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CN-116321515-B - Cognitive-assisted large-scale terminal unlicensed random access method

CN116321515BCN 116321515 BCN116321515 BCN 116321515BCN-116321515-B

Abstract

The invention belongs to the technical field of wireless communication and discloses a cognitive-assisted large-scale terminal unlicensed random access method, which comprises the steps of firstly enabling active users to sense an uplink channel state, selecting a channel to be accessed according to interference power levels of all channels, determining uplink transmission power levels, then enabling the active users to randomly select a preamble sequence to spread data, combining the preamble sequence and the spread data into a frame signal, enabling the selected power levels to transmit signal frames to a base station through the selected channel, finally enabling the base station to separate signals with different power levels by adopting a sequential interference cancellation technology, recovering the transmission signals of the active users in each power level through preamble detection, judging the competition result of the active users and analyzing random access performance. The invention is suitable for the uplink burst transmission scene of large-scale users, can effectively reduce large-scale unlicensed random access conflict, improve the access success probability of users and improve the throughput of uplink channels of a cellular network.

Inventors

  • ZHANG JING
  • Kai Jinjin
  • WEI GUO
  • ZHU HONGBO

Assignees

  • 南京邮电大学

Dates

Publication Date
20260505
Application Date
20230328

Claims (7)

  1. 1. The cognitive-assisted large-scale terminal unlicensed random access method is characterized by comprising the following steps of: Step 1, active users sense the state of an uplink channel in a sensing time slot, select channels to be accessed according to interference power levels of different channels and determine uplink transmission power levels, and independently sense the interference power levels of all N c uplink channels to select the interference power levels lower than a threshold value The smallest channel is used as an uplink access channel, and one power level is selected from the power level set Q to be used as an uplink transmission power level according to a power level selection criterion; Step 2, the active users execute competition access and data transmission in the transmission time slot, each active user randomly selects a preamble sequence from the preamble combination, spreads the transmission data by using the preamble sequence, combines the preamble sequence and the spread data into a frame signal, and transmits the signal frame to the base station through a selected channel at a selected power level; Step 3, the active user receives the access result fed back by the base station in the feedback waiting time slot, the base station receives the uplink signal of the active user, adopts the sequential interference cancellation technology to detect the power level of the received signal, and then detects the preamble sequence carried on each power level through the correlation operation, thereby recovering the uplink transmission data of the active user, determining the access conflict condition of the user and feeding back the access result of the user; In step 1, consider a single cell mMTC system scenario: The base station is equipped with M antennas, N single antenna active user terminals are uniformly distributed in the cell, the single burst service data length of each active user is v bits, and the active user label set is The system has N c uplink frequency channels and K orthogonal leader sequences with length J serving uplink random access of users, K is less than or equal to J, and the uplink channel set is defined as Preamble sequence set Where s k denotes the kth leader sequence, The different preambles are orthogonal to each other and have an energy of 1, i.e All have Defining a preamble matrix SS H ＝I K , where S H represents the hermitian of matrix S, I K represents the K row and K column single-bit matrix, A complex field representing K rows and J columns; The uplink access channel selection method and the uplink transmission power level selection method are specifically described as follows: step 1a, defining a user transmission power level set and dividing an interference power level section; Let the set of uplink transmit power levels for active users be q= { Q 1 ,…,q L }, the set containing L power levels, where Q l represents the i-th power level, I q is a reference number set indicating the transmission power level, and the channel interference power level is uniformly divided into L sections corresponding to the transmission power level, so that And Respectively representing the start point value and the end point value of the ith section, prescribing Wherein the method comprises the steps of An interference power threshold representing an accessible channel; The power levels Q i and Q j in set Q must meet Q i <q j and the end point value of the ith interference power level segment Also less than the endpoint value of the jth interference power level segment I.e. Step 1b, the active user selects an uplink access channel according to the interference power level; let the set of interference power levels of all N c uplink channels perceived by active users N, N E I a be Wherein the method comprises the steps of Indicating that active user n perceives an interference power level on channel u, active user n never meeting an interference power threshold, i.e. Selecting the channel with the smallest current interference power level as the channel to be accessed, namely selecting the channel As an uplink access channel; if an active user perceives that the interference power level on all current channels is higher than the interference power threshold The active user retries access after delaying for one frame time; Step 1c, an active user selects an uplink transmission power level; Uplink access channel selected according to step 1b Query collection Obtaining that active user n is on the channel Upper perceived interference power level Judging the interference power level section where it is located if Then Belonging to the ith zone, active user n selects the (l+1-i) th power level q L+1-i as the transmit power level for its uplink access transmission.
  2. 2. The cognitive-assisted large-scale terminal unlicensed random access method according to claim 1, wherein the active user access transmission time frame structure is specifically: The time frame comprises a sensing time slot, a transmission time slot and a feedback waiting time slot, wherein the sensing time slot has the length of tau and the transmission time slot has the length of T d , an active user senses the state of an uplink channel by adopting an energy detection method in the sensing time slot and acquires the interference power level of each channel, an uplink access channel and an uplink transmission power level are selected according to the interference power level of each channel, the active user transmits a preamble and a data signal to a base station through the selected channel in the transmission time slot at the selected power level, and the active user waits for an access result feedback message from the base station in the feedback waiting time slot.
  3. 3. The cognitive-assisted large-scale terminal unlicensed random access method according to claim 1, wherein active users transmit preamble and data signals to a base station at a selected transmit power level through a selected uplink channel, the preamble and data transmission steps being specifically: step 2a-1, an active user randomly selects one leader sequence from K leader sequences; Let the preamble sequence number c n ,c n e {1, 2..once, K }, N e {1, 2..once, N }, selected by the active user N, the preamble selection vector of this user is Where 1 [x] is an indicator function, 1 [x] =1 when condition x is met, otherwise 1 [x] =0, and then the preamble sequence p n sent by active user n is expressed as: Wherein S T represents the transpose of the preamble matrix S; the transposed vector of p n is represented, And ii p n ‖ 2 = 1, Step 2a-2, the active user uses the selected preamble sequence to spread the v bit service data to generate a spread sequence with the length of D= vJ; Let v n ＝[d 1 ,d 2 ,...d v be the original service data of active user n, and the data x n after spreading it by p n is expressed as x n ＝[x 1 ,x 2 ,...x D ]＝[d 1 p n ,d 2 p n ,...d v p n ] (2) Wherein, the ‖x n ‖ 2 =1,D=vJ; Step 2a-3, the active user combines the preamble sequence and the spread spectrum data into a frame of signal, and sends the signal frame to the base station at a selected power level through a selected uplink channel; combining equation (1) and equation (2), a frame signal z n sent by active user n in the time domain is: Order the A channel selection vector representing active user n, a frame signal F n transmitted by active user n in a time-frequency two-dimensional space is represented as Wherein, the A transmission signal representing active user n on channel u;
  4. 4. The cognitive-assisted large-scale terminal unlicensed random access method according to claim 3, wherein the base station performs power level detection on the received signal first, specifically: Step 3a-1, a base station receives summation signals from N c uplink channels; Considering that the uplink channel from the active user to the base station is a Rayleigh fading joint additive Gaussian white noise channel, the channel characteristic is kept constant and quasi-orthogonality is satisfied in one frame time, and one frame signal G received by the base station is the sum signal of N users and is expressed as: wherein F n ＝z n u n represents a frame signal of active user n; an attenuation coefficient matrix of N c uplink channels from the user N to M antennas of the base station is represented; Attenuation coefficient vector representing N c uplink channels of user N and base station antenna m, wherein Represents the attenuation coefficient of the u-th uplink channel between the user N and the base station antenna m, N represents the uplink channel complex additive white gaussian noise matrix, It obeys a Gaussian distribution with 0 variance sigma 2 I M as the mean, namely N-CN (0, sigma 2 I M ) is noise average power, and I M represents an M-dimensional unit array; Step 3b-1, the base station carries out band-pass filtering on the received uplink signals to obtain the received signals of N c uplink channels; The base station receives the signal G which is a broadband signal containing N c frequency bands, carries out N c paths of band pass filtering on the received signal to obtain N c uplink channels of received signals; let the received signal on the uplink channel u be G u , u ε CH, expressed as Wherein, the A sum signal representing the received power level q l on channel u, Q l,n represents that active user n chooses the first power level q l ,l∈I q ; a channel attenuation coefficient vector representing active user n to base station M antennas on channel u; Representing the set of active users on channel u that select power level q l ; Step 3c-1, detecting each power level signal from high to low by sequentially using sequential interference cancellation SIC technique on the received signal G u on each uplink channel Assuming a power level signal contained in the received signal G u on channel u The method meets the following conditions: calculating a power level signal Signal to interference plus noise ratio (snr) The method comprises the following steps: Wherein, the Representing the set of active users on channel u that select power level q l , Represents the set of active users on channel u with the selected power level q j ,q j <q l , N u,l and N u,j represent the number of active users carried by power levels q l and q j on channel u, respectively, σ 2 represents the channel noise power, Judging Whether or not it is greater than the detection threshold of the base station receiver I.e. Whether or not it is: If not, the signals carried on the power level q l ,q l-1 ,…,q 1 on the channel u cannot be detected, and the active users carried on the power levels fail to access; If yes, the base station adopts SIC technology to detect the power level signals from high to low Detecting that the output power level signal is Is recorded as the estimated value of (2)
  5. 5. The cognitive assisted large scale terminal unlicensed random access method of claim 4, wherein the base station further performs preamble detection on the detected power level signal on each channel to recover active user data and determine a random access result; the preamble sequence detection method specifically comprises the following steps: step 3a-2, each power level signal carried from each channel Separating the preamble signal and the data signal of the active user; Will be Is decomposed into Wherein, the A preamble signal of q l representing the power level carried by channel u detected by the base station, A data signal with the power level q l , which represents the channel u detected by the base station; And Expressed as: step 3b-2, receiving and preamble signals Performing correlation operation with the preamble matrix S to obtain an estimated value of a user preamble selection vector, and then recovering a preamble sequence of the user; Base station receives and preambles on channel u and power level q l Performing correlation operation with the preamble sequence matrix S, and recording the result as Expressed as: Wherein, the A channel attenuation coefficient matrix representing N active users to a base station on a channel u; A joint selection matrix representing N active users for channel u and power level q l ; representing a preamble sequence matrix transmitted by N active users; Representing a preamble matrix; Representing the preamble selection matrix of N active users on channel u and power level q l , A preamble selection vector representing active user n on channel u and power level q l if The kth element of (1), i.e The preamble sequence representing active user n transmitting on channel u at power level q l is s k ; Representing a noise matrix superimposed on N active user signals, And (3) with Have the same distribution; Assuming a matrix of channel attenuation coefficients It is known to combine it with Multiplying to obtain preamble selection matrix of N active users on channel u and power level q l Estimate of (2) Is that Wherein, the Representation matrix Is a hermitian matrix of (c); adopts rounding method to pair Element rounding to obtain an approximate estimate thereof Preamble selection vector representing user n on channel u and power level q l Is a similar estimate of (1); In view of each active user selecting only one preamble sequence to send, matrix in case of no access collision At most one element is 1 and the other elements are all 0, so that the preamble sequence index transmitted by active user n on channel u at power level q l is estimated as: Wherein, the Representing vectors Is the kth element of (2); here the number of the elements is the number, Indicating that active user n did not transmit a preamble signal on channel u at power level q l , and correspondingly, the preamble sequence estimate transmitted on channel u at power level q l The method comprises the following steps: Supplementary definition herein Is a null preamble sequence; For received signals Traversing channel u and power level q l to obtain all Whereas each active user selects only one channel and one power level to perform random access, the estimated value of the preamble sequence p n transmitted by active user n The calculation is as follows: accordingly, the estimated value of the preamble sequence matrix P transmitted by all N active users Final detection as Step 3c-2, for received data signals Detecting and recovering active user data signals; Data signals received by a base station on channel u and power level q l Represented as Wherein, the A spread spectrum data signal matrix representing the transmissions of N active users; Will be And channel characteristic matrix Multiplying to obtain estimated values of spread spectrum signal matrix transmitted by N active users on channel u and power level q l The method comprises the following steps: traversing channel u and power level q l to find all And adding to obtain signal sequences sent by N active users Estimate of (2) The method comprises the following steps: Wherein, the An estimate representing the signal sequence x n transmitted by active user n; By means of For a pair of Despreading to recover the original business data of active user
  6. 6. The cognitive-assisted large-scale terminal unlicensed random access method according to claim 5, wherein the user collision detection method specifically comprises: Two or more users using the same channel and the same power level and the same preamble will experience access collisions, i.e. users experiencing access collisions are co-located in the set And And its leading selection vector And The same; Step 3a-3, acquiring an active user set carried by each power level on all channels; Active user set having preamble sequence transmitted at power level q l on channel u Is estimated as (1) The calculation is as follows: Wherein, the Preamble selection vector representing active user n on channel u and power level q l Is a function of the estimated value of (2); representing vectors 0-Norm of (i.e. vector) The number of non-zero elements in the received and preamble signal Traversing channel u and power level q l , the active user set on all channels can be obtained Step 3b-3, calculating a user pilot frequency conflict pattern; Defining a pilot collision pattern e u,l (n, n ') for user n, n' on channel u and power level q l as a user preamble selection vector And The product of (a), i.e In view of the difficulty of the base station to learn the exact preamble selection vector of active users n, n' And Can only obtain its estimated value And Therefore, the formula (20) And The estimated value is used for replacing the estimated value to obtain the estimated value of the pilot collision pattern e u,l (n, n') I.e. If user n, n ' selects the same pilot sequence, e u,l (n, n ')=1, otherwise, e u,l (n, n ')=0; Step 3c-3, judging the random access conflict of the active user; based on the formula (21), the following active user access conflict judgment method is designed: 1) If e u,l (n, n ')=1, the active users n, n' have access collision, both of which have failed in contention access; 2) If e u,l (n, n')=0, the active users n, n ′ do not have access collision, both of which compete for successful access, traversing the whole user set The access competition result of all active users can be obtained; Step 3d-3, the base station feeds back the access result to the active users; For the user with access success, the base station feeds back the access success confirmation message to the user through the broadcast channel, and for the user with access failure, the base station feeds back the access failure message to the user through the broadcast channel and informs the user of the delay and then tries to access again.
  7. 7. The cognitive-assisted large-scale terminal unlicensed random access method of claim 6, wherein the access performance of active users is analyzed as follows: Defining random access probability as probability of successfully decoding uplink signal sent by active user at base station, making any active user n select channel u and power level q l , i.e The random access probability of the user is analyzed in three ways: step 3a-4, calculating the probability of the active user successfully obtaining the access channel; When the active user n perceives that the interference power level of at least one channel is lower than the interference power threshold, the user can obtain the access channel, and therefore, the probability P ch that the active user n successfully obtains the access channel is calculated as: Wherein, the Indicating that active user n perceives an interference level on channel u Exceeding an interference power threshold Probability of (2); Step 3b-4, calculating the probability that the power level is correctly detected; The probability that the active user signal carried by the power level q l on the channel u can be correctly detected is not limited by the successful access of the active user n to the channel u and the selection of the power level q l as the uplink transmission power The calculation is as follows: Wherein, the Indicating the probability that the ith power level on channel u can be correctly detected; Step 3c-4, calculating the probability that the active user uses a unique preamble on the selected channel and power level; If the number of users selecting channel u and power level q l is N u,l , the probability that user N selects a unique preamble on channel u and power level q l Calculated as Wherein K represents the number of orthogonal preamble sequences; Step 3d-4, calculating random access probability of the active user; the access probability Pr u,l under the conditions of the active user n selection channel u and the power level q l is calculated as: Averaging the channel u and the power level q l by the equation (25) to obtain the random access probability of the active user as follows: Wherein, the

Description

Cognitive-assisted large-scale terminal unlicensed random access method Technical Field The invention belongs to the technical field of wireless communication, and particularly relates to a cognitive-assisted large-scale terminal unlicensed random access method. Background Large-scale machine type Communication (MASSIVE MACHINE TYPE Communication, mMTC) is one of three application scenarios of the fifth generation mobile Communication system, and is mainly accessed to a network by deploying mass machine equipment so as to realize intelligent society such as intelligent mapping, automatic driving, intelligent medical treatment and the like. mMTC system presents characteristics of mass equipment access, uplink small data transmission, sporadic communication, low power consumption of terminal and the like, and the brand new characteristics bring brand new challenges to wireless access technology. For example, the random access based on authorization has the problems of large control signaling overhead and overlong transmission delay, and the limited spectrum resources can not bear the orthogonal access of massive terminals. Therefore, how to carry mMTC efficient low-overhead random access of a terminal (user) with limited spectrum resources is one of the important problems to be solved in the current wireless network. Unlicensed random access is one of the mainstream technical schemes for supporting mMTC terminal low-overhead access transmission. However, since the base station does not participate in access coordination, and the terminal (user) is unknown to the network environment, the probability of collision of user access is high. Currently mMTC terminal unlicensed random access studies are mostly spread around reducing access collision, for example, document CN115499938a discloses a mMTC unlicensed random access method based on multiple power levels-multiple preambles, which forms a combined preamble by transmitting multiple preambles while distinguishing users with multiple power levels to reduce access collision of users. However, this scheme does not consider the advanced awareness of the access environment, i.e. the channel occupancy and interference situation by the user before random access is still unknown, and transmitting multiple preambles will occupy additional transmission time and transmit power and consume additional reception detection overhead. Disclosure of Invention In order to solve the technical problems, the invention provides a cognition-assisted large-scale terminal unlicensed random access method which is suitable for the scene of uplink burst transmission of a large number of machine type terminals (users). The method combines an unlicensed random access technology with a Cognitive Radio (Cognitive Radio) technology, provides 'eyes' for uplink random access of a user by enabling mMTC frequency spectrum sensing capability of the terminal (user), enables active users to obtain occupation conditions of a current channel before random access, thereby pertinently avoiding high-load channels and selecting channel access with lowest current interference, simultaneously distinguishes users by combining multiple power levels, determines uplink transmission power according to interference power levels of the selected channels so as to reduce random access collision of the user under a single preamble, saves preamble time cost and power cost, and finally improves channel multiplexing efficiency and access success probability of the user. The cognitive auxiliary large-scale terminal unlicensed random access method comprises the following steps: Step 1, active users sense the state of an uplink channel in a sensing time slot, select channels to be accessed according to interference power levels of different channels and determine uplink transmission power levels, and independently sense the interference power levels of all N c uplink channels to select the interference power levels lower than a threshold value The smallest channel is used as an uplink access channel, and one power level is selected from the power level set Q to be used as an uplink transmission power level according to a power level selection criterion; Step 2, the active users execute competition access and data transmission in the transmission time slot, each active user randomly selects a preamble sequence from the preamble combination, spreads the transmission data by using the preamble sequence, combines the preamble sequence and the spread data into a frame signal, and transmits the signal frame to the base station through a selected channel at a selected power level; And step 3, the active user receives the access result fed back by the base station in the feedback waiting time slot, the base station receives the uplink signal of the active user, adopts the sequential interference cancellation technology to detect the power level of the received signal, and then detects the preamble sequence carried on each power level