WO2019071503A1

WO2019071503A1 - System and method for identifying communication nodes

Info

Publication number: WO2019071503A1
Application number: PCT/CN2017/105816
Authority: WO
Inventors: Zhifeng Yuan; Xun Yang; Weimin Li; Yuzhou HU; Hong Tang
Original assignee: Zte Corporation
Priority date: 2017-10-12
Filing date: 2017-10-12
Publication date: 2019-04-18
Also published as: CN111201828B; CN111201828A

Abstract

A system and method for allocating network resources are disclosed herein. In one embodiment, the method, performed by a first wireless communication node, includes: receiving a signal comprising a plurality of first spread symbols; selecting a first subset from a plurality of pre-configured spreading sequences by using the signal to calculate a metric for each of the first subset of the plurality of pre-configured spreading sequences; and based on the first subset of the plurality of pre-configured spreading sequences, processing the signal to identify at least one second wireless communication node.

Description

SYSTEM AND METHOD FOR IDENTIFYING COMMUNICATION NODES

TECHNICAL FIELD

The disclosure relates generally to wireless communications and, more particularly, to systems and methods for identifying one or more wireless communication nodes.

BACKGROUND

Generally, in a wireless communication network, a user equipment device (UE) sends at least one corresponding preamble signal to a base station (BS) to initiate a random access procedure. Such a preamble signal is used as a temporary identity of the UE for the BS to estimate various information, e.g.， timing advance command, scheduling of uplink resources for the UE to use in subsequent steps, such that the UE may use the above-mentioned information to finish the random access procedure. And after the random access procedure is finished, the UE is then allowed to transmit/receive data to/from the BS.

In some scenarios, while there are a plurality of UE’s in the wireless communication network, each of which would like to perform a respective random access procedure, each UE may randomly select a respective preamble signal to initiate the random access procedure. As the number of the UE’s that each would like to perform the random access procedure (at the same time) increases, such random selection on the preamble signals may cause collision, which may disadvantageously affect the random access procedures. To decrease the collision, a technique to increase a number of different preamble signals has been proposed.

However, the increased number of the preamble signals may in turn cause various issues such as, for example, additional waste on time/frequency resources, increased complexity for a receiving node (e.g.， the BS) to process the preamble signals, etc. Moreover, in various applications (e.g.， Massive Machine-Type Communications (M-MTC) , Ultra-Reliable and Low Latency Communications (URLLC) , Enhanced Mobile Broadband (eMBB) , etc. ) of the 5G New Radio (NR) communication network (hereinafter “5G network” ) , it is understood that the above-mentioned scenarios may occur more frequently. While exiting systems and methods cannot provide an entirely satisfactory solution, there is a need for a method and system to provide a technique to meet such an anticipated demand in the 5G network.

SUMMARY OF THE INVENTION

The exemplary embodiments disclosed herein are directed to solving the issues relating to one or more of the problems presented in the prior art, as well as providing additional features that will become readily apparent by reference to the following detailed description when taken in conjunction with the accompany drawings. In accordance with various embodiments, exemplary systems, methods, devices and computer program products are disclosed herein. It is understood, however, that these embodiments are presented by way of example and not limitation, and it will be apparent to those of ordinary skill in the art who read the present disclosure that various modifications to the disclosed embodiments can be made while remaining within the scope of the invention.

In one embodiment, a method includes: providing, by a first wireless communication node, a plurality of bits that comprise a spreading sequence； based on the spreading sequence, generating a plurality of spread symbols； and transmitting the plurality of spread symbols to perform a communication procedure initiated by the first wireless communication node.

In a further embodiment, a method, performed by a first wireless communication node, includes: receiving a signal comprising a plurality of first spread symbols； selecting a first subset from a plurality of pre-configured spreading sequences by using the signal to calculate a metric for each of the first subset of the plurality of pre-configured spreading sequences； and based on the first subset of the plurality of pre-configured spreading sequences, processing the signal to identify at least one second wireless communication node.

BRIEF DESCRIPTION OF THE DRAWINGS

Various exemplary embodiments of the invention are described in detail below with reference to the following Figures. The drawings are provided for purposes of illustration only and merely depict exemplary embodiments of the invention to facilitate the reader's understanding of the invention. Therefore, the drawings should not be considered limiting of the breadth, scope, or applicability of the invention. It should be noted that for clarity and ease of illustration these drawings are not necessarily drawn to scale.

Figure 1 illustrates an exemplary cellular communication network in which techniques disclosed herein may be implemented, in accordance with an embodiment of the present disclosure.

Figure 2 illustrates block diagrams of an exemplary base station and a user equipment device, in accordance with some embodiments of the present disclosure.

Figures 3A and 3B collectively illustrate a flow chart of an exemplary method to identify one or more wireless communication nodes, in accordance with some embodiments of the present disclosure.

Figures 4A and 4B collectively illustrate a symbolic diagram showing how a correlation matrix that is used to identify one or more wireless communication nodes is generated, in accordance with some embodiments of the present disclosure.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Various exemplary embodiments of the invention are described below with reference to the accompanying figures to enable a person of ordinary skill in the art to make and use the invention. As would be apparent to those of ordinary skill in the art, after reading the present disclosure, various changes or modifications to the examples described herein can be made without departing from the scope of the invention. Thus, the present invention is not limited to the exemplary embodiments and applications described and illustrated herein. Additionally, the specific order or hierarchy of steps in the methods disclosed herein are merely exemplary approaches. Based upon design preferences, the specific order or hierarchy of steps of the disclosed methods or processes can be re-arranged while remaining within the scope of the present invention. Thus, those of ordinary skill in the art will understand that the methods and techniques disclosed herein present various steps or acts in a sample order, and the invention is not limited to the specific order or hierarchy presented unless expressly stated otherwise.

Figure 1 illustrates an exemplary wireless communication network 100 in which techniques disclosed herein may be implemented, in accordance with an embodiment of the present disclosure. In the following discussion, the wireless communication network 100 may be a NB-IoT network, which is herein referred to as “network 100. ” Such an exemplary network 100 includes a base station 102 (hereinafter “BS 102” ) and a user equipment device 104 (hereinafter “UE 104” ) that can communicate with each other via a communication link 110 (e.g.， a wireless communication channel) , and a cluster of

notional cells

126, 130, 132, 134, 136, 138 and 140 overlaying a geographical area 101. In Figure 1, the BS 102 and UE 104 are contained within a respective geographic boundary of cell 126. Each of the

other cells

130, 132, 134, 136, 138 and 140 may include at least one base station operating at its allocated bandwidth to provide adequate radio coverage to its intended users.

For example, the BS 102 may operate at an allocated channel transmission bandwidth to provide adequate coverage to the UE 104. The BS 102 and the UE 104 may communicate via a downlink radio frame 118, and an uplink radio frame 124 respectively. Each radio frame 118/124 may be further divided into sub-frames 120/127 which may include data symbols 122/128. In the present disclosure, the BS 102 and UE 104 are described herein as non-limiting examples of “communication nodes, ” generally, which can practice the methods disclosed herein. Such communication nodes may be capable of wireless and/or wired communications, in accordance with various embodiments of the invention.

Figure 2 illustrates a block diagram of an exemplary wireless communication system 200 for transmitting and receiving wireless communication signals, e.g.， OFDM/OFDMA signals, in accordance with some embodiments of the invention. The system 200 may include components and elements configured to support known or conventional operating features that need not be described in detail herein. In one exemplary embodiment, system 200 can be used to transmit and receive data symbols in a wireless communication environment such as the wireless communication environment 100 of Figure 1, as described above.

System 200 generally includes a base station 202 (hereinafter “BS 202” ) and a user equipment device 204 (hereinafter “UE 204” ) . The BS 202 includes a BS (base station) transceiver module 210, a BS antenna 212, a BS processor module 214, a BS memory module 216, and a network communication module 218, each module being coupled and interconnected with one another as necessary via a date communication bus 220. The UE 204 includes a UE (user equipment) transceiver module 230, a UE antenna 232, a UE memory module 234, and a UE processor module 236, each module being coupled and interconnected with one another as necessary via a data communication bus 240. The BS 202 communicates with the UE 204 via a communication channel 250, which can be any wireless channel or other medium known in the art suitable for transmission of data as described herein.

As would be understood by persons of ordinary skill in the art, system 200 may further include any number of modules other than the modules shown in Figure 2. Those skilled in the art will understand that the various illustrative blocks, modules, circuits, and processing logic described in connection with the embodiments disclosed herein may be implemented in hardware, computer-readable software, firmware, or any practical combination thereof. To clearly illustrate this interchangeability and compatibility of hardware, firmware, and software, various illustrative components, blocks, modules, circuits, and steps are described generally in terms of their functionality. Whether such functionality is implemented as hardware, firmware, or software depends upon the particular application and design constraints imposed on the overall system. Those familiar with the concepts described herein may implement such functionality in a suitable manner for each particular application, but such implementation decisions should not be interpreted as limiting the scope of the present invention.

In accordance with some embodiments, the UE transceiver 230 may be referred to herein as an "uplink" transceiver 230 that includes a RF transmitter and receiver circuitry that are each coupled to the antenna 232. A duplex switch (not shown) may alternatively couple the uplink transmitter or receiver to the uplink antenna in time duplex fashion. Similarly, in accordance with some embodiments, the BS transceiver 210 may be referred to herein as a "downlink" transceiver 210 that includes RF transmitter and receiver circuity that are each coupled to the antenna 212. A downlink duplex switch may alternatively couple the downlink transmitter or receiver to the downlink antenna 212 in time duplex fashion. The operations of the two

transceivers

210 and 230 are coordinated in time such that the uplink receiver is coupled to the uplink antenna 232 for reception of transmissions over the wireless transmission link 250 at the same time that the downlink transmitter is coupled to the downlink antenna 212. Preferably there is close time synchronization with only a minimal guard time between changes in duplex direction.

The UE transceiver 230 and the base station transceiver 210 are configured to communicate via the wireless data communication link 250, and cooperate with a suitably configured RF antenna arrangement 212/232 that can support a particular wireless communication protocol and modulation scheme. In some exemplary embodiments, the UE transceiver 210 and the base station transceiver 210 are configured to support industry standards such as the Long Term Evolution (LTE) and emerging 5G standards, and the like. It is understood, however, that the invention is not necessarily limited in application to a particular standard and associated protocols. Rather, the UE transceiver 230 and the base station transceiver 210 may be configured to support alternate, or additional, wireless data communication protocols, including future standards or variations thereof.

In accordance with various embodiments, the BS 202 may be an evolved node B (eNB) , a serving eNB, a target eNB, a femto station, or a pico station, for example. In some embodiments, the UE 204 may be embodied in various types of user devices such as a mobile phone, a smart phone, a personal digital assistant (PDA) , tablet, laptop computer, wearable computing device, etc. The

processor modules

214 and 236 may be implemented, or realized, with a general purpose processor, a content addressable memory, a digital signal processor, an application specific integrated circuit, a field programmable gate array, any suitable programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof, designed to perform the functions described herein. In this manner, a processor may be realized as a microprocessor, a controller, a microcontroller, a state machine, or the like. A processor may also be implemented as a combination of computing devices, e.g.， a combination of a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other such configuration.

Furthermore, the steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in firmware, in a software module executed by

processor modules

214 and 236, respectively, or in any practical combination thereof. The

memory modules

216 and 234 may be realized as RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. In this regard,

memory modules

216 and 234 may be coupled to the

processor modules

210 and 230, respectively, such that the

processors modules

210 and 230 can read information from, and write information to,

memory modules

216 and 234, respectively. The

memory modules

216 and 234 may also be integrated into their

respective processor modules

210 and 230. In some embodiments, the

memory modules

216 and 234 may each include a cache memory for storing temporary variables or other intermediate information during execution of instructions to be executed by

processor modules

210 and 230, respectively.

Memory modules

216 and 234 may also each include non-volatile memory for storing instructions to be executed by the

processor modules

210 and 230, respectively.

The network communication module 218 generally represents the hardware, software, firmware, processing logic, and/or other components of the base station 202 that enable bi-directional communication between base station transceiver 210 and other network components and communication nodes configured to communication with the base station 202. For example, network communication module 218 may be configured to support internet or WiMAX traffic. In a typical deployment, without limitation, network communication module 218 provides an 802.3 Ethernet interface such that base station transceiver 210 can communicate with a conventional Ethernet based computer network. In this manner, the network communication module 218 may include a physical interface for connection to the computer network (e.g.， Mobile Switching Center (MSC) ) .

Referring again to Figure 1, as discussed above, when a plurality of UE’s (e.g., 104) each would like to initiate a random access procedure, each of the plurality of UE’s sends a preamble signal to the BS 102 for the BS 102 to identify the UE’s and accordingly send required information to respective UE’s for subsequent data communication. When the number of the UE’s increases, such techniques and corresponding improved techniques to increase randomness (i.e.， decreasing collision) have encountered various issues in the 5G network, as mentioned above.

The present disclosure provides various embodiments of systems and methods for the BS 102 to identify each of a plurality of UE’s without requiring the UE’s to send any preamble signals when initiating respective random access procedures. Instead, in some embodiments, each of the plurality of UE’s uses a spreading sequence, which is associated with one or more information bits that the UE would like to transmit, to spread respective symbols that are modulated based on the information bits, and transmits such spread symbols to the BS 102 for initiating the respective random access procedure. In some embodiments, when the BS 102 receives a signal containing such plural spread symbols that are respectively sent from the plurality of UE’s requesting the random access procedures, the BS 102 uses a Successive Interference Cancellation (SIC) technique to blindly decode the signal so as to identify each of the UE’s , and obtain respective information bit (s) . In some embodiments, the BS 102 successively filters one or more spreading sequences from the plurality of pre-configured spreading sequences by using the received signal to estimate at least one measurement, or metric. It is understood that the terms “measurement” and “metric” are exchangeable, for purposes of consistency, the term “measurement” will be used in the following discussions. More particularly, according to some embodiments of the present disclosure, the at least one measurement may be calculated, by the BS 102, based on a correlation matrix derived from the signal, or a cross-correlations matrix derived from the signal when the signal is received via two or more antennas of the BS 102. As such, the BS 102 may efficiently narrow down the number of spreading sequences that the BS 102 will use to reconstruct the received signal (e.g., to identify the UE’s and further obtain the information bit (s) that each UE sends) , which, in turn, may significantly decrease complexity and/or increase accuracy of identifying the UE’s even when collision occurs.

Embodiments on a transmitter side (e.g., a UE)

In some embodiments, when a UE (e.g.， UE 104) would like to initiate a random access procedure, the UE 104 may perform at least some of the following steps: providing a sequence d_O including a plurality of bits N_O to be transmitted, wherein the bits N_O include one or more information bits N_U that the UE 104 would like to transmit to the BS 102, and one or more bits N_D representing a spreading sequence； performing an error-detecting process (e.g.， a cyclic redundancy check (CRC) process) on the sequence d_O so as to generate an CRC’ed sequence d_E that includes N_E bits (N_E > N_O) ； performing a coding process (e.g.， a Turbo coding process) on the CRC’ed sequence d_E to generate a sequence d_Y that include N_Y bits (N_Y > N_E) ； performing a modulation process (e.g., a quadrature phase shift keying (QPSK) modulation process) on the sequence d_Y to generate a sequence d_C that includes N_C modulated symbols

wherein L_M represents a bit number of a single modulated symbol； using a spreading sequence identity, which may be indicated in the sequence d_E, to select the spreading sequence from a plurality of pre-configured spreading sequences or the spreading sequence, which may be already indicated in the sequence d_E, to spread the sequence d_C so as to generate a sequence d_W (alength of the sequence d_W, “N_W, ” may be equal to N_CN_S, wherein N_S is a length of the spreading sequence) ； and transmitting the sequence d_W using corresponding time-frequency resources to the BS 102. In some embodiments, subsequently to the CRC process, the one or more bits N_D representing the spreading sequence may be included (e.g., ) in respective CRC bits of the sequence d_E. In some other embodiments, the one or more bits N_D may correspond to a spreading sequence identity representing the spreading sequence, which may be used to identify the spreading sequence from a plurality of pre-configured spreading sequences. In some embodiments, the one or more information bits N_U may include an identity of the UE 104, which is typically knows as a UE ID.

Embodiments on a receiver side (e.g., a BS)

Figures 3A and 3B collectively illustrate a flow chart of an exemplary method performed by the BS 102 to identify one or more UE’s that each sends a plurality of spread symbols (as described above) to initiate a random access procedure, in accordance with various embodiments. The illustrated embodiment of the method 300 is merely an example. Therefore, it should be understood that any of a variety of operations may be omitted, re-sequenced, and/or added while remaining within the scope of the present disclosure. Moreover, in some embodiments, operations of the method 300 are provided to generally illustrate how the BS 102 identifies the one or more UE’s , so that each operation of the method 300 will be briefly described and further details will be provided in the following examples (e.g.， Examples 1 to 9) .

In some embodiments, the method 300 starts with operation 302 in which the BS 102 receives a signal “y, ” and uses the signal y to estimate a first measurement for each of a plurality of pre-configured spreading sequences. In some embodiments, such a signal y may include the above-discussed sequence d_W that include a plurality of spread symbols so that the signal y is herein referred to as spread symbols y. Further, in some embodiments, the spread symbols y may be a combination of a plurality of such sequences d_W, each of which is sent from a respective different UE requesting a respective random access procedure. Next, the method 300 continues to operation 304 in which the BS 102 selects a first subset from the plurality of pre-configured spreading sequences based on the first measurements. The method 300 continues to operation 306 in which the BS 102 uses the spread symbols y to estimate a second measurement for each of the first subset of pre-configured spreading sequences. The method 300 continues to operation 308 in which the BS 102 selects K_s equalized measurement vectors based on the second measurements, and uses the K_s equalized measurement vectors to respectively demodulate/decode the spread symbols y. The method 300 continues to determination operation 310 in which the BS 102 determines whether the decoded signals are each valid by checking whether the decoded signal passes an error detection circuit (e.g.， a CRC circuit) . If so, the method 300 continues to operation 312 in which the BS 102 retrieves various information from each of the decoded signals, and uses at least a portion of the various information to obtain a corresponding re-constructed signal “s. ” In some embodiments, the various information may include a UE ID of a particular UE, and the spreading sequence that the UE used to initiate the random access procedure. In some embodiments, when the UE ID and the spread sequence of this particular UE are retrieved, such a particular UE may be “identified. ” It is noted by persons of ordinary skill in the art that the re-constructed signal is generated by performing a series of substantially similar processes on the transmission end (e.g.， the UE 104) , e.g.， coding, modulating, spreading, etc.， to re-construct a sequence (e.g.， the sequence d_W) that the UE 104 sent. The method 300 continues to operation 314 in which the BS 102 performs a channel estimation based on each of the re-constructed signals. Next, the method 300 continues to operation 316 in which the BS 102 performs an interference cancelation on the spread symbols y. In some embodiments, subsequent to the operation 316, the method 300 may be iteratively performed from the operation 302 to the determination operation 310 until no more decoded signal that has been determined to be valid, in which the method 300 ends at operation 318.

Example 1

In some embodiments, the BS 102 may use a single antenna to receive the aforementioned spread symbols y. When the spread symbols y is presented in a matrix form, the spread symbols y may be an N_S×N_C matrix, wherein N_S represents a length of a spreading sequence, which may be predefined； and N_C represents a number of symbols prior to being spread, which may be determined by the BS 102 once the BS 102 receives the spread symbols y. Then, the BS 102 iteratively performs the following steps 1-10 of a procedure to process the spread symbols y so as to identify one or more UE’s that each sends a sequence (e.g.， d_W) to request the respective random access procedure.

Step 1 (corresponding to the operation 302) , the BS 102 estimates the first measurement “m” for each of the plurality of pre-configured spreading sequences, which are in a number of M_s. More specifically, in some embodiments, for a k^th spreading sequence among the M_s pre-configured spreading sequences, a respective first measurement m_k may be estimated by

wherein c_krepresents the k^th spreading sequence that may be presented as an N_S×1 vector, and k＝1, 2, …, M_S； and

that may be presented as an N_S×N_S matrix. Further, y^H represents a conjugate transport of the spread symbols y when the spread symbols y are in the matrix form, and

represents an inverse of the matrix

In some embodiments, the matrix

may be a correlation matrix of the spread symbols y when the spread symbols y are presented in the matrix form.

Step 2 (corresponding to part of the operation 304) , the BS 102 ascending sorts the respective first measurements of the M_s pre-configured spreading sequences. More specifically, the BS 102 rearrange the first measurements

in an ascending order to obtain

wherein the indexes

to

may respectively represent the rearranged M_s pre-configured spreading sequences in the ascending order, in accordance with some embodiments.

Step 3 (corresponding to part of the operation 304) , the BS 102 selects L_s spreading sequences,

from the M_s pre-configured spreading sequences as the first subset, wherein such L_s spreading sequences respectively correspond to the L_s smallest first measurements (L_S≤M_S) . Further, the BS 102 associates the spread symbols y with the first subset (i.e., the L_s spreading sequences) to obtain measurement vectors “u_i” . More specifically,

wherein u_i is a 1×N_C vector and i＝1, 2, …, L_S.

Step 4, the BS 102 equalizes the measurement vectors u_i to obtain equalized measurement vectors

wherein

is a 1×N_C vector and i＝1, 2, …, L_S.

Step 5 (corresponding to part of the operation 306) , the BS 102 calculates “r” for each of the equalized measurement vectors. In some embodiments, the r may be a signal-to-interference-plus-noise ratio (SINR) . More specifically, the BS 102 calculates the SINR for each of the equalized measurement vectors

to obtain

Step 6 (corresponding to the operation 308) , the BS 102 descending sorts the SINR’s of the L_s equalized measurement vectors. More specifically, the BS 102 rearrange

in a descending order to obtain

Further, the BS 102 selects K_s equalized measurement vectors from the plurality of equalized measurement vectors

wherein such K_s equalized measurement vectors respectively correspond to the K_s largest second measurements (i.e., SINR in the current example) , or each of the K_s largest second measurements is greater than a predefined SINR threshold. As such, it is understood that K_S≤L_S. Next, the BS 102 uses the K_s equalized measurement vectors to demodulate/decode the spread symbols y. More specifically, by using the K_s spreading sequences to demodulate/decode the spread symbols y, the BS 102 may obtain K_s decoded signals.

Step 7 (corresponding to the operation 310) , the BS 102 checks whether the K_s decoded signals passes the CRC circuit. More specifically, if not (e.g.， none of the K_s decoded signals passes the CRC circuit) , the procedure (to identify one or more UE’s from the spread symbols y) ends； and if so (e.g.， at least one of the K_s decoded signals passes the CRC circuit) , the procedure proceeds to Step 8.

Step 8 (corresponding to the operation 312) , the BS 102 uses the K_s decoded signals to obtain corresponding “used spreading sequences. ” Based on the used spreading sequences, the BS 102 obtains re-constructed signals

each of which may be presented as an N_S×N_C matrix. More specifically, in some embodiments, if in step 7, one or more of the K_s decoded signals do not pass the CRC circuit, the BS 102 may determine corresponding re-constructed signals each as a zero matrix (e.g.， s_k＝0) ； and if one or more of the K_s decoded signals pass the CRC circuit, the BS 102 may retrieve various information contained in the respective decoded signals to obtain corresponding re-constructed signals.

Step 9 (corresponding to operation 314) , the BS 102 estimate respective channel gain coefficients h_k for each of the re-constructed signals

the h_k may be presented as an N_S×N_C matrix. In some embodiments, if the re-constructed signal is a zero matrix (as determined in step 8) , the BS 102 may determine its corresponding channel gain coefficient as zero (i.e.， without performing a channel estimation procedure) .

Step 10 (corresponding to operation 316) , the BS 102 performs interference cancelation on the spread symbols y. More specifically, the BS 102 uses the following equation,

to cancel the signal (i.e.， the sequence including plural spread symbols) sent by each “identified” UE from the spread symbols y so as to continue identifying the remaining UE or UE’s. In some embodiments, h_k·s_k is a Hadamard product of h_k and s_k.

Example 2

In some embodiments, the BS 102 may use a single antenna to receive the aforementioned spread symbols y. When the spread symbols y are presented in a matrix form, the spread symbols y may be an N_S×N_C matrix, wherein N_S represents a length of a spreading sequence, which may be predefined； and N_C represents a number of symbols prior to being spread, which may be determined by the BS 102 once the BS 102 receives the spread symbols y. Then, the BS 102 iteratively performs the following steps 1-10 of a procedure to process the spread symbols y so as to identify one or more UE’s that each sends a sequence (e.g.， d_W) to request the respective random access procedure.

Step 1 (corresponding to the operation 302) , the BS 102 estimates the first measurement for each of the plurality of pre-configured spreading sequences, which are in a number of M_s. More specifically, in some embodiments, for a k^th spreading sequence among the M_s pre-configured spreading sequences, the respective first measurement m_k may be estimated by

that may be presented as an N_S×N_C matrix. Further, y^H represents a conjugate transport of the spread symbols y when the spread symbols y are in the matrix form, and

represents an inverse of the matrix

In some embodiments, the matrix

Step 2 (corresponding to part of the operation 304) , the BS 102 ascending sorts the respective first measurements of the M_s pre-configured spreading sequences. More specifically, the BS 102 rearrange the respective first measurements

of the M_s pre-configured spreading sequences in an descending order to obtain

wherein the indexes

to

or

wherein u_i is a 1×N_C vector and i＝1, 2, …, L_S.

wherein

is a 1×N_C vector and i＝1, 2, …, L_S.

to obtain

in a descending order to obtain

wherein such K_s equalized measurement vectors respectively correspond to the K_s largest second measurements (i.e., SINR in the current example) , or each of the K_s largest second measurements is greater than a predefined SINR threshold. As such, it is understood that K_S≤L_S. Next, the BS 102 uses the the K_s equalized measurement vectors to demodulate/decode the spread symbols y. More specifically, by using the K_s spreading sequences to demodulate/decode the spread symbols y, the BS 102 may obtain K_s decoded signals.

Step 8 (corresponding to the operation 312) , the BS 102 uses the K_s decoded signals to obtain corresponding used spreading sequences. Based on the used spreading sequences, the BS 102 obtains re-constructed signals

Example 3

In some embodiments, the BS 102 may use two or more antennas to receive the aforementioned spread symbols y. For example, a first antenna and a second antenna of the BS 102 may respectively receive signals y1 and y2, each of which includes a plurality of spread symbols. In this example, the BS 102 combine the signals y1 and y2, with respective weightings, as the spread symbols y. More specifically, the BS 102 may calculate a candidate set of weighting vectors, a_j, to combine the two or more signals, wherein j＝1, 2, …, M_C. That is, the candidate set includes M_c weighting vectors:

In some embodiments, the weighting vector a_j is an N_R×1 vector, wherein N_R is the number of antennas of the BS 102 that respectively receives the component signals of the spread symbols y. Further, the M_c weighting vectors

satisfy

When the spread symbols y are presented in a matrix form, the spread symbols y may be an N_S×N_C matrix, wherein N_S represents a length of a spreading sequence, which may be predefined； and N_C represents a number of symbols prior to being spread, which may be determined by the BS 102 once the BS 102 receives the spread symbols y. Then, the BS 102 iteratively performs the following steps 1-10 of a procedure to decode the spread symbols y so as to identify one or more UE’s that each sends a sequence (e.g.， d_W) to request the respective random access procedure.

Different form the Examples 1 and 2 in which the BS 102 only uses one antenna to receive the spread symbols y, before calculating the first measurements of the plurality of pre-configured spreading sequence, in some embodiments, the BS 102 may perform Step 0 to obtain signal

wherein

is an N_S×N_C matrix. Since the following steps are substantially similar to the Example 1 and 2, detailed descriptions of the following steps are not repeated here.

Step 1, for each weighting vector a_j, the BS 102 estimates the first measurement “m_k, _j” for each of the plurality of pre-configured spreading sequences. More specifically, in some embodiments, for a k^th spreading sequence, a respective first measurement m_k, _j may be estimated by

that may be presented as an N_S×N_S matrix.

Step 2, for each weighting vector a_j, the BS 102 ascending sorts the

to obtain

Step 3, the BS 102 selects L_s spreading sequences,

wherein L_S≤M_S. Further, the BS 102 associates the spread symbols y with the L_s spreading sequences to obtain respective measurement vectors

wherein u_i, j is a 1×N_C vector and i＝1, 2, …, L_S, and j＝1, 2, …, M_C.

Step 4, the BS 102 equalizes the measurement vectors u_i, j to obtain equalized measurement vectors

wherein i＝1, 2, …, L_S, and j＝1, 2, …, M_C.

Step 5, the BS 102 calculates a respective SINR for each of

to obtain r_i, j, wherein i＝1, 2, …, L_S, and j＝1, 2, …, M_C.

Step 6, the BS 102 descending sorts

to obtain

Further, the BS 102 selects K_s equalized measurement vectors from the set containing

wherein such K_s equalized measurement vectors correspond to the K_s largest SINR (K_S≤L_SM_C) , or each of the K_s largest SINR is greater than a predefined SINR threshold. Next, the BS 102 uses the K_s equalized measurement vectors (i.e., the K_s spreading sequences) to demodulate/decode the spread symbols y. More specifically, by using the K_s spreading sequences to demodulate/decode the spread symbols y, the BS 102 may obtain K_s decoded signals.

Step 7, the BS 102 checks whether the K_s decoded signals passes the CRC circuit. More specifically, if not (e.g.， none of the K_s decoded signals passes the CRC circuit) , the procedure (to identify one or more UE’s from the spread symbols y) ends； and if so (e.g.， at least one of the K_s decoded signals passes the CRC circuit) , the procedure proceeds to Step 8.

Step 8, the BS 102 uses the K_s decoded signals to obtain corresponding used spreading sequences. Based on the used spreading sequences, the BS 102 obtains re-constructed signals

each of which may be presented as an N_S×N_C×N_R matrix. More specifically, in some embodiments, if in step 7, one or more of the K_s decoded signals do not pass the CRC circuit, the BS 102 may determine corresponding re-constructed signals each as a zero matrix (e.g.， s_k＝0) ； and if one or more of the K_s decoded signals pass the CRC circuit, the BS 102 may retrieve various information contained in the respective decoded signals to obtain corresponding re-constructed signals.

Step 9, the BS 102 estimate respective channel gain coefficients h_k for each of the re-constructed signals

the h_k may be presented as an N_S×N_C×N_R matrix.

Step 10, the BS 102 performs interference cancelation on the spread symbols y. More specifically, the BS 102 uses the following equation,

to cancel the signal (i.e., the sequence including plural spread symbols) sent by each “identified” UE from the spread symbols y so as to continue identifying the remaining UE or UE’s. In some embodiments, h_k·s_k is a Hadamard product of h_k and s_k.

Example 4

In some embodiments, the BS 102 may use two or more antennas to receive the aforementioned spread symbols y. For example, a first antenna and a second antenna of the BS 102 may respectively receive signals y1 and y2. In this example, the BS 102 combine the signals y1 and y2, with respective weightings, as the spread symbols y. More specifically, the BS 102 may calculate a candidate set of weighting vectors, a_j, to combine the two or more signals, wherein j＝1, 2, …, M_C. That is, the candidate set includes M_c weighting vectors:

satisfy

When the spread symbols y are presented in a matrix form, the spread symbols y may be an N_S×N_C matrix, wherein N_S represents a length of a spreading sequence, which may be predefined； and N_C represents a number of symbols prior to being spread, which may be determined by the BS 102 once the BS 102 receives the spread symbols y. Then, the BS 102 iteratively performs the following steps 1-10 of a procedure to decode the spread symbols y so as to identify one or more UE’s that each sends a sequence (e.g., d_W) to request the respective random access procedure.

wherein

Step 1, for each weighting vector a_j, the BS 102 estimates the first measurement “m_k, j” for each of the plurality of pre-configured spreading sequences. More specifically, in some embodiments, for a k^th spreading sequence, a respective first measurement m_k, _j may be estimated by

that may be presented as an N_S×N_S matrix.

Step 2, for each weighting vector a_j, the BS 102 descending sorts the

to obtain

Step 3, the BS 102 selects L_s spreading sequences,

or

wherein i＝1, 2, …, L_S, and j＝1, 2, …, M_C.

Step 5, the BS 102 calculates a respective SINR for each of

to obtain r_i, j, wherein i＝1, 2, …, L_S, and j＝1, 2, …, M_C.

Step 6, the BS 102 descending sorts

to obtain

the h_k may be presented as an N_S×N_C×N_R matrix.

Example 5

Similar to Example 3, the BS 102 may use two or more antennas to receive the aforementioned spread symbols y, but different from Example 3, in some embodiments, the BS 102 may “append” the spread symbols y1 to y2, or the spread symbols y2 to y1, as the spread symbols y, which will be discussed in further detail below. Accordingly, the BS 102 iteratively performs the following steps 1-12 of a procedure to process the spread symbols y so as to identify one or more UE’s that each sends a sequence (e.g.， d_W) to request the respective random access procedure. It is noted that some of the steps in this procedure are substantially similar to the steps of above-discussed Examples, so the steps in this procedure will be briefly described.

Step 1, for a k^th (k＝1, 2, …, M_R) spreading sequence among the M_s pre-configured spreading sequences, the BS 102 calculate a matrix d_k.

wherein c_krepresents the k^th spreading sequence that may be presented as an N_S×1 vector, d_k may be presented as an N_RN_S×N_R matrix, and “0” represents an N_S×1 zero vector.

Step 2, for the k^th spreading sequence, the BS 102 estimates the corresponding first measurement “m_k, ” wherein

represent eigenvalues of the a matrix q_k and n is a positive integer, wherein

and

In some embodiments, the matrix

is an N_RN_S×N_RN_S matrix that may be a correlation matrix of the spread symbols y when the spread symbols y are presented in the matrix form.

Step 3, the BS 102 descending sorts

to obtain

Step 4, the BS 102 selects

wherein L_S≤M_R.

Step 5, for each weighting vector a_j (similar to the weighting vector in Example 3) , the BS 102 calculates

corresponding to the

spreading sequence, wherein u_i, j is a 1×N_C vector and i＝1, 2, …, L_S, and j＝1, 2, …, M_C.

Step 6, the BS 102 equalizes u_i, j to obtain

wherein i＝1, 2, …, L_S, and j＝1, 2, …, M_C.

Step 7, the BS 102 calculates the SINR r_i, j for each of

Step 8, the BS 102 descending sorts

to obtain

wherein such K_s equalized measurement vectors respectively correspond to the K_s largest SINR (K_S≤L_SM_C) , or each of the K_s largest SINR is greater than a predefined SINR threshold. Next, the BS 102 uses the K_s equalized measurement vectors (i.e.， the K_s spreading sequences) to demodulate/decode the spread symbols y. More specifically, by using the K_s spreading sequences to demodulate/decode the spread symbols y, the BS 102 may obtain K_s decoded signals.

Step 9, the BS 102 checks whether the K_s decoded signals passes the CRC circuit. More specifically, if not (e.g.， none of the K_s decoded signals passes the CRC circuit) , the procedure (to identify one or more UE’s from the spread symbols y) ends； and if so (e.g.， at least one of the K_s decoded signals passes the CRC circuit) , the procedure proceeds to Step 10.

Step 10, the BS 102 uses the K_s decoded signals to obtain corresponding used spreading sequences. Based on the used spreading sequences, the BS 102 obtains re-constructed signals

each of which may be presented as an N_RN_S×N_C matrix. More specifically, in some embodiments, if in step 9, one or more of the K_s decoded signals do not pass the CRC circuit, the BS 102 may determine corresponding re-constructed signals each as a zero matrix (e.g.， s_k＝0) ； and if one or more of the K_s decoded signals pass the CRC circuit, the BS 102 may retrieve various information contained in the respective decoded signals to obtain corresponding re-constructed signals.

Step 11, the BS 102 estimate respective channel gain coefficients h_k for each of the re-constructed signals

the h_k may be presented as an N_RN_S×N_C matrix. In some embodiments, if the re-constructed signal is a zero matrix (as determined in step 10) , the BS 102 may determine its corresponding channel gain coefficient as zero (i.e.， without performing a channel estimation procedure) .

Step 12, the BS 102 performs interference cancelation on the spread symbols y. More specifically, the BS 102 uses the following equation,

Example 6

represent eigenvalues of the a matrix q_k and n is a positive integer, wherein

and

In some embodiments, the matrix

Step 3, the BS 102 ascending sorts

to obtain

Step 4, the BS 102 selects

wherein L_S≤M_R.

or

corresponding to the

Step 6, the BS 102 equalizes u_i, j to obtain

wherein i＝1, 2, …, L_S, and j＝1, 2, …, M_C.

Step 7, the BS 102 calculates the SINR for each of

Step 8, the BS 102 descending sorts

to obtain

Example 7

In this Example, the BS 102 performs a substantially similar procedure as the procedure discussed in Example 4 except that the BS 102 uses a different technique to estimate the weighting vector a_j, which will be discussed in the step 5 below. Accordingly, it is noted that some of the steps in this procedure will be briefly described.

represent eigenvalues of the a matrix q_k and n is a positive integer, wherein

and

In some embodiments, the matrix

Step 3, the BS 102 descending sorts

to obtain

Step 4, the BS 102 selects

wherein L_S≤M_R.

Step 5, the BS 102 calculates the weighting vector a_j by using:

wherein

j＝1, 2, …, N_R, and 1≤j_min≤N_R.

are eigenvalues of the matrix

and

is an N_R×1 vector；

is the eigenvector corresponding to the eigenvalue

i.e.，

wherein i＝1, 2, …, L_S, and j＝1, 2, …, N_R.

Step 6, the BS 102 calculates

corresponding to the

spreading sequence, wherein u_i is a 1×N_C vector and i＝1, 2, …, L_S.

Step 7, the BS 102 equalizes u_i to obtain

wherein i＝1, 2, …, L_S.

Step 8, the BS 102 calculates the SINR r_i for each of

Step 9, the BS 102 descending sorts

to obtain

wherein such K_s spreading sequences respectively correspond to the K_s largest second measurements (K _S≤L_S) , or each of the K_s largest second measurements is greater than a predefined SINR threshold. Next, the BS 102 uses the K_s equalized measurement vectors to demodulate/decode the spread symbols y. More specifically, by using the K_s spreading sequences to demodulate/decode the spread symbols y, the BS 102 may obtain K_s decoded signals.

Step 10, the BS 102 checks whether the K_s decoded signals passes the CRC circuit. More specifically, if not (e.g.， none of the K_s decoded signals passes the CRC circuit) , the procedure (to identify one or more UE’s from the spread symbols y) ends； and if so (e.g.， at least one of the K_s decoded signals passes the CRC circuit) , the procedure proceeds to Step 10.

Step 11, the BS 102 uses the K_s decoded signals to obtain corresponding used spreading sequences. Based on the used spreading sequences, the BS 102 obtains re-constructed signals

each of which may be presented as an N_RN_S×N_C matrix. More specifically, in some embodiments, if in step 10, one or more of the K_s decoded signals do not pass the CRC circuit, the BS 102 may determine corresponding re-constructed signals each as a zero matrix (e.g.， s_k＝0) ； and if one or more of the K_s decoded signals pass the CRC circuit, the BS 102 may retrieve various information contained in the respective decoded signals to obtain corresponding re-constructed signals.

Step 12, the BS 102 estimate respective channel gain coefficients h_k for each of the re-constructed signals

Step 13, the BS 102 performs interference cancelation on the spread symbols y. More specifically, the BS 102 uses the following equation,

Example 8

represent eigenvalues of the a matrix q_k and n is a positive integer, wherein

and

In some embodiments, the matrix

Step 3, the BS 102 ascending sorts

to obtain

Step 4, the BS 102 selects

wherein L_S≤M_R.

Step 5, the BS 102 calculates the weighting vector a_j by using:

wherein

j＝1, 2, …, N_R, and 1≤j_min≤N_R.

are eigenvalues of the matrix

and

is an N_R×1 vector；

is the eigenvector corresponding to the eigenvalue

i.e.，

wherein i＝1, 2, …, L_S, and j＝1, 2, …, N_R.

Step 6, the BS 102 calculates

or

corresponding to the

spreading sequence, wherein u_i is a 1×N_C vector and i＝1, 2, …, L_S.

Step 7, the BS 102 equalizes u_i to obtain

wherein i＝1, 2, …, L_S.

Step 8, the BS 102 calculates the SINR r_i for each of

Step 9, the BS 102 descending sorts

to obtain

wherein such K_s spreading sequences respectively correspond to the K_s largest second measurements (K_S≤L_S) , or each of the K_s largest second measurements is greater than a predefined SINR threshold. Next, the BS 102 uses the K_s equalized measurement vectors to demodulate/decode the spread symbols y. More specifically, by using the K_s spreading sequences to demodulate/decode the spread symbols y, the BS 102 may obtain K_s decoded signals.

Example 9

In this Example, the BS 102 performs a substantially similar procedure as the procedure discussed in Example 5 except that the BS 102 uses a different technique to estimate the first measurement m_k, which will be discussed in the step 1 below. Accordingly, it is noted that some of the steps in this procedure will be briefly described.

Step 1, for the k^th spreading sequence, the BS 102 estimates the corresponding first measurement “m_k, ” wherein

represent eigenvalues of the a matrix q_k and n is a positive integer, wherein

and

In some embodiments, the matrix

is an N_S×N_S matrix that may be a correlation matrix of the spread symbols y when the spread symbols y are presented in the matrix form.

Step 2, the BS 102 descending sorts

to obtain

Step 3, the BS 102 selects

wherein L_S≤M_R.

Step 4, the BS 102 obtains signal

wherein

is an N_S×N_C matrix.

Step 5, the BS 102 calculates

corresponding to the

spreading sequences, wherein u_i is a 1×N_C vector, i＝1, 2, …, L_S, and j＝1, 2, …, M_C. And

wherein

is an N_S×N_S matrix.

Step 6, the BS 102 equalizes u_i, j to obtain

wherein i＝1, 2, …, L_S and j＝1, 2, …, M_C.

Step 7, the BS 102 calculates the SINR for each of

Step 8, the BS 102 descending sorts

to obtain

Step 10, the BS 102 uses the K_s decoded signals to obtain re-constructed signals

each of which may be presented as an N_RN_S×N_C matrix. Specifically, the BS 102 uses the K_s decoded signals to obtain corresponding used spreading sequences. Based on the used spreading sequences, the BS 102 obtains re-constructed signals

As mentioned above, in various embodiments of the present disclosure, the BS 102 uses the received signal y (spread symbols y) to generate a correlation matrix (e.g.，

) , and further uses the correlation matrix to identify one or more UE’s. Figures 4A and 4B symbolically illustrate how such a correlation matrix is generated using a simplified example in which 2 UE’s respectively send a plurality of spread symbols. In the illustrated embodiment of Figure 4A, a first UE (1^st UE) generates a sequence 401 (e.g.， the sequence d_C as discussed above) including 5 (e.g.， N_Cas discussed above) modulated symbols, uses a spreading sequence 403 with a length of 4 (e.g.， N_S as discussed above) to generate a sequence 405 (e.g.， the sequence d_W as discussed above) including 20 spread symbols, and sends the sequence 405 through a channel 407. Similarly, a second UE (2^nd UE) generates a sequence 411 (e.g.， the sequence d_C as discussed above) including 5 (e.g.， N_Cas discussed above) modulated symbols, uses a spreading sequence 413 with a length of 4 (e.g.， N_S as discussed above) to generate a sequence 415 (e.g.， the sequence d_W as discussed above) including 20 spread symbols, and sends the sequence 415 through a channel 417. In some embodiment, the spreading sequence, respectively used by the 1^st and 2^nd UE’s, may be identical to or different from each other.

Referring still to Figure 4, after the 1^st and 2^nd UE’s send the sequences 415 and 417 through the respective channels 407 and 417, the BS 102 receives the sequences 415 and 417, through the channels 407 and 417, as a plurality of spread symbols 431 (e.g.， the signal y as discussed above) . In some embodiments, the spread symbols 431 may be a sum of the sent sequences 415 and 417. As discussed above, the spread symbols 431 may be presented in a matrix form, which is illustrated as a matrix 433 shown in Figure 4B. Specifically, the matrix 433 has five columns 433-1, 433-2, 433-3, 433-4, and 433-5, each of which has 4 spread symbols (that may be sent from the 1^st and/or 2^nd UE’s ) . In some embodiments, based on the above-discussed equations through Examples 1-9, the correlation matrix can be calculated as:

which is also shown in the illustrated embodiment of Figure 4B. According to some embodiments, the BS 102 then uses such a correlation matrix to process the spread symbols 431 so as to identify the 1^st and 2^nd UE’s, as discussed above.

While various embodiments of the invention have been described above, it should be understood that they have been presented by way of example only, and not by way of limitation. Likewise, the various diagrams may depict an example architectural or configuration, which are provided to enable persons of ordinary skill in the art to understand exemplary features and functions of the invention. Such persons would understand, however, that the invention is not restricted to the illustrated example architectures or configurations, but can be implemented using a variety of alternative architectures and configurations. Additionally, as would be understood by persons of ordinary skill in the art, one or more features of one embodiment can be combined with one or more features of another embodiment described herein. Thus, the breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments.

It is also understood that any reference to an element herein using a designation such as "first, " "second, " and so forth does not generally limit the quantity or order of those elements. Rather, these designations can be used herein as a convenient means of distinguishing between two or more elements or instances of an element. Thus, a reference to first and second elements does not mean that only two elements can be employed, or that the first element must precede the second element in some manner.

Additionally, a person having ordinary skill in the art would understand that information and signals can be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits and symbols, for example, which may be referenced in the above description can be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

A person of ordinary skill in the art would further appreciate that any of the various illustrative logical blocks, modules, processors, means, circuits, methods and functions described in connection with the aspects disclosed herein can be implemented by electronic hardware (e.g., a digital implementation, an analog implementation, or a combination of the two) , firmware, various forms of program or design code incorporating instructions (which can be referred to herein, for convenience, as "software" or a "software module) , or any combination of these techniques. To clearly illustrate this interchangeability of hardware, firmware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware, firmware or software, or a combination of these techniques, depends upon the particular application and design constraints imposed on the overall system. Skilled artisans can implement the described functionality in various ways for each particular application, but such implementation decisions do not cause a departure from the scope of the present disclosure.

Furthermore, a person of ordinary skill in the art would understand that various illustrative logical blocks, modules, devices, components and circuits described herein can be implemented within or performed by an integrated circuit (IC) that can include a general purpose processor, a digital signal processor (DSP) , an application specific integrated circuit (ASIC) , a field programmable gate array (FPGA) or other programmable logic device, or any combination thereof. The logical blocks, modules, and circuits can further include antennas and/or transceivers to communicate with various components within the network or within the device. A general purpose processor can be a microprocessor, but in the alternative, the processor can be any conventional processor, controller, or state machine. A processor can also be implemented as a combination of computing devices, e.g.， a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other suitable configuration to perform the functions described herein.

If implemented in software, the functions can be stored as one or more instructions or code on a computer-readable medium. Thus, the steps of a method or algorithm disclosed herein can be implemented as software stored on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that can be enabled to transfer a computer program or code from one place to another. A storage media can be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer.

In this document, the term "module" as used herein, refers to software, firmware, hardware, and any combination of these elements for performing the associated functions described herein. Additionally, for purpose of discussion, the various modules are described as discrete modules； however, as would be apparent to one of ordinary skill in the art, two or more modules may be combined to form a single module that performs the associated functions according embodiments of the invention.

Additionally, memory or other storage, as well as communication components, may be employed in embodiments of the invention. It will be appreciated that, for clarity purposes, the above description has described embodiments of the invention with reference to different functional units and processors. However, it will be apparent that any suitable distribution of functionality between different functional units, processing logic elements or domains may be used without detracting from the invention. For example, functionality illustrated to be performed by separate processing logic elements, or controllers, may be performed by the same processing logic element, or controller. Hence, references to specific functional units are only references to a suitable means for providing the described functionality, rather than indicative of a strict logical or physical structure or organization.

Various modifications to the implementations described in this disclosure will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other implementations without departing from the scope of this disclosure. Thus, the disclosure is not intended to be limited to the implementations shown herein, but is to be accorded the widest scope consistent with the novel features and principles disclosed herein, as recited in the claims below.

Claims

A method, comprising:

providing, by a first wireless communication node, a plurality of bits that comprise a spreading sequence；

based on the spreading sequence, generating a plurality of spread symbols； and

transmitting the plurality of spread symbols to perform a communication procedure initiated by the first wireless communication node.
The method of claim 1, wherein the communication procedure comprises at least one random access procedure.
The method of claim 1, wherein the plurality of bits further comprise one or more information bits to be transmitted by the first wireless communication node.
The method of claim 3, wherein the plurality of bits further comprise one or more cyclic redundancy check bits, and the spreading sequence is included in either the one or more cyclic redundancy check bits or the one or more information bits.
The method of claim 1, wherein the plurality of bits further comprise a spreading sequence identity associated with the spreading sequence for the spreading sequence to be identified from a plurality of pre-configured spreading sequences.
The method of claim 1, wherein the plurality of bits further comprise an identity of the first wireless communication node.
A computing device configured to carry out the method of any one claims 1 through 6.
A non-transitory computer-readable medium having stored thereon computer-executable instructions for carrying out the method of any one claims 1 through 6.
A method performed by a first wireless communication node, comprising:

receiving a signal comprising a plurality of first spread symbols；

selecting a first subset from a plurality of pre-configured spreading sequences by using the signal to calculate a metric for each of the first subset of the plurality of pre-configured spreading sequences； and

based on the first subset of the plurality of pre-configured spreading sequences, processing the signal to identify at least one second wireless communication node.
The method of claim 9, wherein the plurality of spread symbols are generated based on a plurality of information bits that the second wireless communication node transmits for performing a random access procedure.
The method of claim 9, wherein the plurality of first spread symbols are transmitted by one or more wireless communication nodes each requesting for a respective random access procedure.
The method of claim 9, further comprising:

receiving the plurality of first spread symbols using a first antenna of the first wireless communication node.
The method of claim 12, wherein the metric is calculated based on a correlation matrix of the signal when the signal is presented in a matrix form.
The method of claim 13, further comprising:

in an ascending order, sort the metrics of the plurality of pre-configured spreading sequences；

selecting a first number of smallest sorted metrics； and

determining the first subset as ones of the plurality of pre-configured spreading sequences with the first number of smallest sorted metrics.
The method of claim 13, further comprising:

in a descending order, sort the metrics of the plurality of pre-configured spreading sequences；

selecting a first number of largest sorted metrics； and

determining the first subset as ones of the plurality of pre-configured spreading sequences with the first number of largest sorted metrics.
The method of claim 9, further comprising:

associating the signal with the first subset of the plurality of pre-configured spreading sequences to provide a plurality of measurement vectors；

equalizing the plurality of measurement vectors；

calculating a signal-to-interference-plus-noise ratio for each of the plurality of equalized measurement vectors； and

selecting a subset from the plurality of equalized measurement vectors, wherein each of the subset of the plurality of equalized measurement vectors satisfies a predefined condition.
The method of claim 16, further comprising:

using the subset of the plurality of equalized measurement vectors to decode the signal；

based on respective decoding results on the signal, retrieving one or more used spreading sequences and identifying the at least one second wireless communication node；

using the one or more used spreading sequences to re-construct the signal；

performing a channel estimation based on each of the re-constructed signal； and

performing an interference cancelation on the signal.
The method of claim 9, further comprising:

receiving the signal using a first antenna and a second antenna of the first wireless communication node, wherein the plurality of first spread symbols are received by the first antenna and a plurality of second spread symbols comprised in the signal are received by the second antenna.
The method of claim 18, further comprising:

weighting the pluralities of first and second spread symbols, respectively； and

combining the weighted pluralities of first and second spread symbols as the signal.
The method of claim 18, further comprising:

when the pluralities of first and second spread symbols are presented in respective matrix forms, appending the matrix form of the plurality of first spread symbols to the matrix form of the plurality of second spread symbols as the signal.
The method of claim 18, wherein the metric is calculated based on a correlation matrix of the signal when the signal is presented in a matrix form.
The method of claim 21, further comprising:

in an ascending order, sort the metrics of the plurality of pre-configured spreading sequences；

selecting a first number of smallest sorted metrics； and

determining the first subset as ones of the plurality of pre-configured spreading sequences with the first number of smallest sorted metrics.
The method of claim 21, further comprising:

in a descending order, sort the metrics of the plurality of pre-configured spreading sequences；

selecting a first number of largest sorted metrics； and

determining the first subset as ones of the plurality of pre-configured spreading sequences with the first number of largest sorted metrics.
The method of claim 21, further comprising:

associating the signal with the first subset of the plurality of pre-configured spreading sequences to provide a plurality of measurement vectors.
The method of claim 24, further comprising:

equalizing the plurality of measurement vectors；

calculating a signal-to-interference-plus-noise ratio for each of the plurality of equalized measurement vectors； and

selecting a subset from the plurality of equalized measurement vectors, wherein each of the subset of the plurality of equalized measurement vectors satisfies a predefined condition；
The method of claim 25, further comprising:

using the subset of the plurality of equalized measurement vectors to decode the signal；

based on respective decoding results on the signal, retrieving one or more used spreading sequences and identifying the at least one second wireless communication node；

using the one or more used spreading sequences to re-construct the signal；

performing a channel estimation based on the re-constructed signal； and

performing an interference cancelation on the signal.
A computing device configured to carry out the method of any one claims 9 through 26.
A non-transitory computer-readable medium having stored thereon computer-executable instructions for carrying out the method of any one claims 9 through 26.