105 and a network node (gNB) 110 in communication with each other is shown. The UE 105 may be a user device capable of connecting to a wireless network (e.g., a fifth generation (5G) cellular network), such as a mobile phone or a laptop or tablet computer capable of accessing a wireless network. The UE 105 may include a radio 115 and a processing circuit (or means for processing) 120, which may perform various methods disclosed herein, such as, Figure 2 For example, the processing circuit 120 may receive a transmission from the network node (gNB) 110 via the radio 115, and the processing circuit 120 may send a signal to the gNB 110 via the radio 115.

[0042] In operation, UE 105 may receive (i) a reference signal (e.g., a demodulation reference signal (DMRS)) and (ii) a data transmission (e.g., a physical downlink shared channel (PDSCH) transmission) from gNB 110. UE 105 may (i) perform noise estimation and channel estimation (CE) based on the received DMRS, and (ii) use the estimated noise and channel estimates (e.g., estimated channel characteristics resulting from a channel estimation process) to calculate a log likelihood ratio for each bit of one of the other transmissions. The channel estimate may include a frequency domain or time domain representation of the channel as a linear system (e.g., it may include or consist of an impulse response of the channel or a frequency response of the channel). For example, the frequency response of the channel may include the effects of frequency dependent attenuation (such as may occur due to diffraction around obstacles or ripple due to multipath). Similarly, in the presence of multipath, the impulse response of the channel may include multiple peaks corresponding to different paths that the signal may take from the transmitter to the receiver. UE 105 may then use the log likelihood ratio to decode the other transmission. However, due to errors in the channel estimates, the calculated log-likelihood ratios may be biased (and therefore less accurate than they would be in the absence of such bias). Therefore, improved log-likelihood ratios calculated using the methods disclosed herein may be used to improve decoding performance.

[0043] The connection between UE 105 and gNB 110 can be a multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system with the following system model.

[0044]

[0045] Where H = [h 0 …h L-1 ] is the channel impulse response of all layers, h i is the channel impulse response of the i-th layer, and n is the noise, where L represents the number of transmission layers, n r represents the number of receiving antennas, and Where N is a normal distribution.

[0046] The channel estimation error matrix can be defined as E = [e 0 … e L-1 ], where e i is the channel estimation error at the i-th layer, and in

[0047] E{e j,i}=0

[0048] and

[0049]

[0050] Therefore, the received signal at the PDSCH resource element (RE) can be expressed as the estimated channel CE error j and noise function, as follows:

[0051]

[0052] Since the channel estimate is obtained from the DMRS RE, e j Independent of the noise at the PDSCH RE (CE error e j is related to the noise at the DMRS RE), that is,

[0053] E{e j n H}=0.

[0054] In addition, assuming that the linear least mean square estimation (LMMSE) channel estimation is used, the CE error (e j ) is orthogonal to the channel estimate, that is,

[0055]

[0056] Therefore, ej Approximately White Gaussian and define

[0057]

[0058] It follows

[0059]

[0060] in

[0061]

[0062] in, Yes r ×n r The identity matrix, and LLR can be written as:

[0063]

[0064] Finally, by applying the maximum logarithmic mapping (MLM) approximation, the LLR is obtained as

[0065]

[0066] In some embodiments, the full Euclidean distance (ED) is used to calculate the log-likelihood ratio. As shown in Equation 1, the LLR calculation that fully incorporates the CE error power can be written as:

[0067]

[0068] For rank 2 MIMO detection, the LLRs can be obtained as

[0069]

[0070] As used herein, "rank" is the number of spatial channels used in a MIMO system. For example, in a system with two transmit antennas and two receive antennas, the rank can be 1 (e.g., if poor channel conditions adversely affect one of the spatial streams) or 2 (when there are favorable channel conditions). Euclidean distance scaling can be performed as follows. As shown in Equation 3, full ED adjustment can involve applying two corrections (or "correction mappings") on the traditional ED calculation (wherein "traditional ED calculation" means that the Euclidean distance calculation does not include these corrections): (i) scaling the traditional ED (e.g., applying a multiplicative correction mapping to the traditional ED), and (ii) applying an offset correction (e.g., an additive correction mapping) to the scaled ED value. As used herein, a "correction mapping" is a mapping from an uncorrected value to a correction value. However, in some cases, the gain using the additive correction mapping may be relatively small, and ED scaling (using the multiplicative correction mapping) is the correction mapping responsible for most of the performance improvement. Therefore, in some embodiments, only ED scaling is used. The equation for the LLR can then be written in the following lower complexity form:

[0071]

[0072] Although ED scaling reduces the complexity of accounting for CE error power when computing LLRs, using this solution may still involve significant hardware complexity.

[0073] Thus, in order to avoid computing the full Euclidean distance and to avoid per-ED scaling, we can use the form {1+λ|x| 2 The average scaling on the final calculated LLR of}=1+rank×λ is used as the average scaling for all and all The final LLR can be obtained as

[0074]

[0075] In Equation 5, the factor can be considered as the uncorrected log-likelihood ratio, which is corrected by using the correction factor The multiplicative correction mapping is adjusted to reduce or eliminate CE-error-related bias in the calculated log-likelihood ratio. It can be seen that this multiplicative correction mapping is based on (e.g., depends on) (i) the rank and (ii) the ratio λ of the channel estimate error power to the noise power.

[0076] Depending on the modulation order and the bit position k, is not necessarily true; however, to avoid per-ED scaling, the final scaling can still be approximated as 1+λE{|x|2}=1+rank×λ.

[0077] The computational complexity of the log-likelihood ratios may be further reduced by using a multiplicative correction factor (in the multiplicative correction mapping) that is equal to (e.g., rounded to be equal to) an integer power of 2, e.g., by replacing LLR scaling with a simple bit shift (which may correspond to multiplication by a power of 2). For example,

[0078]

[0079] where the rounding of the multiplication correction factor can be written as

[0080] q 2 =-round(log 2 (1+rank×λ)).

[0081] The benefit of applying LLR scaling in the form of a simple bit shift is that a bit shift q can be applied 2 As part of the final q factor (a factor used to determine the location of the binary point in the fixed-point representation of the log-likelihood ratio). For example, the q factor can be written as two parts q 1 and q 2 The sum of is as follows:

[0082] q=q 1 +q 2

[0083] Among them, q 2 is obtained as a function of the CE error, and q 1 is the residual tuning factor. The q factor (q) can be used to determine the location of the binary point in the fixed-point representation of the log-likelihood ratio. For example, the log-likelihood ratio can be stored in a fixed-point representation with the first term (q 1 ) and the second term (q 2 ) where, when the multiplicative correction factor is equal to an integer power of 2, the second term is an integer that is a power of 2, as discussed above.

[0084] The difficulty in tuning the q factor is that q is a function of several parameters such as rank, signal-to-noise ratio (SNR), Doppler spread, delay spread, subcarrier spacing (SCS), and modulation order, e.g.

[0085] q=func(rank,SNR,Dopp,DS,SCS,Mod).

[0086] However, as shown above, the effect of CE error power can be incorporated in the form of an LLR bit shift that can be applied as part of the q factor. For example, the q factor can be written as two parts q 1and q 2 The sum is q = q 1 +q 2 ,in:

[0087]

[0088] When this is done, as determined by simulation, the remainder of q (i.e., q 1 ) can be a function of rank, SNR, and modulation order only:

[0089] q 1 =func(rank,SNR,Mod).

[0090] The absence of dependence on Doppler spread, delay spread, and subcarrier spacing (SCS) can significantly simplify q 1 The calculation of q is simplified and thus the calculation of q is simplified. Doppler spread can be the spread of the spectrum of the signal as a result of the time-varying range rate. Delay spread can be the spread of the delay value due to the time-varying distance between the UE and the gNB, and the subcarrier spacing can be the frequency spacing between adjacent subcarriers of a component carrier (CC).

[0091] The CE error power that may be used as part of the calculation of the log-likelihood ratio may be calculated as follows, assuming that a frequency domain LMMSE (FD-LMMSE+TDI) channel estimate with time domain interpolation (TDI) is applied using a general form of time domain interpolation.

[0092] As defined in Equation 6, q 2 is a function of rank and

[0093] In the case of two DMRS symbols (the results are easily generalized to the case with more than two DMRS symbols), where t s represents the DMRS symbol position, where s∈{0,1}, where, represents the channel estimate at the tth OFDM symbol, where j represents the DMRS port index, and w j denotes the FD-LMMSE filter weight for the jth DMRS port, and v(t)=[v 0 (t)v 1 (t)] represents the TDI weight used to obtain the CE at the t-th OFDM symbol, which can be derived as follows For FD-LMMSE, the channel estimation output is

[0094]

[0095] And by applying TDI, the final CE result at the tth OFDM symbol can be obtained as

[0096]

[0097] Therefore, for the CE error power after TDI,

[0098]

[0099] Where P h,j =E{|h j (t)| 2}.

[0100] definition

[0101] γ s =r t (tt s )

[0102] And replace

[0103]

[0104] E{y(t s )y H (t s )}=R f

[0105] and

[0106]

[0107] It can be shown

[0108]

[0109] For the normalized FD-LMMSE estimation error (relative to P h Normalized),

[0110]

[0111] Averaging over all OFDM symbols (T∈{0,…,13}), for the CE error power after TDI, we get

[0112]

[0113] in, Therefore, for

[0114]

[0115] Because P hrepresents the per-port power on DMRS RE, and due to the structure of frequency domain orthogonal cover code (FD-OCC),

[0116]

[0117] Therefore, averaging over all ports, we can show

[0118]

[0119] in

[0120]

[0121] Among them, scl 1 Use one of the following values, depending on the number of DMRS ports:

[0122] For a DMRS port:

[0123]

[0124] For two or four DMRS ports:

[0125]

[0126] And for three DMRS ports:

[0127]

[0128] It can be seen that scl 1 Each expression of (and hence the expression of the CE error power ) based on (eg, depending on) (i) the weights of the time domain interpolation (eg, v 0 ) and (ii) the correlation time (γ) of the channel response of the channel corresponding to the channel estimation error.

[0129] In some embodiments, as mentioned above, UE 105 may calculate log-likelihood ratios for received transmissions (e.g., PDSCH transmissions) in a manner that reduces or avoids the presence of CE error-related bias in the log-likelihood ratios. UE 105 may achieve this using one of the methods disclosed herein, for example, by calculating uncorrected log-likelihood ratios and adjusting the uncorrected log-likelihood ratios by one or more correction mappings (e.g., additive or multiplicative correction mappings). In some embodiments, Figure 2Such a method is shown. The UE 105 may receive a reference signal at 205; the UE 105 may generate a channel estimate based on the reference signal at 210; the UE 105 may determine a channel estimation error metric for the channel estimate at 215; the UE 105 may receive a transmission (e.g., a PDSCH transmission) at 220; the UE 105 may calculate a log-likelihood ratio for each of a plurality of bit positions of the transmission based on the channel estimation error metric at 225; and the UE 105 may decode the transmission based on the log-likelihood ratio at 230.

[0130] As mentioned above, calculating the log-likelihood ratio by the UE 105 may include calculating a corrected log-likelihood ratio that is equal to the uncorrected log-likelihood ratio adjusted by one or more correction mappings. For example, the uncorrected log-likelihood ratio may be adjusted by a multiplicative correction mapping. The multiplicative correction factor used in the multiplicative correction mapping may be equal to (e.g., it may be rounded to be equal to) an integer power of 2; in such an embodiment, the computational cost of applying the multiplicative correction may be reduced because applying the multiplicative correction mapping may (i) correspond to a shift (if a fixed-point representation is used to represent the log-likelihood ratio), or (ii) correspond to a change in an exponent (if a floating-point representation is used to represent the log-likelihood ratio). In some embodiments, the log-likelihood ratio is stored in a fixed-point representation having a binary point position calculated as the sum of a first term and a second term. In an embodiment where the multiplicative correction factor is equal to an integer power of 2, the second term may be an integer power of 2.

[0131] Figure 3 3 is a block diagram of an electronic device 301 (eg, UE 105) in a network environment 300 according to an embodiment. The electronic device 301 may (eg, a processing circuit of the electronic device 301 may) perform some or all of the methods disclosed herein.

[0132] refer to Figure 3, the electronic device 301 in the network environment 300 may communicate with the electronic device 302 via a first network 398 (e.g., a short-range wireless communication network), or communicate with the electronic device 304 or the server 308 via a second network 399 (e.g., a long-range wireless communication network). The electronic device 301 may communicate with the electronic device 304 via the server 308. The electronic device 301 may include a processor 320, a memory 330, an input device 350, a sound output device 355, a display device 360, an audio module 370, a sensor module 376, an interface 377, a haptic module 379, a camera module 380, a power management module 388, a battery 389, a communication module 390, a subscriber identification module (SIM) card 396, or an antenna module 397. In one embodiment, at least one of the components (e.g., the display device 360 ​​or the camera module 380) may be omitted from the electronic device 301, or one or more other components may be added to the electronic device 301. Some of the components may be implemented as a single integrated circuit (IC). For example, the sensor module 376 (eg, a fingerprint sensor, an iris sensor, or an illumination sensor) may be embedded in the display device 360 ​​(eg, a display).

[0133] The processor 320 may execute software (eg, program 340 ) to control at least one other component (eg, hardware or software component) of the electronic device 301 coupled to the processor 320 , and may perform various data processing or calculations.

[0134] As at least part of data processing or calculation, the processor 320 may load commands or data received from another component (e.g., the sensor module 376 or the communication module 390) into the volatile memory 332, process the commands or data stored in the volatile memory 332, and store the resultant data in the non-volatile memory 334. The processor 320 (or "processing circuit" or "means for processing") may include a main processor 321 (e.g., a central processing unit (CPU) or an application processor (AP)) and an auxiliary processor 323 (e.g., a graphics processing unit (GPU), an image signal processor (ISP), a sensor hub processor, or a communication processor (CP)), wherein the auxiliary processor 323 may operate independently of the main processor 321 or in conjunction with the main processor 321. Additionally or alternatively, the auxiliary processor 323 may be adapted to consume less power than the main processor 321, or to perform a specific function. The auxiliary processor 323 may be implemented to be separate from the main processor 321 or to be a part of the main processor 321.

[0135] The auxiliary processor 323 may control at least some of the functions or states related to at least one component (e.g., display device 360, sensor module 376, or communication module 390) among the components of the electronic device 301 instead of the main processor 321 while the main processor 321 is in an inactive (e.g., sleep) state, or the auxiliary processor 323 may control at least some of the functions or states related to at least one component (e.g., display device 360, sensor module 376, or communication module 390) among the components of the electronic device 301 together with the main processor 321 while the main processor 321 is in an active state (e.g., executing an application). The auxiliary processor 323 (e.g., an image signal processor or a communication processor) may be implemented as a part of another component (e.g., a camera module 380 or a communication module 390) that is functionally related to the auxiliary processor 323.

[0136] The memory 330 may store various data used by at least one component of the electronic device 301 (e.g., the processor 320 or the sensor module 376). The various data may include, for example, software (e.g., program 340) and input data or output data for commands related thereto. The memory 330 may include a volatile memory 332 or a non-volatile memory 334. The non-volatile memory 334 may include an internal memory 336 and / or an external memory 338.

[0137] The program 340 may be stored as software in the memory 330 , and may include, for example, an operating system (OS) 342 , middleware 344 , or an application 346 .

[0138] The input device 350 may receive a command or data to be used by another component (eg, the processor 320) of the electronic device 301 from outside (eg, a user) of the electronic device 301. The input device 350 may include, for example, a microphone, a mouse, or a keyboard.

[0139] The sound output device 355 can output sound signals to the outside of the electronic device 301. The sound output device 355 can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as playing multimedia or recording, and the receiver can be used to receive incoming calls. The receiver can be implemented as a part of the speaker or as a separate speaker.

[0140] The display device 360 ​​can visually provide information to the outside (e.g., user) of the electronic device 301. The display device 360 ​​may include, for example, a display, a hologram device, or a projector, and a control circuit for controlling a corresponding one of the display, the hologram device, and the projector. The display device 360 ​​may include a touch circuit suitable for detecting a touch or a sensor circuit (e.g., a pressure sensor) suitable for measuring the strength of a force caused by a touch.

[0141] The audio module 370 can convert sound into an electrical signal, and vice versa. The audio module 370 can obtain sound via the input device 350, or output sound via the sound output device 355 or the earphone of the external electronic device 302 directly (eg, wired) or wirelessly coupled to the electronic device 301.

[0142] The sensor module 376 can detect the operating state (e.g., power or temperature) of the electronic device 301 or the environmental state (e.g., the state of the user) outside the electronic device 301, and then generate an electrical signal or data value corresponding to the detected state. The sensor module 376 may include, for example, a gesture sensor, a gyroscope sensor, an atmospheric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an infrared (IR) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illumination sensor.

[0143] The interface 377 may support one or more designated protocols for coupling the electronic device 301 directly (e.g., wired) or wirelessly with the external electronic device 302. The interface 377 may include, for example, a high-definition multimedia interface (HDMI), a universal serial bus (USB) interface, a secure digital (SD) card interface, or an audio interface.

[0144] The connection terminal 378 may include a connector via which the electronic device 301 may be physically connected to the external electronic device 302. The connection terminal 378 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (eg, a headphone connector).

[0145] The haptic module 379 may convert the electrical signal into mechanical stimulation (eg, vibration or movement) or electrical stimulation that can be recognized by the user via tactile or kinesthetic sense. The haptic module 379 may include, for example, a motor, a piezoelectric element, or an electrical stimulator.

[0146] The camera module 380 may capture still images or moving images. The camera module 380 may include one or more lenses, an image sensor, an image signal processor, or a flash. The power management module 388 may manage the power supplied to the electronic device 301. The power management module 388 may be implemented as at least a portion of a power management integrated circuit (PMIC), for example.

[0147] The battery 389 may supply power to at least one component of the electronic device 301. The battery 389 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0148] The communication module 390 can support establishing a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device 301 and an external electronic device (e.g., electronic device 302, electronic device 304, or server 308) and perform communication via the established communication channel. The communication module 390 may include one or more communication processors that can operate independently of the processor 320 (e.g., AP) and support direct (e.g., wired) communication or wireless communication. The communication module 390 may include a wireless communication module 392 (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module 394 (e.g., a local area network (LAN) communication module or a power line communication (PLC) module). A corresponding one of these communication modules can communicate via a first network 398 (e.g., a short-range communication network such as Bluetooth). TM , Wireless Fidelity (Wi-Fi) Direct, or Infrared Data Association (IrDA) standards) or a second network 399 (e.g., a telecommunication network such as a cellular network, the Internet, or a computer network (e.g., a LAN or a wide area network (WAN)))). These various types of communication modules may be implemented as a single component (e.g., a single IC), or may be implemented as multiple components (e.g., multiple ICs) separated from each other. The wireless communication module 392 may use user information (e.g., an International Mobile Subscriber Identity (IMSI)) stored in the subscriber identification module 396 to identify and authenticate the electronic device 301 in a communication network (such as a first network 398 or a second network 399).

[0149] The antenna module 397 may transmit or receive signals or power to or from the outside of the electronic device 301 (e.g., an external electronic device). The antenna module 397 may include one or more antennas, and at least one antenna suitable for a communication scheme used in a communication network (such as the first network 398 or the second network 399) may be selected from them by the communication module 390 (e.g., the wireless communication module 392), for example. Then, signals or power may be transmitted or received between the communication module 390 and the external electronic device via the selected at least one antenna.

[0150] A command or data may be sent or received between the electronic device 301 and the external electronic device 304 via a server 308 coupled to the second network 399. Each of the electronic devices 302 and 304 may be a device of the same type or a different type as the electronic device 301. All or some of the operations to be performed at the electronic device 301 may be performed at one or more of the external electronic devices 302, 304, or 308. For example, if the electronic device 301 should automatically perform a function or service, or in response to a request from a user or another device, the electronic device 301 may request one or more external electronic devices to perform at least a portion of the function or service instead of or in addition to performing the function or service. The one or more external electronic devices receiving the request may perform at least a portion of the requested function or service, or additional functions or additional services related to the request, and transmit the result of the execution to the electronic device 301. The electronic device 301 may provide the result as at least a part of the reply to the request with or without further processing the result. To this end, for example, cloud computing, distributed computing, or client-server computing technology may be used.

[0151] The subject matter and the embodiments of the operation described in this specification may be implemented in digital electronic circuits, or in computer software, firmware or hardware (including the structures disclosed in this specification and their structural equivalents), or in a combination of one or more of them. The embodiments of the subject matter described in this specification may be implemented as one or more computer programs, i.e., one or more modules of computer program instructions, which are encoded on a computer storage medium for execution by a data processing device or for controlling the operation of a data processing device. Alternatively or additionally, the program instructions may be encoded on an artificially generated propagation signal, for example, a machine-generated electrical, optical or electromagnetic signal, which is generated to encode information for transmission to a suitable receiver device for execution by a data processing device. The computer storage medium may be or be included in a computer-readable storage device, a computer-readable storage substrate, a random or serial access memory array or device, or a combination thereof. In addition, although the computer storage medium is not a propagation signal, the computer storage medium may be the source or destination of the computer program instructions encoded in the artificially generated propagation signal. The computer storage medium can also be, or be included in, one or more separate physical components or media (e.g., multiple CDs, disks, or other storage devices). In addition, the operations described in this specification can be implemented as operations performed by a data processing apparatus on data stored on one or more computer-readable storage devices or received from other sources.

[0152] Although this specification may contain many specific implementation details, the implementation details should not be interpreted as a limitation on the scope of any claimed subject matter, but rather as a description of features specific to a particular embodiment. Certain features described in the context of a separate embodiment in this specification may also be implemented in combination in a single embodiment. On the contrary, the various features described in the context of a single embodiment may also be implemented in multiple embodiments individually or in any suitable sub-combination. In addition, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from the claimed combination may be excluded from the combination in some cases, and the claimed combination may be directed to a sub-combination or a variation of the sub-combination.

[0153] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that such operations be performed in the particular order shown or in sequence, or that all of the operations shown be performed, to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0154] Thus, specific embodiments of the subject matter have been described herein. Other embodiments are within the scope of the following claims. In some cases, the actions set forth in the claims can be performed in a different order and still achieve the desired results. Additionally, the processes depicted in the accompanying drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing may be advantageous.

[0155] As those skilled in the art will recognize, the innovative concepts described herein may be modified and varied over a wide range of applications.Thus, the scope of the claimed subject matter should not be limited to any specific exemplary techniques discussed above, but rather is defined by the appended claims.

Claims

1. A method comprising: receiving a reference signal; generating a channel estimate based on the reference signal; determining a channel estimation error metric for the channel estimation; Receive transmissions; calculating a log-likelihood ratio for each of a plurality of bit positions of the transmission based on the channel estimation error metric; as well as decoding the transmission based on the log-likelihood ratio, Therein, the calculation of the log-likelihood ratio includes calculating a corrected log-likelihood ratio based at least on an uncorrected log-likelihood ratio.

2. The method according to claim 1, wherein: The corrected log-likelihood ratio is also equal to the uncorrected log-likelihood ratio further adjusted by one or more correction maps.

3. The method according to claim 2, wherein: A first of the correction maps is based on a multiplication correction map.

4. The method according to claim 3, wherein: The first of the correction maps comprises multiplication by an integer power of 2.

5. The method according to claim 4, further comprising: The log-likelihood ratio is stored in a fixed point representation having a binary point location calculated based on a first term and a second term, the second term being the integer.

6. The method according to claim 3, wherein: The first correction map is based on a rank of the transmission.

7. The method according to claim 6, wherein: The first correction mapping is based on the channel estimation error metric.

8. The method according to claim 7, wherein: The channel estimation error metric is based on a ratio of channel estimation error power to noise power.

9. The method according to claim 8, wherein: The determination of the channel estimation error metric comprises determining the channel estimation error power based on time domain interpolated weights.

10. The method according to claim 9, wherein: The determining of the channel estimation error metric includes determining the channel estimation error power further based on a correlation time of a channel response of a channel corresponding to the channel estimation error.

11. A system comprising: one or more processors; and A memory storing instructions that, when executed by the one or more processors, cause the following operations to be performed: receiving a reference signal; generating a channel estimate based on the reference signal; determining a channel estimation error metric for the channel estimation; Receive transmissions; calculating a log-likelihood ratio for each of a plurality of bit positions of the transmission based on the channel estimation error metric; as well as decoding the transmission based on the log-likelihood ratio, The calculation of the log-likelihood ratio includes calculating a corrected log-likelihood ratio based at least on an uncorrected log-likelihood ratio.

12. The system according to claim 11, wherein: The corrected log-likelihood ratio is also equal to the uncorrected log-likelihood ratio further adjusted by one or more correction maps.

13. The system according to claim 12, wherein: A first of the correction maps is based on a multiplication correction map.

14. The system of claim 13, wherein: The first of the correction maps comprises multiplication by an integer power of 2; and The instructions, when executed by the one or more processors, further cause the following operations: storing the log-likelihood ratio in a fixed point representation having a binary point position calculated based on a first term and a second term, the second term being the integer.

15. The system of claim 13, wherein: The first correction map is based on a rank of the transmission.

16. The system of claim 15, wherein: The first correction mapping is based on the channel estimation error metric.

17. The system of claim 16, wherein: The channel estimation error metric is based on a ratio of channel estimation error power to noise power.

18. The system of claim 17, wherein: The determination of the channel estimation error metric comprises determining the channel estimation error power based on time domain interpolated weights.

19. The system of claim 18, wherein: The determining of the channel estimation error metric includes determining the channel estimation error power further based on a correlation time of a channel response of a channel corresponding to the channel estimation error.

20. A system comprising: Parts for processing; and A memory storing instructions that, when executed by the means for processing, cause the following operations to be performed: receiving a reference signal; generating a channel estimate based on the reference signal; determining a channel estimation error metric for the channel estimation; Receive transmissions; calculating a log-likelihood ratio for each of a plurality of bit positions of the transmission based on the channel estimation error metric; as well as decoding the transmission based on the log-likelihood ratio, The calculation of the log-likelihood ratio includes calculating a corrected log-likelihood ratio based at least on an uncorrected log-likelihood ratio.

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