MIMO Detection Apparatus and Method with Continuous Transmission Layer Detection and Soft Interference Cancellation

Abstract

A MIMO detection device is disclosed. The device can perform a first tree search based at least in part on a first triangular R matrix and a first received signal to obtain a first set of candidate symbol paths associated with a first transmission layer. The device can generate a first set of LLRs associated with the first transmission layer. The device can generate a first reconstructed symbol associated with the first transmission layer based at least in part on the first set of LLRs. The device can remove the last row and the last column from the first triangular R matrix to obtain a second triangular R matrix associated with a second transmission layer. The device can subtract the first reconstructed symbol from the first received signal to obtain a second estimated signal associated with the second transmission layer.

Description

[0001] Cross - reference to related applications

[0002] This application claims the priority of U.S. Provisional Patent Application 62 / 991,360, filed on March 18, 2020, entitled "MIMO Detection with Continuous Transmission Layer Detection and Soft Cancellation", the entire content of which is incorporated herein by reference. Background of the Invention

[0003] Embodiments of the present disclosure relate to wireless communication devices and methods.

[0004] Wireless communication systems are widely deployed to provide various telecommunication services, such as telephony, video, data, messaging, and broadcasting. The development of wireless communication, especially cellular communication systems, such as the 4th generation (4G) Long - Term Evolution (LTE) and the 5th generation (5G) New Radio (NR), has made higher - speed data services crucial. Multiple - Input Multiple - Output (MIMO) communication has received attention because MIMO communication uses spatial multiplexing methods, which can perform multipath propagation by transmitting multiple signal streams (also referred to as "transmission layers") using multiple transmit and receive antennas to meet high - speed data requirements. Summary of the Invention

[0005] Embodiments of MIMO detection devices and methods with continuous transmission layer detection and soft interference cancellation are disclosed herein.

[0006] According to one aspect of the present disclosure, a wireless communication device is disclosed, which may include a memory and at least one processor. The at least one processor is coupled to the memory and is configured to perform operations associated with MIMO detection. For example, in some embodiments, the at least one processor may be configured to perform a first tree search at least partially based on a first triangular R - matrix and a first received signal to obtain a first set of candidate symbol paths associated with a first transmission layer. In some other embodiments, the at least one processor may further be configured to generate a first set of log - likelihood ratios (LLRs) associated with the first transmission layer at least partially based on the first set of candidate symbol paths. In some other embodiments, the at least one processor may further be configured to generate a first reconstructed symbol associated with the first transmission layer at least partially based on the first set of LLRs. In some other embodiments, the at least one processor may further be configured to remove the last row and the last column from the first triangular R - matrix to obtain a second triangular R - matrix associated with a second transmission layer. In some other embodiments, the at least one processor may further be configured to subtract the first reconstructed symbol from the first received signal to obtain a second signal associated with the second transmission layer.

[0007] According to another aspect of the present disclosure, a wireless communication method is disclosed. In some embodiments, the method may include performing a first tree search at least partially based on a first triangular R matrix and a first received signal to obtain a first set of candidate symbol paths associated with a first transmission layer. In some embodiments, the method may include generating a first set of LLRs associated with the first transmission layer at least partially based on the first set of candidate symbol paths. In some embodiments, the method may include generating a first reconstructed symbol associated with the first transmission layer at least partially based on the first set of LLRs. In some embodiments, the method may include removing the last row and the last column of the first triangular R matrix to obtain a second triangular R matrix associated with a second transmission layer. In some embodiments, the method may include subtracting the first reconstructed symbol from the first received signal to obtain a second signal associated with the second transmission layer.

[0008] According to yet another aspect of the present disclosure, a baseband chip for wireless communication is disclosed. The baseband chip may include a MIMO detection circuit. In certain embodiments, the MIMO detection circuit may be configured to perform a first tree search at least partially based on a first triangular R matrix and a first received signal to obtain a first set of candidate symbol paths associated with a first transmission layer. In certain other embodiments, the MIMO detection circuit may be configured to generate a first set of LLRs associated with the first transmission layer at least partially based on the first set of candidate symbol paths. In certain other embodiments, the MIMO detection circuit may be configured to generate a first reconstructed symbol associated with the first transmission layer at least partially based on the first set of LLRs. In certain other embodiments, the MIMO detection circuit may be configured to remove the last row and the last column of the first triangular R matrix to obtain a second triangular R matrix associated with a second transmission layer. In certain other embodiments, the MIMO detection circuit may be configured to subtract the first reconstructed symbol from the first received signal to obtain a second signal associated with the second transmission layer. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The drawings incorporated herein and forming a part of the specification illustrate embodiments of the present disclosure and, together with the description, further serve to explain the principles of the present disclosure and enable those of ordinary skill in the art to make and use the present disclosure.

[0010] Figure 1 An exemplary wireless network according to some embodiments of the present disclosure is shown.

[0011] Figure 2 An exemplary MIMO communication system according to some embodiments of the present disclosure is shown.

[0012] Figure 3 Shown according to some embodiments of the present disclosure Figure 2Detailed block diagram of the MIMO communication system in

[0013] Figure 4 Schematic diagram of an exemplary MIMO channel according to some embodiments of the present disclosure.

[0014] Figure 5 Block diagram of an exemplary MIMO detection system according to some embodiments of the present disclosure.

[0015] Figure 6A and 6B Flowchart of an exemplary method for MIMO detection according to some embodiments of the present disclosure.

[0016] Figure 7A and 7B Block diagram of an exemplary device including a host chip, a radio frequency (RF) chip, and a baseband chip according to some embodiments of the present disclosure, where the baseband chip is implemented in software and hardware respectively Figure 5 in the MIMO detection system in

[0017] Figure 8 Block diagram of an exemplary receiving device according to some embodiments of the present disclosure.

[0018] Embodiments of the present disclosure will be described with reference to the accompanying drawings. Detailed implementation manners

[0019] Although specific configurations and arrangements are discussed, it should be understood that this is done for illustrative purposes only. Those skilled in the relevant art will recognize that other configurations and arrangements can be used without departing from the spirit and scope of the present disclosure. It will be apparent to those skilled in the relevant art that the present disclosure can also be used in various other applications.

[0020] It should be noted that references to "embodiments", "one embodiment", "exemplary embodiments", "some embodiments", "certain embodiments", etc. in the specification indicate that the described embodiments may include specific features, structures, or characteristics, but not every embodiment necessarily includes that specific feature, structure, or characteristic. Moreover, these phrases do not necessarily refer to the same embodiment. Additionally, when a specific feature, structure, or characteristic is described in connection with an embodiment, implementing such feature, structure, or characteristic in connection with other embodiments will be within the knowledge of those skilled in the relevant art, whether or not explicitly described.

[0021] In general, terms may be understood, at least in part, based on their use in context. For example, the term "one or more" as used herein depends, at least in part, on context and can be used to describe any feature, structure, or characteristic in a singular sense or can be used to describe a combination of features, structures, or characteristics in a plural sense. Similarly, terms such as "a," "an," or "the" can also be understood to convey a singular usage or to convey a plural usage, at least in part, depending on context. Additionally, the term "based on" can be understood to not necessarily be intended to convey an exclusive set of factors but can allow for additional factors that are not necessarily explicitly described, again at least in part, depending on context.

[0022] Aspects of a wireless communication system will now be described with reference to various apparatuses and methods. These apparatuses and methods will be described in the following detailed description and illustrated in the accompanying drawings by various blocks, modules, units, components, circuits, steps, operations, processes, algorithms, etc. (collectively referred to as "elements"). These elements can be implemented using electronic hardware, firmware, computer software, or any combination thereof. Whether these elements are implemented as hardware, firmware, or software depends on the particular application and design constraints imposed on the overall system.

[0023] The techniques described herein can be used in various wireless communication networks, such as code division multiple access (CDMA) systems, time division multiple access (TDMA) systems, frequency division multiple access (FDMA) systems, orthogonal frequency division multiple access (OFDMA) systems, single carrier frequency division multiple access (SC-FDMA) systems, and other networks, including but not limited to 4G, LTE, and 5G cellular networks. The terms "network" and "system" are often used interchangeably. The techniques described herein can be used in the above-mentioned wireless networks as well as other wireless networks.

[0024] Multiple-input multiple-output (MIMO) technology forms the basis of various wireless communication systems, such as 3G, LTE, and NR, to name just a few. In a MIMO system, both the transmitter and the receiver are equipped with multiple antennas. Multiple data streams can be simultaneously transmitted to the receiver through spatial multiplexing. Each data stream can be associated with a transmission layer. Spatial multiplexing provides high spectral efficiency but at the cost of increased signal processing complexity, most notably the MIMO detector in the baseband chip, which can be used to recover the data streams from the channel and noise / interference.

[0025] For a MIMO system with N transmission layers and M receiver antennas, the mathematical system model can be described using Equation (1):

[0026] y = Hx + n (1), where, is the received signal vector; is the transmitted quadrature amplitude modulation (QAM) symbol vector, where, is a set of possible QAM symbols for a specific modulation order m (e.g., for Quadrature Phase Shift Keying (QPSK), m = 2; for 16QAM, m = 4; for 64QAM, m = 6; for 256QAM, m = 8; for 1024QAM, m = 10, etc.); is a complex channel matrix; is a Gaussian white noise vector. In some embodiments, each transmission layer may have the same modulation order. However, in some other embodiments, different transmission layers may have different modulation orders. For example, layer 0 and layer 1 may use 16QAM, while layer 2 and layer 3 may use 64QAM. The operations described herein may be performed for any of the embodiments.

[0027] After performing noise whitening on the received signal, n may be a complex Gaussian noise vector with unit variance and may be considered uncorrelated among vector elements. For example, the noise covariance matrix Φ n = I M where I M represents an M-dimensional identity matrix. Given the estimated channel matrix and the received signal vector y, the baseband chip may be configured to perform MIMO detection to estimate x.

[0028] Among various types of MIMO detection techniques, Maximum Likelihood Detection (MLD) provides the best theoretical error performance. Using the above system model, assuming white noise Φ n = I N , the Maximum Likelihood (ML) solution is equivalent to solving the least squares problem of Equation (2):

[0029]

[0030] where, is the ML of the estimated transmitted QAM symbol vector.

[0031] In some embodiments, the least squares problem may be solved by QR decomposition techniques. For example, by performing QR decomposition on where, is an orthogonal matrix and is an upper triangular matrix. It can be assumed, without loss of generality, that the number of receiver antennas is greater than or equal to the number of transmission layers. For example, M ≥ N. Under this assumption, the lower M - N rows of the upper triangular matrix R are always zero, so only the upper N×N square matrix and the upper rows of the triangular matrix are meaningful. By processing the received vector y with Q H e.g., which is a sufficient statistic of y, the system model can be transformed into the following as shown in Equation (3):

[0032]

[0033] Among them, is still an uncorrelated white Gaussian noise vector, and Therefore, the problem of finding the ML solution can be equivalent to solving Equation (4):

[0034]

[0035] As an example and not a limitation, for a system with four transmission layers and four receiver antennas (e.g., a 4x4 system), Equation (3) can be expressed as:

[0036]

[0037] For a hard-output detection scheme, such as Vertical Bell Laboratories Layered Space-Time Code (V-BLAST), detection starts from layer 3 by solving Equation (5):

[0038]

[0039] Then, layer 2 can be detected by eliminating the detection result of layer 3, as shown in Equation (6) below:

[0040]

[0041] The successive interference cancellation / back substitution process performed on layer 2 can be iteratively performed for layers 1 and 0. However, such techniques are affected by error propagation. That is, the detection error of layer k has a negative impact on the detection of layers k - 1,..., layer 0. Therefore, the transmission layers can be sorted so that stronger layers are detected first to minimize the error propagation problem.

[0042] On the other hand, the soft-output detection scheme based on ML detection essentially searches for the solution of Equation (4) in the vector space of all It can be shown that the problem in Equation (4) can be transformed into an equivalent QAM symbol tree search problem, where the root-to-leaf tree path represents the transmitted QAM symbol vector based at least in part on the upper triangular matrix R. Such a QAM symbol vector has a length of N and can include QAM symbols from these N transmission layers. The search result of one iteration of the tree search can be a path metric representing one or more QAM symbols.

[0043] The soft output of the QAM symbol vector (e.g., log-likelihood ratio (LLR)) can be calculated based on one or more path metrics that lead to tree search. The performance improvement of the soft output system is achieved at the cost of higher computational complexity associated with tree search. As the modulation order m and / or the number of transmission layers N increase, the size of the tree and thus the computational complexity of the ML detection algorithm increase exponentially. Therefore, even for traditional near-MLD schemes that reduce computational complexity by restricting the number of paths in tree search, the computational resources for performing such calculations are still excessive, especially for higher-order QAMs such as 16QAM, 64QAM, 256QAM, 1024QAM, etc.

[0044] Therefore, there is an unmet need for MIMO detection techniques that provide performance improvements associated with tree search without introducing the significant computational complexity required by traditional near-MLD scheme techniques.

[0045] Compared with traditional MIMO detection schemes, the exemplary MIMO detection scheme of the present disclosure combines soft output tree search and successive interference cancellation (SIC) to improve performance and reduce complexity. For example, the exemplary baseband chip of the present disclosure uses soft output LLR as the detection output for each transmission layer. Then, the soft output is also used to reconstruct the soft transmitted QAM symbols for the detected transmission layer in a probabilistic manner. That is, the reconstructed symbols may not be part of the transmitted constellation but the statistical average of the possible transmitted QAM symbols based on the received signal vector y. Then the reconstructed and / or remapped symbols are subtracted from the received signal for the remaining transmission layers to be detected.

[0046] Figure 1 An exemplary wireless network 100 according to some embodiments of the present disclosure is shown, which can implement certain aspects of the present disclosure. As Figure 1 shown, the wireless network 100 can include a network of nodes such as user equipment (UE) 102, access node 104, and core network element 106. The user equipment 102 can be any terminal device, such as a mobile phone, desktop computer, laptop computer, tablet device, in-vehicle computer, gaming console, printer, positioning device, wearable electronic device, smart sensor, or any other device capable of receiving, processing, and sending information, such as any member of a vehicle-to-everything (V2X) network, a cluster network, a smart grid node, or an Internet of Things (IoT) node. It should be understood that the user equipment 102 is shown as a mobile phone by way of illustration and not limitation.

[0047] The access node 104 can be a device that communicates with the user equipment 102, such as a wireless access point, a base station (BS), a Node B, an evolved Node B (eNodeB or eNB), a next-generation Node B (gNodeB or gNB), a cluster master node, etc. The access node 104 can have a wired connection to the user equipment 102, a wireless connection to the user equipment 102, or any combination thereof. The access node 104 can be connected to the user equipment 102 through multiple connections, and the user equipment 102 can be connected to other access nodes in addition to the access node 104. The access node 104 can also be connected to other user equipment. It should be understood that the access node 104 is shown as a radio tower by way of illustration and not limitation.

[0048] The core network element 106 can serve the access node 104 and the user equipment 102 to provide core network services. Examples of the core network element 106 can include a home subscriber server (HSS), a mobility management entity (MME), a serving gateway (SGW), or a packet data network gateway (PGW). These are examples of core network elements of an evolved packet core (EPC) system, which is the core network of an LTE system. Other core network elements can be used in LTE and other communication systems. In some embodiments, the core network element 106 includes an access and mobility management function (AMF) device, a session management function (SMF) device, or a user plane function (UPF) device of the core network of an NR system. It can be understood that the core network element 106 is shown as a set of rack-mounted servers by way of illustration and not limitation.

[0049] The core network element 106 can be connected to a large network such as the Internet 108 or other Internet Protocol (IP) networks to transmit packet data over any distance. Thus, data from the user equipment 102 can be transmitted to other user equipment connected to other access points, such as a computer 110 connected to the Internet 108 using, for example, a wired connection or a wireless connection, or a tablet device 112 wirelessly connected to the Internet 108 through a router 114. Therefore, the computer 110 and the tablet device 112 provide additional examples of possible user equipment, and the router 114 provides another example of a possible access node.

[0050] A general example of a rack-mounted server is provided as a schematic of the core network element 106. However, there may be multiple components in the core network, including database servers, such as database 116, and security and authentication servers, such as authentication server 118. For example, database 116 can manage data related to user subscriptions to network services. A home location register (HLR) is an example of a standardized database of subscriber information in a cellular network. Similarly, authentication server 118 can handle the authentication of users, sessions, etc. In an NR system, an authentication server function (AUSF) device can be a specific entity that performs user equipment authentication. In some embodiments, a single server rack can handle multiple such functions, such that the connections between the core network element 106, authentication server 118, and database 116 can be local connections within a single rack.

[0051] As described in detail below, in some embodiments, MIMO communication can be established between any suitable nodes in the wireless network 100, such as between the user equipment 102 and the access node 104, for sending and receiving data over a MIMO channel. The transmitting node can establish a MIMO channel with the receiving node (e.g., establish a multipath communication link between multiple transmitting antennas and multiple receiving antennas), and transmit coded symbols in multiple signal streams over the MIMO channel. The receiving node can receive multiple transmitted signal streams over the MIMO channel, and can detect the symbol vector using a baseband chip that implements the MIMO detection scheme disclosed herein based on successive transmission layer detection and soft interference cancellation.

[0052] Figure 1 Each node in the wireless network 100 suitable for receiving data can be considered a receiving device in MIMO communication. In Figure 8 the description of the receiving device 800 in Figure 1 more details about possible implementations of the receiving device are provided by way of example. The receiving device 800 can be configured to Figure 1 be the user equipment 102, access node 104, or core network element 106 in Figure 8 . Similarly, the receiving device 800 can also be configured to

[0053] The transceiver 806 may include any suitable device for transmitting and / or receiving data. The receiving device 800 may include one or more transceivers, although only one transceiver 806 is shown for simplicity of illustration. The antenna 808 is shown as a possible communication mechanism for the receiving device 800. Multiple antennas and / or antenna arrays may be used for MIMO communication. Additionally, examples of the receiving device 800 may communicate using wired technologies instead of wireless technologies (or in addition to wireless technologies). For example, the access node 104 may communicate wirelessly with the user equipment 102 and may communicate with the core network element 106 via a wired connection (e.g., via an optical fiber cable or coaxial cable). Other communication hardware, such as a network interface card (NIC), may also be included.

[0054] As Figure 8 shown, the receiving device 800 may include a processor 802. Although only one processor is shown, it is understood that multiple processors may be included. The processor 802 may include a microprocessor, a microcontroller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a programmable logic device (PLD), a state machine, gated logic, discrete hardware circuits, and other suitable hardware configured to perform the various functions described throughout this disclosure. The processor 802 may be a hardware device having one or more processing cores. The processor 802 may execute software. Software should be construed broadly as instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, processes, functions, etc., regardless of whether it is referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. Software may include computer instructions written in an interpreted language, a compiled language, or machine code. Other techniques for instructing hardware are also permitted under the broad category of software.

[0055] As Figure 8As shown, the receiving device 800 may further include a memory 804. Although only one memory is shown, it should be understood that multiple memories may be included. The memory 804 may broadly include memory and storage. For example, the memory 804 may include random access memory (RAM), read-only memory (ROM), static RAM (SRAM), dynamic RAM (DRAM), ferroelectric RAM (FRAM), electrically erasable programmable ROM (EEPROM), CD-ROM or other optical disc storage, hard disk drive (HDD), such as magnetic disk storage or other magnetic storage devices, flash drive, solid state drive (SSD), or any other medium that can be used to carry or store the required program code in the form of instructions that can be accessed and executed by the processor 802. Broadly speaking, the memory 804 may be implemented by any computer-readable medium, such as a non-transitory computer-readable medium.

[0056] The processor 802, the memory 804, and the transceiver 806 may be implemented in various forms in the receiving device 800 for performing MIMO communication functions. In some embodiments, the processor 802, the memory 804, and the transceiver 806 of the receiving device 800 are implemented (e.g., integrated) on one or more system-on-chips (SoCs). In one example, the processor 802 and the memory 804 may be integrated on an application processor (AP) SoC (sometimes referred to as a "host", herein referred to as a "host chip") that processes applications in an operating system environment, including generating initial data to be transmitted. In another example, the processor 802 and the memory 804 may be integrated on a baseband processor (BP) SoC (sometimes referred to as a modem, herein referred to as a "baseband chip"), which converts, for example, initial data from the host chip into signals that can be used to modulate a transmission carrier frequency, and vice versa, and it may run a real-time operating system (RTOS). In yet another example, the processor 802 and the transceiver 806 (and in some cases the memory 804) may be integrated on a radio frequency (RF) SoC (sometimes referred to as a transceiver, herein referred to as an "RF chip") that transmits and receives RF signals using the antenna 808. It should be understood that in some examples, some or all of the host chip, the baseband chip, and the RF chip may be integrated into a single SoC. For example, the baseband chip and the RF chip may be integrated into a single SoC that manages all radio functions for cellular communication.

[0057] Various aspects of the present disclosure related to MIMO detection can be implemented as software and / or firmware elements executed by a general-purpose processor in a baseband chip (e.g., a baseband processor). It should be understood that in some examples, one or more software and / or firmware elements can be replaced by dedicated hardware components in the baseband chip, including integrated circuits (ICs), such as ASICs. Mapped to the wireless communication (e.g., 4G, LTE, 5G, etc.) layer architecture, embodiments of the present disclosure can be at layer 1, e.g., the physical (PHY) layer.

[0058] Figure 2 FIG. 200 shows an exemplary MIMO communication system according to some embodiments of the present disclosure. The MIMO communication system 200 can be used between suitable nodes in the wireless network 100. As Figure 2 shown, the MIMO communication system 200 can include a transmitting device 210, a receiving device 220, and a MIMO channel 230 (e.g., a multipath communication link between the transmitting antenna and the receiving antenna). For example, each of the transmitting device 210 and the receiving device 220 can be Figure 1 an example of the user equipment 102, the access node 104, or the core network element 106 in the wireless network 100 as described above. The MIMO communication system 200 can be used to increase the data transmission rate between the transmitting device 210 and the receiving terminal device. Both the transmitting device 210 and the receiving device 220 can include a processor, a memory, and a transceiver, which can be examples of the processor 802, the memory 804, and the transceiver 806 described in detail above with respect to Figure 8 this.

[0059] As Figure 2 shown, the transmitting device 210 can process the original data (e.g., process the input bits through various functional stages of encoding and interleaving, modulation, symbol mapping, and layer mapping and precoding), and can transmit the processed data (e.g., encoded symbols) in multiple signal streams through the MIMO channel 230 to the receiving device 220. The receiving device 220 can receive the multiple transmitted signal streams and detect the original data (e.g., decoded bits) through reverse processes, such as de-precoding, MIMO detection, demapping, and channel decoding.

[0060] As an example of a MIMO communication system implementing the above MIMO detection scheme, Figure 3 FIG. 200 shows a detailed block diagram of a MIMO communication system according to some embodiments of the present disclosure. As Figure 3 shown, the transmitting device 210 can include a channel coding and interleaving module 312, a modulation module 314, a symbol mapping module 316, and a layer mapping and precoding module 318 for processing the original data to be transmitted.

[0061] For example, the channel coding and interleaving module 312 may be configured to add extra bits (i.e., redundant bits) to the original data (e.g., input bits) for error detection. The modulation module 314 (e.g., QAM modulation module) may be configured to modulate and combine different signals (e.g., different bit streams) by modulating two carriers (e.g., 90° out of phase with each other) using an amplitude shift keying (ASK) digital modulation scheme or an amplitude modulation (AM) analog modulation scheme, and add the two carriers together. The symbol mapping module 316 may be configured to map the combined signal to coded symbols. The layer mapping and precoding module 318 may be configured to map the coded symbols onto different signal streams / layers. For example, the layer mapping and precoding module 318 may perform space-time and / or spatial multiplexing precoding, where the coded symbols on each signal stream / layer are precoded into symbol vectors (e.g., QAM symbol vectors) and transmitted through all the transmit antennas.

[0062] The QAM symbol vector may be transmitted to the receive antennas via the MIMO channel 230 according to Equation (1) above.

[0063] As an example of the MIMO channel, Figure 4 FIG. shows a schematic diagram of an exemplary MIMO channel 230 according to some embodiments of the present disclosure. As shown. As Figure 4 shown, the transmitting device 210 may include n transmit antennas (e.g., labeled Tx1, Tx2,..., Txn respectively) for transmitting n transmit signal streams, and the receiving device 220 may include m receive antennas (e.g., labeled Rx1, Rx2,..., Rxm respectively) for receiving the transmit signal streams. The complex channel matrix H may include n columns (e.g., corresponding to the conditions of n transmit signal streams) and m rows (e.g., corresponding to the conditions of m receive antennas).

[0064] Return Figure 3 , the receiving device 220 may include a despreading module 322, a demapping module 326, and a channel decoding module 328 for reversing the transmitter processing operations (e.g., space-time despreading, demapping, demodulation, decoding, etc.), and may determine the original data transmitted by the transmitting device 210 to generate decoded bits. The receiving device 220 may further include an MIMO detection module 324 for detecting the transmitted QAM symbol vector x based on the estimated matrix of the channel matrix H and the received symbol vector y.

[0065] In some embodiments, the MIMO detection module 324 may permute the transmitted signal streams based on a metric of the signal streams and perform MIMO detection based on the permuted signal streams. After detection, the MIMO detection module 324 may further de-permute the signal streams back to the original order for further processing. For example, the channel decoding module 328 may include a log-likelihood ratio (LLR) calculation unit for calculating the LLR based on the detected signal streams in the original order (e.g., the restored original order), and may feed the LLR calculation result as an input to a channel decoder such as a Turbo decoder or a low-density parity-check (LDPC) decoder for decoding.

[0066] As Figure 3 an example of the MIMO detection module 324 in Figure 5 FIG. 5 shows a schematic diagram of an exemplary MIMO detection system 500 according to some embodiments of the present disclosure. As Figure 5 shown, the MIMO detection system 500 may be configured to perform successive layer detection and interference cancellation. For example, the MIMO detection system 500 may include a QR decomposition module 502, one or more R matrix update / interference cancellation modules 504a, 504b, 504c, one or more tree search and LLR generation modules 506a, 506b, 506c, one or more QAM symbol reconstruction modules 508a, 508b, and an LLR buffer 510. In addition, the MIMO detection system 500 may include modules dedicated to each of the N transmission layers. The N transmission layers may be arranged in ascending order such that layer 0 has the lowest received signal strength and layer N−1 has the highest received signal strength. Although not shown, there may be embodiments in which the MIMO detection system 500 includes a single R matrix update / interference cancellation module, a single tree search and LLR generation module, and a QAM symbol reconstruction module. In such embodiments, the modules may be time-division multiplexed to process different transmission layers.

[0067] For an M×B, M≥N system with a modulation order of m, the following operations in conjunction with Figure 5 describe the process of an exemplary MIMO detection technique. The N main steps process the N layers. In each main step, there are generally 3 sub-steps, except that sub-step 1 is omitted in main step 1 and sub-step 3 is omitted in main step N. The first sub-steps of steps 2 and N perform interference cancellation on the detected layers and prepare the input for the tree search algorithm in sub-step 2. In sub-step 2, a reduced-complexity tree search algorithm generates the LLR, which is sent to the output and used for soft interference reconstruction in sub-step 3.

[0068] More specifically, first, the MIMO detection system 500 can receive a data stream associated with a channel. The data stream can include, for example, layer N-1, layer N-2, ... layer 0. The data stream (e.g., the received signal vector y) can be associated with a complex channel matrix H. The MIMO detection system 500 can generate an estimated channel matrix based at least in part on, for example, dedicated pilot signals transmitted by a transmitter. Estimated channel matrix And the estimated channel matrix and the received signal vector y can be input into the QR decomposition module 502. The QR decomposition module 502 can perform a first QR decomposition on the estimated channel matrix To generate a triangular R matrix, as shown in Equation (7) below:

[0069]

[0070] In addition, the QR decomposition module 502 can perform a second QR decomposition on the received signal vector y to produce an estimated signal As shown in Equation (8) below. In some embodiments, the first and second QR decompositions can be part of the same QR decomposition operation. For example, the QR decomposition module 502 can perform a QR decomposition that generates a triangular R matrix (e.g., the first QR decomposition) and generates an estimated signal (e.g., the second QR decomposition).

[0071]

[0072] The transmission layer N-1 has the highest received signal strength and is thus the initial layer detected by the MIMO detection system 500. As described above, the first R matrix update / interference cancellation module 504a may not perform matrix subtraction and / or interference cancellation. Instead, the first R matrix update / interference cancellation module 504a sets R = R1 and R1 and Both can be input into the first tree search and LLR generation module 506a.

[0073] The first tree search and LLR generation module 506a can perform a first tree search based at least in part on R1 (the first triangular R matrix) and (the first estimated signal) to obtain a first set of candidate symbol paths associated with layer N-1 (the first transmission layer). The tree search for layer N–1 is performed for all N layers. The tree search will produce K candidate symbol paths, which are used to generate LLRl (soft output values) for layer N–1: There can be at most 2 m Candidate symbol paths, where m is the modulation order.

[0074] The complexity-reducing tree search operation used in sub-step 2 of each main step performs a limited search on the simplified QAM symbol tree. For step k, layer N-k is being processed. The simplified QAM symbol tree includes layers N-k to 0, corresponding to the simplified input R k matrix. This operation produces a set of candidate paths, which are then used for LLR calculation for layer N-k. The operation used here can be any operation with a fixed / deterministic complexity. An ideal common property of the operation is that the search range should be large enough for layer N-k (which is the first layer under the root of the simplified QAM symbol tree) in terms of the number of QAM constellation points explored. This is important for generating LLRs with at least threshold accuracy. Other details associated with generating LLRs are elaborated below.

[0075] For example, for the bit b of layer n ∈ {0, 1, …, N-1} u,n the posterior LLR for i = 0, 1, …, m-1, given the received vector is defined as Equation (9):

[0076]

[0077] where is the conditional probability that the transmitted bit b is +1 given the received vector i,n

[0078] The entire symbol path for all N layers can be defined as Equation (10):

[0079]

[0080] where is the set of candidate paths ( subset) whose bit ib of layer n i,n = +1, regardless of the bit values of other bits of other transmission layers, and is the probability of the vector given the received vector

[0081] Using Bayes' criterion, can be defined according to Equation (11):

[0082]

[0083] where is the uncorrelated Gaussian white noise vector as described above. Assuming Pr(x) is constant, for example, all symbols are transmitted with equal probability, and considering that the ratio in Equation (9) may not depend on Equation (9) can be rewritten as Equation (12): ​​

[0084]

[0085] For tree search with reduced complexity, since the search range is limited, or is possible. Therefore, it is impossible to calculate the LLR according to (9). Therefore, the tree search algorithm used here must search a large enough subset of and such that there are enough vectors in

[0086] to generate LLRs with precision meeting the minimum threshold. For a smaller modulation order, e.g., m ≤ 64, the tree search algorithm can cover all the constellation points of layer N–k only, where, for a larger modulation order, e.g., 256QAM, 1024QAM, etc., the search range can be narrowed down to a larger subset of the constellation to control the overall complexity. i > 0 when

[0087]

[0088] However, the problem of or still exists. The reduced-complexity tree search performed by each tree search and LLR generation module 506a, 506b, 506c can be applied to both equations (12) and (13) or any other approximation of equation (9).

[0089] Although the tree search is performed in each main step (e.g., main step 1, main step 2, main step 3, etc.), the depth of the tree decreases with each main step, so the overall computational complexity is reduced compared to traditional techniques.

[0090] Still referring to main step 1, the first tree search and LLR generation module 506a can output the first set of LLRs to the first QAM symbol reconstruction module 508a. In addition, the first tree search and LLR generation module 506a can output the first set of LLRs to the LLR buffer 510.

[0091] The first QAM symbol reconstruction module 508a can generate a first reconstructed symbol associated with layer N-1 (the first transmission layer) at least partially based on the first set of LLRs. For example, the reconstructed symbol can be defined according to equation (14):

[0092]

[0093] wherein, represents that the given LLR value is the probability of the transmitted symbol x.

[0094] For example, the LLR value represents the probability that, given a received vector, the bit is +1 or -1. From Equation (9), given the value of l b,n and considering the probabilities of the LLR values of the bits being +1 or -1 can be defined according to Equations (15) and (16) respectively:

[0095] and

[0096]

[0097] Therefore, the first QAM symbol reconstruction module 508a can calculate the posterior probability of the QAM symbol at layer N-1 given the LLR according to how the transmitted bits are mapped to the QAM constellation symbol points at the transmitter. The rule for mapping the bits to the QAM symbols can be known to both the transmitter and the receiver. Assume the bits B0, B1, …, B m-1 , wherein, the bit B i = ±1, i = 0, 1, …, m-1 are mapped to the QAM symbol bit x, then conversely, the first QAM reconstruction module 508a can represent the bit corresponding to the symbol x as Then, given the LLR value, the posterior probability of x can be defined according to Equation (17):

[0098]

[0099] And the soft reconstruction of the transmitted symbol can be generated according to Equation (18):

[0100]

[0101] Moving to layer N-2, the information associated with the soft reconstruction of the transmitted symbol generated according to Equation (18) can be input into the second R matrix update and interference cancellation module 504b.

[0102] The second R matrix update and interference cancellation module 504b can remove the last row and the last column of R1 to generate R2 (the second triangular R matrix), as shown in Equation (19) below:

[0103]

[0104] In addition, the second R matrix update and interference cancellation module 504b can subtract the soft reconstruction from the received values from other layers to obtain As shown in Equation (20) below:

[0105]

[0106] The second tree search and LLR generation module 506b can use R2 and perform a reduced-complexity tree search. The second tree search and LLR generation module 506b can perform the second tree search using the same or similar operations as described above in connection with the first tree search and LLR generation module 506a. For the sake of brevity, these operations are not repeated here. The second tree search will produce K candidate symbol paths, which are used to generate soft values, such as the LLRs of layer N–2: The second set of LLRs generated by the second tree search and LLR generation module 506b can be output to the LLR buffer 510 and the second QAM symbol reconstruction module 508b. The information associated with the second set of candidate symbol paths can be used to obtain the second set of LLRs through the second tree search, and the information associated with the second set of LLRs can be input into the second QAM symbol reconstruction module 508b.

[0107] Using the second set of LLRs, the second QAM symbol reconstruction module 508b can generate the second reconstructed symbols of layer N-2 according to Equation (21):

[0108]

[0109] The operations described above with respect to main step 1 and main step 2 can be repeated for the remaining layers until layer 0. When calculating the LLR set of layer 0, the operation terminates. Since layer 0 is the last layer, the soft reconstruction step can be omitted because the reconstructed symbols are used for interference cancellation in subsequent layers.

[0110] Note that for the general step k-1, R k-1 can be obtained by removing the last column and the last row of k . However, the updated received vector is recalculated from according to Equation (22):

[0111]

[0112] As described above in connection with Figure 5 The exemplary MIMO detection scheme described combines soft output tree search and SIC, and using this scheme, higher performance can be achieved with reduced complexity compared to traditional MIMO detection schemes.

[0113] Figure 6A and 6BA flowchart of an exemplary method 600 for MIMO detection according to some embodiments of the present disclosure is shown. Examples of apparatuses that can perform the operations of method 600 include, for example Figure 5 the MIMO detection system 500 depicted in Figure 7A the baseband chip 704A depicted in Figure 7B the baseband chip 704B depicted in, or any other suitable apparatus disclosed herein. It can be understood that the operations shown in method 600 are not exhaustive, and other operations can be performed before, after, or between any of the shown operations. Additionally, some operations can be performed simultaneously, or in a different order than Figure 6A and Figure 6B shown.

[0114] Referring to Figure 6A , at 602, the baseband chip can receive a data stream associated with a channel. In certain aspects, the channel can include multiple transmission layers. In certain other aspects, the multiple transmission layers can include a first transmission layer associated with a first constellation point and a second transmission layer associated with a second constellation point. For example, referring to Figure 5 , first, the MIMO detection system 500 can receive a data stream associated with a channel. The data stream can include, for example, layer N - 1, layer N - 2,... layer 0. The data stream (e.g., the received signal vector y) can be associated with a complex channel matrix H.

[0115] At 604, the baseband chip can generate an estimated channel matrix based at least in part on the data stream associated with the channel. For example, referring to Figure 5 , the MIMO detection system 500 can generate an estimated channel matrix based at least in part on the received data stream The estimated channel matrix and the received signal vector y can be input into the QR decomposition module 502.

[0116] At 606, the baseband chip can perform a first QR decomposition on the estimated channel matrix to obtain a first triangular R matrix. For example, referring to Figure 5 , the QR decomposition module 502 can perform a first QR decomposition of the estimated channel matrix to generate a triangular R matrix, as shown in equation (7) above. The first R matrix update / interference cancellation module 504a can not perform matrix subtraction and / or interference cancellation. Instead, the first R matrix update / interference cancellation 504a sets R = R1 and R1 and both can be input into the first tree search and LLR generation module 506a.

[0117] At 608, the baseband chip can perform a second QR decomposition on the data stream to obtain a first estimated signal. For example, referring to Figure 5, the QR decomposition module 502 can perform a second QR decomposition on the received signal vector y to generate an estimated signal As shown in Equation (8) above. In some embodiments, the first and second QR decompositions can be part of the same QR decomposition operation. For example, the QR decomposition module 502 can perform a QR decomposition that generates a triangular R matrix (e.g., the first QR decomposition) and generates an estimated signal (e.g., the second QR decomposition).

[0118] At 610, the baseband chip can perform a first tree search based at least in part on the first triangular R matrix and the first estimated signal to obtain a first set of candidate symbol paths associated with the first transmission layer. For example, referring to Figure 5 , the first tree search and LLR generation module 506a can perform a first tree search based at least in part on R1 (the first triangular R matrix) and (the first estimated signal) to obtain a first set of candidate symbol paths associated with layer N-1 (the first transmission layer). The tree search for layer N-1 is performed for all N layers. The tree search will produce K candidate symbol paths, which are used to generate LLRl (soft output values) for layer N–1:

[0119] At 612, the baseband chip can generate a first set of LLRs associated with the first transmission layer based at least in part on the first set of candidate symbol paths. For example, referring to Figure 5 , the tree search will produce m candidate symbol paths, which are used to generate LLRl (soft output values) for layer N–1: The additional details thereof are as described above.

[0120] At 614, the baseband chip can generate a first reconstructed symbol associated with the first transmission layer based at least in part on the first set of LLRs. For example, referring to Figure 5 , the first QAM symbol reconstruction module 508a can generate a first reconstructed symbol associated with layer N-1 (the first transmission layer) based at least in part on the first set of LLRs. For example, the reconstructed symbol can be generated according to Equations (14)-(18).

[0121] At 616, the baseband chip can remove the last row and the last column from the first triangular R matrix to obtain a second triangular R matrix associated with the second transmission layer. For example, referring to Figure 5 , the second R matrix update and interference cancellation module 504b can remove the last row and the last column of R1 to generate R2 (the second triangular R matrix), as shown in Equation (19) above.

[0122] At 618, the baseband chip can subtract the first reconstructed symbol from the first estimated signal to obtain a second estimated signal associated with the second transmission layer. For example, referring toFigure 5 , the second R matrix update and interference cancellation module 504b can subtract from the received values from other layers the soft reconstruction of to obtain as shown in Equation (20) above.

[0123] Refer to Figure 6B , at 620, the baseband chip can perform a second tree search based at least in part on the second triangular R matrix and the second estimated signal to obtain a second set of candidate symbol paths. For example, refer to Figure 5 , the second tree search and LLR generation module 506b can use R2 and to perform a reduced-complexity tree search. The second tree search and LLR generation module 506b can perform the second tree search using the same or similar operations as described above in connection with the first tree search and LLR generation module 506a.

[0124] At 622, the baseband chip can generate a second set of LLRs associated with the second transmission layer based at least in part on the second set of candidate symbol paths. For example, refer to Figure 5 , the second tree search will result in m candidate symbol paths, which are used to generate soft values, e.g., the second set of LLRs for layer N-2:

[0125] At 624, the baseband chip can hold the first set of LLRs. For example, refer to Figure 5 , the LLR buffer 510 can hold the first set of LLRs until all transmission layers have been detected.

[0126] At 626, the baseband chip can hold the second set of LLRs. For example, refer to Figure 5 , the LLR buffer 510 can hold the second set of LLRs until all transmission layers have been detected.

[0127] At 628, the baseband chip can perform channel decoding based at least in part on the first set of LLRs and the second set of LLRs. For example, refer to Figure 3 and Figure 5 , the LLR buffer 510 can output the first and second sets of LLRs to the channel decoding module 328. The channel decoding module 328 can perform channel decoding based at least in part on the first and second sets of LLRs. In other words, the LLRs generated for each transmission layer can be used for channel decoding.

[0128] For simplicity, the exemplary MIMO detection operations have been described above in connection with Figure 6A and Figure 6B . However, those of ordinary skill in the art will readily understand Figure 6A and 6BThe MIMO detection operation is not limited to performing two iterations for two transmission layers. Instead, Figure 6A and 6B the MIMO detection operation can include iterations for each transmission layer. Thus, when there are more than two transmission layers, more than two iterations can be performed, for example, as described above in connection with Figure 5 , Figure 6A and Figure 6B .

[0129] It is contemplated that the MIMO detection system 500 for MIMO communication described above can be implemented in software or hardware. For example, Figure 7A and 7B show a block diagram of an exemplary apparatus 700 including a host chip, an RF chip, and a baseband chip according to some embodiments of the present disclosure, where the baseband chip is implemented in software and hardware respectively Figure 5 for the MIMO detection system in Figure 1 . The apparatus 700 can be an example of any suitable node of the wireless network 100 in Figure 7A and Figure 7B , such as the user equipment 102 or the access node 104. As shown in Figure 7A and Figure 7B , the apparatus 700 can include an RF chip 702, a baseband chip 704 ( Figure 7A the baseband chip 704A in Figure 7B or the baseband chip 704B in Figure 7B ), a host chip 706, and a plurality of antennas 710. In some embodiments, as described with respect to Figure 8 , the baseband chip 704 is implemented by a processor 802 and a memory 804, and the RF chip 702 is implemented by a processor 802, a memory 804, and a transceiver 806. In addition to the on-chip memory 712 (also referred to as "internal memory", e.g., as registers, buffers, or caches) on each chip 702, 704, or 706, the apparatus 700 can also include a system memory 708 (also referred to as the main memory) that can be shared by each chip 702, 704, or 706 via a main bus. Although the baseband chip 704 is shown as an independent SoC in Figure 7A and Figure 7B , it can be understood that in one example, as described above, the baseband chip 704 and the RF chip 702 can be integrated into one SoC; in another example, the baseband chip 704 and the host chip 706 can be integrated into one SoC; in yet another example, the baseband chip 704, the RF chip 702, and the host chip 706 can be integrated into one SoC.

[0130] In the uplink, the host chip 706 can generate raw data and send it to the baseband chip 704 for encoding, modulation, and mapping. The baseband chip 704 can directly access the raw data from the host chip 706 using the interface 714 or through the system memory 708, and then perform the functions of the channel coding and interleaving module 312, the modulation module 314, the symbol mapping module 316, and the layer mapping and precoding module 318, as described in detail above with respect to Figure 3 described. Then the baseband chip 704 can pass the modulated signal to the RF chip 702 through the interface 714. The transmitter (Tx) 716 of the RF chip 702 can convert the modulated signal in digital form from the baseband chip 704 into an analog signal, i.e., an RF signal, and send the RF signals in multiple signal streams to the MIMO channel through multiple antennas 710 respectively.

[0131] In the downlink, multiple antennas 710 can receive the RF signals in multiple transmitted signal streams through the MIMO channel and pass the RF signals to the receiver (Rx) 718 of the RF chip 702. The RF chip 702 can perform any suitable front-end RF functions, such as filtering, downconversion, or sample rate conversion, and convert the RF signal into a low-frequency digital signal (baseband signal) that can be processed by the baseband chip 704. In the downlink, the interface 714 of the baseband chip 704 can receive the baseband signal, e.g., multiple transmitted signal streams. The baseband chip 704 can then perform the functions of the despreading module 322, the MIMO detection module 324, the demapping module 326, and the channel decoding module 328, as described in detail above with respect to Figure 3 described. The raw data can be extracted by the baseband chip 704 from the baseband signal and passed to the host chip 706 through the interface 714 or stored in the system memory 708.

[0132] In some embodiments, the MIMO detection scheme disclosed herein (e.g., of the MIMO detection module 324 or the MIMO detection system 500) can be implemented in software by Figure 7A the baseband chip 704A therein, which has a baseband processor 720 that executes stored instructions, as shown in Figure 7A shown. The baseband processor 720 can be a general-purpose processor not dedicated to MIMO detection, such as a central processing unit or a DSP. That is, the baseband processor 720 is also responsible for any other functions of the baseband chip 704A and can be interrupted by other processes with higher priorities when performing MIMO detection. Each element in the MIMO detection system 500 can be implemented as a software module executed by the baseband processor 720 to perform the respective functions described in detail above.

[0133] In some other embodiments, the MIMO detection schemes (e.g., of MIMO detection module 324 or MIMO detection system 500) disclosed herein may be implemented in hardware by a baseband chip 704B in Figure 7B which has dedicated MIMO detection circuitry 722, as shown in Figure 7A . The MIMO detection circuitry 722 may include one or more ICs, such as an ASIC, dedicated to implementing the MIMO detection schemes disclosed herein. Each element in the MIMO detection system 500 may be implemented as circuitry to perform the respective functions described in detail above. One or more microcontrollers (not shown) in the baseband chip 704B may be used to program and / or control the operation of the MIMO detection circuitry 722. It should be understood that in some examples, the MIMO detection schemes disclosed herein may be implemented in a hybrid manner, e.g., in both hardware and software. For example, some elements in the MIMO detection system 500 may be implemented as software modules executed by the baseband processor 720, while some elements in the MIMO detection system 500 may be implemented as circuitry.

[0134] In various aspects of the present disclosure, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, these functions may be stored or encoded as instructions or code on a non-transitory computer-readable medium. Computer-readable media include computer storage media. The storage media may be any available medium that can be accessed by a receiving device such as Figure 8 the receiving device 800 in. By way of example and not limitation, such computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, HDD such as magnetic disk storage or other magnetic storage devices, flash drives, SSDs, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and that can be accessed by a processing system (such as a mobile device or a computer). As used herein, disk and optical disks include CDs, laser disks, optical disks, DVDs, and floppy disks, where disks generally reproduce data magnetically, while optical disks reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0135] According to one aspect of the present disclosure, a wireless communication device is disclosed, which may include a memory and at least one processor coupled to the memory and configured to perform operations associated with MIMO detection. For example, in some embodiments, the at least one processor may be configured to perform a first tree search based at least in part on a first triangular R matrix and a first estimated signal to obtain a first set of candidate symbol paths associated with a first transmission layer. In some other embodiments, the at least one processor may also be configured to generate a first set of log-likelihood ratios (LLRs) associated with the first transmission layer based at least in part on the first set of candidate symbol paths. In some other embodiments, the at least one processor may also be configured to generate a first reconstructed symbol associated with the first transmission layer based at least in part on the first set of LLRs. In some other embodiments, the at least one processor may also be configured to remove the last row and the last column from the first triangular R matrix to obtain a second triangular R matrix associated with a second transmission layer. In some other embodiments, the at least one processor may also be configured to subtract the first reconstructed symbol from the first estimated signal to obtain a second estimated signal associated with the second transmission layer.

[0136] In some other embodiments, the at least one processor may also be configured to receive a data stream associated with a channel. In some aspects, the channel may include multiple transmission layers. In some other aspects, the multiple transmission layers may include a first transmission layer associated with a first constellation point and a second transmission layer associated with a second constellation point. In some other embodiments, the at least one processor may be configured to generate an estimated channel matrix based at least in part on the data stream associated with the channel.

[0137] In some other embodiments, the at least one processor may also be configured to perform a first QR decomposition on the estimated channel matrix to obtain a first triangular R matrix. In some other embodiments, the at least one processor may also be configured to perform a second QR decomposition on the data stream to obtain a first estimated signal.

[0138] In some other embodiments, the at least one processor may also be configured to perform a second tree search based at least in part on the second triangular R matrix and the second estimated signal to obtain a second set of candidate symbol paths. In some other embodiments, the at least one processor may also be configured to generate a second set of LLRs associated with the second transmission layer based at least in part on the second set of candidate symbol paths.

[0139] In some embodiments, the memory may be configured to hold the first set of LLRs. In some embodiments, the memory may be configured to hold the second set of LLRs.

[0140] In some other embodiments, at least one processor may be further configured to perform channel decoding at least in part based on the first set of LLRs and the second set of LLRs.

[0141] In some aspects, the first reconstructed symbol may be a statistical average of the possible symbols transmitted in the first transmission layer.

[0142] According to another aspect of the present disclosure, a method for wireless communication is disclosed. In some embodiments, the method may include performing a first tree search at least in part based on a first triangular R matrix and a first estimated signal to obtain a first set of candidate symbol paths associated with the first transmission layer. In some embodiments, the method may include generating a first set of LLRs associated with the first transmission layer at least in part based on the first set of candidate symbol paths. In some embodiments, the method may include generating a first reconstructed symbol associated with the first transmission layer at least in part based on the first set of LLRs. In some embodiments, the method may include removing the last row and the last column from the first triangular R matrix to obtain a second triangular R matrix associated with the second transmission layer. In some embodiments, the method may include subtracting the first reconstructed symbol from the first estimated signal to obtain a second estimated signal associated with the second transmission layer.

[0143] In some other embodiments, the method may further include receiving a data stream associated with the channel. In some aspects, the channel may include multiple transmission layers. In some other aspects, the multiple transmission layers may include a first transmission layer associated with a first constellation point and a second transmission layer associated with a second constellation point. In some other embodiments, the method may further include generating an estimated channel matrix at least in part based on the data stream associated with the channel.

[0144] In some other embodiments, the method may further include performing a first QR decomposition on the estimated channel matrix to obtain a first triangular R matrix. In some other embodiments, the method may further include performing a second QR decomposition on the data stream to obtain a first estimated signal.

[0145] In some other embodiments, the method may further include performing a second tree search at least in part based on the second triangular R matrix and the second estimated signal to obtain a second set of candidate symbol paths. In some other embodiments, the method may further include generating a second set of LLRs associated with the second transmission layer at least in part based on the second set of candidate symbol paths.

[0146] In some other embodiments, the method may further include holding the first set of LLRs. In some other embodiments, the method may further include holding the second set of LLRs in a buffer.

[0147] In some other embodiments, the method may further include performing channel decoding based at least in part on the first set of LLRs and the second set of LLRs.

[0148] In some aspects, the first reconstructed symbol may be a statistical average of the possible symbols transmitted in the first transmission layer.

[0149] According to another aspect of the present disclosure, a baseband chip for wireless communication is disclosed. The baseband chip may include a MIMO detection circuit. In some embodiments, the MIMO detection circuit may be configured to perform a first tree search based at least in part on a first triangular R matrix and a first estimated signal to obtain a first set of candidate symbol paths associated with the first transmission layer. In some other embodiments, the MIMO detection circuit may be configured to generate a first set of LLRs associated with the first transmission layer based at least in part on the first set of candidate symbol paths. In some other embodiments, the MIMO detection circuit may be configured to generate a first reconstructed symbol associated with the first transmission layer based at least in part on the first set of LLRs. In some other embodiments, the MIMO detection circuit may be configured to remove the last row and the last column of the first triangular R matrix to obtain a second triangular R matrix associated with the second transmission layer. In some other embodiments, the MIMO detection circuit may be configured to subtract the first reconstructed symbol from the first estimated signal to obtain a second estimated signal associated with the second transmission layer.

[0150] In some other embodiments, the baseband chip may include an interface operably coupled to the MIMO detection circuit and configured to receive a data stream associated with a channel. In some aspects, the channel may include multiple transmission layers. In some other aspects, the multiple transmission layers may include a first transmission layer associated with a first constellation point and a second transmission layer associated with a second constellation point. In some other embodiments, the MIMO detection circuit may further be configured to generate an estimated channel matrix based at least in part on the data stream associated with the channel.

[0151] In some other embodiments, the MIMO detection circuit is further configured to perform a first QR decomposition on the estimated channel matrix to obtain a first triangular R matrix. In some other embodiments, the MIMO detection circuit may be configured to perform a second QR decomposition on the data stream to obtain a first estimated signal.

[0152] In some other embodiments, the MIMO detection circuit may be configured to perform a second tree search based at least in part on the second triangular R matrix and the second estimated signal to obtain a second set of candidate symbol paths. In some other embodiments, the MIMO detection circuit may be configured to generate a second set of LLRs associated with the second transmission layer based at least in part on the second set of candidate symbol paths.

[0153] In some other embodiments, the baseband chip may further include a memory configured to hold a first set of LLRs. In some other aspects, the memory may further be configured to hold a second set of LLRs.

[0154] In some other aspects, the baseband chip may include a channel decoder circuit configured to perform channel decoding based at least in part on the first set of LLRs and the second set of LLRs.

[0155] The foregoing description of specific embodiments will disclose the general nature of the present disclosure, such that others can, by applying knowledge within the scope of the art, readily modify and / or adapt various applications, such as the specific embodiments, without undue experimentation and without departing from the general concept of the present disclosure. Accordingly, such adaptations and modifications are intended to be within the meaning and range of equivalents of the disclosed embodiments based on the teachings and guidance presented herein. It should be understood that the language or terminology herein is for the purpose of description and not of limitation, and thus the terminology or wording of this specification will be interpreted by those skilled in the art in light of the teachings and guidance.

[0156] Embodiments of the present disclosure have been described above by means of functional building blocks that illustrate the implementation of specified functions and their relationships. For convenience of description, the boundaries of these functional building blocks have been arbitrarily defined herein. Alternative boundaries may be defined so long as the specified functions and their relationships are appropriately performed.

[0157] The Summary of the Invention and the Abstract sections may set forth one or more but not all of the exemplary embodiments of the present disclosure as contemplated by the inventors, and thus are not intended to limit the present disclosure and the appended claims in any way.

[0158] Various functional blocks, modules, and steps have been disclosed above. The particular arrangements provided are illustrative and not restrictive. Accordingly, the functional blocks, modules, and steps may be reordered or combined in a manner different from the examples provided above. Similarly, some embodiments include only a subset of the functional blocks, modules, and steps, and any such subset is permitted.

[0159] The breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the appended claims and their equivalents.

Claims

1. A wireless communication device, comprising: a memory; and at least one processor, coupled to the memory and configured to: receive a data stream associated with a channel, the channel including a plurality of transmission layers, and the plurality of transmission layers including a first transmission layer associated with a first constellation point and a second transmission layer associated with a second constellation point; generate an estimated channel matrix at least in part based on the data stream associated with the channel; perform a first QR decomposition on the estimated channel matrix to obtain a first triangular R matrix; perform a second QR decomposition on the data stream to obtain a first received signal; perform a first tree search at least in part based on the first triangular R matrix and the first received signal to obtain a first set of candidate symbol paths associated with the first transmission layer; generate a first set of log-likelihood ratios (LLRs) associated with the first transmission layer at least in part based on the first set of candidate symbol paths; generate a first reconstructed symbol associated with the first transmission layer at least in part based on the first set of LLRs; remove the last row and the last column of the first triangular R matrix to obtain a second triangular R matrix associated with the second transmission layer; and subtract the first reconstructed symbol from the first received signal to obtain a second signal associated with the second transmission layer.

2. The device according to claim 1, wherein, The at least one processor is further configured to: perform a second tree search at least in part based on the second triangular R matrix and the second signal to obtain a second set of candidate symbol paths; and generate a second set of LLRs associated with the second transmission layer at least in part based on the second set of candidate symbol paths.

3. The apparatus according to claim 2, wherein, The memory is configured to: cache the first set of LLRs; and cache the second set of LLRs.

4. The device according to claim 3, wherein The at least one processor is further configured to: perform channel decoding at least in part based on the first set of LLRs and the second set of LLRs.

5. The device according to claim 1, wherein The first reconstructed symbol is a statistical average of possible symbols transmitted in the first transmission layer.

6. A wireless communication method, implemented by a baseband chip, comprising: receive a data stream associated with a channel, the channel including a plurality of transmission layers, and the plurality of transmission layers including a first transmission layer associated with a first constellation point and a second transmission layer associated with a second constellation point; generate an estimated channel matrix at least in part based on the data stream associated with the channel; perform a first QR decomposition on the estimated channel matrix to obtain a first triangular R matrix; perform a second QR decomposition on the data stream to obtain a first received signal; perform a first tree search at least in part based on the first triangular R matrix and the first received signal to obtain a first set of candidate symbol paths associated with the first transmission layer; generate a first set of log-likelihood ratios (LLRs) associated with the first transmission layer at least in part based on the first set of candidate symbol paths; generate a first reconstructed symbol associated with the first transmission layer at least in part based on the first set of LLRs; remove the last row and the last column of the first triangular R matrix to obtain a second triangular R matrix associated with the second transmission layer; and Subtract the first reconstructed symbol from the first received signal to obtain a second signal associated with the second transmission layer.

7. The method according to claim 6, further comprising: Performing a second tree search at least in part based on the second triangular R matrix and the second signal to obtain a second set of candidate symbol paths; And Generating a second set of LLRs associated with the second transmission layer at least in part based on the second set of candidate symbol paths.

8. The method according to claim 7, further comprising: Caching the first set of LLRs; And Caching the second set of LLRs.

9. The method according to claim 8, further comprising: Performing channel decoding at least in part based on the first set of LLRs and the second set of LLRs.

10. The method according to claim 6, wherein, The first reconstructed symbol is the statistical average of the possible symbols transmitted in the first transmission layer.

11. A baseband chip for wireless communication, comprising: An interface configured to receive a data stream associated with a channel, the channel including a plurality of transmission layers, and the plurality of transmission layers including a first transmission layer associated with a first constellation point and a second transmission layer associated with a second constellation point; And A multiple-input multiple-output (MIMO) detection circuit operably coupled to the interface and configured to: Generate an estimated channel matrix at least in part based on the data stream associated with the channel; Perform a first QR decomposition on the estimated channel matrix to obtain a first triangular R matrix; Perform a second QR decomposition on the data stream to obtain a first received signal; Perform a first tree search at least in part based on the first triangular R matrix and the first received signal to obtain a first set of candidate symbol paths associated with the first transmission layer; Generate a first set of log-likelihood ratios (LLRs) associated with the first transmission layer at least in part based on the first set of candidate symbol paths; Generate a first reconstructed symbol associated with the first transmission layer at least in part based on the first set of LLRs; Remove the last row and the last column of the first triangular R matrix to obtain a second triangular R matrix associated with the second transmission layer; and Subtract the first reconstructed symbol from the first received signal to obtain a second signal associated with the second transmission layer.

12. The baseband chip according to claim 11, wherein, The MIMO detection circuit is further configured to: Perform a second tree search at least in part based on the second triangular R matrix and the second signal to obtain a second set of candidate symbol paths; and Generate a second set of LLRs associated with the second transmission layer at least in part based on the second set of candidate symbol paths.

13. The baseband chip according to claim 12, further comprising a memory configured to: Cache the first set of LLRs; and Cache the second set of LLRs.

14. The baseband chip according to claim 13, further comprising a channel decoder circuit configured to: Perform channel decoding at least in part based on the first set of LLRs and the second set of LLRs.

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