A RIS-Assisted Channel Estimation Method for De-Cellular Massive MIMO Symbiotic Communication

Abstract

The present invention relates to the field of wireless communication technologies, and particularly to a RIS-assisted co-cellular massive MIMO coexisting communication channel estimation method, including: deploying M access points (APs), K RISs, and K single-antenna users in a co-cellular massive MIMO network; in the uplink pilot transmission phase, all users simultaneously send pilot and data signals to all APs, and the data signals sent in each time slot are the same; the RIS also sends pilots simultaneously, and uses a binary phase shift keying method for simple processing, allowing the RIS to successively send pilots with two symbols of "+1" and "-1" to the APs. After each AP receives the signals from the direct link and the indirect link, a simple calculation process is performed on the signals received in the previous time slot and the next time slot, and then channel estimation is performed on both of them respectively. The present invention uses a smaller sequence to obtain better channel conditions, reduces the time slot overhead, and has low mean square error and low complexity.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular, to a RIS-assisted cellular-free massive MIMO coexisting communication channel estimation method. Background Art

[0002] With the advent of 5G, the number of wireless communication devices has increased explosively, and the communication industry's demand for wireless spectrum has become increasingly urgent. To solve the problem of scarce spectrum resources, new changes are needed in wireless communication systems after 5G. First, the cellular-free massive MIMO architecture can effectively improve the spectrum efficiency without increasing power and bandwidth resources, and is currently considered to be a key architecture for mobile communication in the post-5G era; second, coexisting communication can take into account the advantages of traditional cognitive radio and emerging passive ambient backscatter communication at the same time, and achieve spectrum-efficient communication, which is a promising transmission technology. Then, RIS is a two-dimensional metasurface composed of a large number of reconfigurable reflecting elements. These reflecting elements can independently adjust the phase shift, amplitude, frequency, and polarization mode of the incident signal, establish a favorable line-of-sight link between the transmitter and the receiver, improve the communication transmission quality, and enhance the communication security, etc. As the most promising network architecture and transmission technology for mobile communication in the post-5G era, they will naturally be integrated with each other. However, there is still little work in this area at present, especially for the channel estimation of joint pilot transmission by users and RIS, and there is a lack of an implementable method. Summary of the Invention

[0003] The purpose of the present invention is to solve the deficiencies in the prior art, and to propose a RIS-assisted cellular-free massive MIMO coexisting communication channel estimation method, which uses a smaller sequence to obtain better channel conditions, reduces the time slot overhead, and has low mean square error and low complexity.

[0004] To achieve the above purpose, the present invention adopts the following technical solutions:

[0005] A RIS-assisted cellular-free massive MIMO coexisting communication channel estimation method, the specific steps are as follows:

[0006] Step 101: Arrange M access points AP, K RISs, and K single-antenna users in the cellular-free massive MIMO coexisting communication network system, where the number of elements on each RIS is N; all access points AP are connected to the same central processing unit and are controlled by the central processing unit; the channel between the access point AP and the user is called the direct link channel, and the channel from the access point AP to the RIS and then to the user is called the indirect link channel;

[0007] Step 102: In the uplink pilot transmission phase, all users simultaneously send pilot and data signals to all access points AP, and the L - 1 data signals sent in each time slot are the same;

[0008] Step 103: RIS also sends pilots simultaneously, and uses binary phase - shift keying for simple processing, enabling RIS to successively send pilots with two symbols, namely "+1" and "-1", to access point AP;

[0009] Step 104: After each access point AP receives signals from RIS and users, it performs a simple calculation on the signals received in the previous time slot and the subsequent time slot. The processed signals are respectively signals that only contain the direct - link channel and signals that only contain the indirect - link channel;

[0010] Step 105: Use the linear minimum mean - square error channel estimation method MMSE to estimate the direct - link channel and the indirect - link channel respectively.

[0011] Preferably, in Step 101, both the access point AP and RIS transmit information to the central processing unit CPU through the fronthaul link. It is assumed in the present invention that the direct - link channel and the indirect - link channel are not correlated.

[0012] Preferably, in Step 102, the signal received by the m - th access point AP from the direct link is:

[0013]

[0014] where P i is the transmission power of the i - th user, is the pilot signal sent by the i - th user and s l (n) is the l - th data signal in the n - th time slot. Each time slot has 1 pilot signal and L - 1 data signals. z k1 is the additive white Gaussian noise, which follows a normal distribution with a mean of 0 and a variance of σ 2 I N where σ 2 is the noise power, f mi is the direct - link channel between the m - th access point AP and the i - th user, which follows a normal distribution with a mean of 0 and a variance of β mi where β mi represents the large - scale fading of the direct - link channel between the m - th access point AP and the i - th user, and is related to shadow fading and path loss.

[0015] Preferably, in Step 103, the signal received by the m - th access point AP from the indirect link is:

[0016]

[0017] where is the indirect link channel between the m-th access point AP and the i-th user, which follows a normal distribution with a mean of 0 and a variance of R mi , where G mi is the channel between the i-th RIS and the m-th access point AP, h i is the channel between the i-th user and the i-th RIS, V i is the phase shift matrix of the i-th RIS, c i ={1, -1}, when the RIS sends a pilot with the symbol "+1", c i =1, when the RIS sends a pilot with the symbol "-1", c i =-1, z k2 is additive white Gaussian noise.

[0018] Preferably, in step 104, the signals received by the m-th access point AP from the direct link and the indirect link in the previous time slot are expressed as:

[0019]

[0020] The signals received by the m-th access point AP from the direct link and the indirect link in the next time slot are expressed as:

[0021]

[0022] where z k3 and z k4 are the additive white Gaussian noise in the previous time slot and the next time slot respectively;

[0023] The access point AP decomposes the signals into signals containing only the direct link channel and signals containing only the indirect link channel through operations and After processing, because the data sent by the user is the same in each time slot, the obtained results are respectively:

[0024]

[0025]

[0026] where z represents the additive white Gaussian noise in the direct link channel after signal processing, and q represents the additive white Gaussian noise in the indirect link channel after signal processing.

[0027] Preferably, in step 105, the minimum mean square error MMSE is used for channel estimation. At this time, the data signal in the direct link is regarded as an interference term. The specific steps are as follows:

[0028] The m-th access point AP places it on the conjugate pilot signal of the k-th user to obtain:

[0029]

[0030]

[0031] Thus, the minimum mean square error MMSE estimate of the direct link channel is obtained:

[0032]

[0033] where is the direct link channel estimate between the m-th access point AP and the k-th user, which follows a normal distribution with a mean of 0 and a variance of . c mlk is expressed as:

[0034]

[0035] where P k is the transmit power of the k-th user, and β mk represents the large-scale fading of the direct link channel between the m-th access point AP and the k-th user, which is related to shadow fading and path loss. The direct link channel estimation error where follows a normal distribution with a mean of 0 and a variance of C mlk . Among them, C mlk =β mlk -P k β mlk c mlk β mlk ;

[0036] The minimum mean square error MMSE estimate of the indirect link channel:

[0037]

[0038]

[0039] where P k is the transmit power of the k-th user, and R mk represents the large-scale fading of the indirect link channel between the m-th access point AP and the k-th user, which is related to shadow fading and path loss. The indirect link channel estimation error where follows a normal distribution with a mean of 0 and a variance of C mdk . Among them, C mdk =R mdk -P k Rmdk c mdk R mdk 。

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. In the present invention, the user and the RIS jointly transmit pilots for channel estimation, reducing the mean square error and improving the accuracy of channel estimation.

[0042] 2. The channel estimation of the present invention is only performed locally at the access point AP, so there is no need to transmit information to the central processing unit, reducing the pressure on the fronthaul link.

[0043] 3. In the present invention, the user simultaneously transmits pilot and data signals, reducing the slot overhead. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flowchart of the present invention;

[0045] Figure 2 is a schematic diagram of the network architecture in the present invention;

[0046] Figure 3 is a schematic diagram of the uplink transmission scheme in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings, so that those skilled in the art can better understand the advantages and features of the present invention, and thus more clearly define the protection scope of the present invention. The embodiments described in the present invention are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0048] Referring to Figures 1 - 3 , a RIS-assisted de-cellularized massive MIMO coexisting communication channel estimation method, the specific steps are as follows:

[0049] Step 101: Deploy M access points AP, K RISs, and K single-antenna users in the de-cellularized massive MIMO coexisting communication network system, where the number of elements on each RIS is N; all access points AP are connected to the same central processing unit and controlled by the central processing unit; the channel between the access point AP and the user is called the direct link channel, and the channel from the access point AP to the RIS and then to the user is called the indirect link channel;

[0050] Step 102: In the uplink pilot transmission phase, all users simultaneously send pilot and data signals to all access points AP, and the L-1 data signals sent in each time slot are the same;

[0051] Step 103: The RIS also sends pilots simultaneously and performs simple processing using binary phase shift keying, allowing the RIS to successively send pilots with two symbols of "+1" and "-1" to the access point AP;

[0052] Step 104: After each access point AP receives the signals from the RIS and the users, it performs a simple calculation on the signals received in the previous time slot and the next time slot. The processed signals are the signals containing only the direct link channel and the signals containing only the indirect link channel respectively;

[0053] Step 105: Use the linear minimum mean square error channel estimation method MMSE to estimate the direct link channel and the indirect link channel respectively.

[0054] The network architecture of the cell-free massive MIMO coexisting communication system in this embodiment is as Figure 2 shown. The illustrated scenario includes M access points AP, 1 central processing unit, K RISs, and K users. The user terminal has a single antenna, each access point AP has N antennas, each RIS has N elements, and the central processing unit is connected to the access point AP through a fronthaul link. The entire system consists of an access point AP201, a central processing unit 202, a user terminal 203, a fronthaul link 204, and a RIS205. Among them, the access point AP201 is mainly responsible for receiving and transmitting data; the central processing unit 202 is mainly responsible for baseband signal processing, user processing unit, and switching processing unit, etc.; the user terminal 203 is the device for users to receive and transmit data; the fronthaul link 204 is mainly responsible for data transmission between the access point and the central processing unit; the RIS205 is mainly responsible for modulating and transmitting the received signals.

[0055] Specifically, for the direct link signal:

[0056] In the uplink pilot transmission phase, as Figure 3 shown, all users simultaneously send pilot and data signals to all access points AP. The signal received by the m-th access point AP from the direct link is:

[0057]

[0058] where P i is the transmission power of the i-th user, is the pilot signal transmitted by the i-th user and s l(n) is the l-th data signal in the n-th time slot. Each time slot has 1 pilot signal and L - 1 data signals, z k1 is additive white Gaussian noise, which follows a normal distribution with a mean of 0 and a variance of σ 2 I N where σ 2 is the noise power, f mi is the direct link channel between the m-th access point AP and the i-th user, which follows a normal distribution with a mean of 0 and a variance of β mi where β mi represents the large-scale fading of the direct link channel between the m-th access point AP and the i-th user, and is related to shadow fading and path loss.

[0059] Specifically, the indirect link signal:

[0060] The RIS successively sends pilots with two symbols of "+1" and "-1" to the access point AP. The signal received by the m-th access point AP from the indirect link is:

[0061]

[0062] where is the indirect link channel between the m-th access point AP and the i-th user, which follows a normal distribution with a mean of 0 and a variance of R mi where G mi is the channel between the i-th RIS and the m-th access point AP, h i is the channel between the i-th user and the i-th RIS, V i is the phase shift matrix of the i-th RIS, c i = {1, -1}. When the RIS sends a pilot with the symbol "+1", c i = 1. When the RIS sends a pilot with the symbol "-1", c i = -1, z k2 is additive white Gaussian noise.

[0063] Specifically, the access point AP performs a simple processing on the signals received in the previous time slot and the next time slot.

[0064] The signals received by the m-th access point AP from the direct link and the indirect link in the previous time slot are expressed as:

[0065]

[0066] The signals received by the m-th access point AP from the direct link and the indirect link in the next time slot are expressed as:

[0067]

[0068] where z k3 and z k4 are the additive white Gaussian noise of the previous time slot and the next time slot respectively.

[0069] The access point AP can decompose the signal into a signal containing only the direct link channel and a signal containing only the indirect link channel through operations and After processing. Since the data sent by the user in each time slot is the same, the obtained results are respectively:

[0070]

[0071]

[0072] where z represents the additive white Gaussian noise in the direct link channel after signal processing, and q represents the additive white Gaussian noise in the indirect link channel after signal processing.

[0073] Specifically, for the direct link channel estimation:

[0074] The m-th access point AP places it on the conjugate pilot signal to obtain:

[0075]

[0076] Thus, the minimum mean square error MMSE estimation of the direct link channel is obtained:

[0077]

[0078] where is the direct link channel estimation between the m-th access point AP and the k-th user, which follows a normal distribution with a mean of 0 and a variance of , and c mlk is expressed as:

[0079]

[0080] where P k is the transmission power of the k-th user, and β mk represents the large-scale fading of the direct link channel between the m-th access point AP and the k-th user, and is related to the shadow fading and path loss. The direct link channel estimation error where follows a normal distribution with a mean of 0 and a variance of C mlk , where C mlk =β mlk -P k β mlk c mlk β mlk。

[0081] Specifically, for the indirect link channel estimation:

[0082] The m-th access point AP places it on the conjugate pilot signal to obtain:

[0083]

[0084] Thus, the minimum mean square error (MMSE) estimation of the indirect link channel is obtained:

[0085]

[0086]

[0087] where P k is the transmit power of the k-th user, and R mk represents the large-scale fading of the indirect link channel between the m-th access point AP and the k-th user, and is related to the shadow fading and path loss. Assume the indirect link channel estimation error where follows a normal distribution with a mean of 0 and a variance of C mdk , where C mdk = R mdk - P k R mdk c mdk R mdk 。

[0088] The descriptions and practices disclosed in the present invention are easy to think about and understand for ordinary technicians in the technical field. Without departing from the principles of the present invention, several improvements and refinements can be made. Therefore, the modifications or improvements made without deviating from the spirit of the present invention should also be regarded as within the protection scope of the present invention.

Claims

1. A RIS-assisted co-cellular massive MIMO coexistence communication channel estimation method, characterized in that The specific steps are as follows: Step 101: Deploy M access points (APs), K reconfigurable intelligent surfaces (RISs), and K single-antenna users in the cellular massive MIMO coexisting communication network system. Here, the number of elements on each RIS is N; all APs are connected to the same central processing unit and controlled by the central processing unit; the channel between the AP and the user is called the direct link channel, and the channel from the AP to the RIS and then to the user is called the indirect link channel; Step 102: In the uplink pilot transmission phase, all users simultaneously send pilot and data signals to all APs, and the L - 1 data signals sent in each time slot are the same; Step 103: The RIS also sends pilots simultaneously and performs simple processing using the binary phase shift keying method, enabling the RIS to successively send pilots with two symbols, namely "+1" and "-1", to the APs; Step 104: After each AP receives the signals from the RIS and the users, it performs a simple calculation on the signals received in the previous time slot and the next time slot. The processed signals are respectively the signals containing only the direct link channel and the signals containing only the indirect link channel; Step 105: Use the linear minimum mean square error (MMSE) channel estimation method to estimate the direct link channel and the indirect link channel respectively.

2. The RIS-assisted co-cellular massive MIMO symbiotic communication channel estimation method according to claim 1, wherein, In Step 101, information is transmitted between the APs, RISs, and the central processing unit (CPU) through the fronthaul link.

3. A RIS-assisted co-cellular massive MIMO coexistence communication channel estimation method according to claim 1, characterized in that, In Step 102, the signal received by the m-th AP from the direct link is: where \(P\) i is the transmit power of the \(i\)-th user, is the pilot signal sent by the \(i\)-th user and \(s\) l (\(n\)) is the \(l\)-th data signal in the \(n\)-th time slot. Each time slot has 1 pilot signal and \(L - 1\) data signals, \(z\) k1 is additive white Gaussian noise, following a normal distribution with mean 0 and variance \(\sigma\) 2 \(I\) N where \(\sigma\) 2 is the noise power, \(f\) mi is the direct link channel between the \(m\)-th access point AP and the \(i\)-th user, following a normal distribution with mean 0 and variance \(\beta\) mi where \(\beta\) mi represents the large-scale fading of the direct link channel between the \(m\)-th access point AP and the \(i\)-th user and is related to shadow fading and path loss.

4. A RIS-assisted co-cellular massive MIMO coexistence communication channel estimation method according to claim 3, characterized in that In Step 103, the signal received by the m-th AP from the indirect link is: Among them is the indirect link channel between the m-th access point AP and the i-th user, which follows a normal distribution with a mean of 0 and a variance of R mi where G mi is the channel between the i-th RIS and the m-th access point AP, h i is the channel between the i-th user and the i-th RIS, V i is the phase shift matrix of the i-th RIS, c i ={1, -1}, when the RIS sends a pilot with a "+1" symbol, c i =1, when the RIS sends a pilot with a "-1" symbol, c i =-1, z k2 is additive white Gaussian noise.

5. A RIS-assisted co-channel estimation method for de-cellularized massive MIMO symbiotic communication according to claim 4, characterized in that, In Step 104, the signals received by the m-th AP from the direct link and the indirect link in the previous time slot are expressed as: The signals received by the m-th AP from the direct link and the indirect link in the next time slot are expressed as: where z k3 and z k4 are the additive white Gaussian noise of the previous time slot and the next time slot respectively; The AP performs the operation and After processing, the signal is decomposed into a signal containing only the direct link channel and a signal containing only the indirect link channel. Since the data sent by the user in each time slot is the same, the obtained results are respectively: where z represents the additive white Gaussian noise in the direct link channel after signal processing, and q represents the additive white Gaussian noise in the indirect link channel after signal processing.

6. A RIS-assisted co-cellular massive MIMO coexistence communication channel estimation method according to claim 5, characterized in that In Step 105, the minimum mean square error (MMSE) is used for channel estimation. At this time, the data signal in the direct link is regarded as an interference term. The specific steps are as follows: The m-th access point AP places it on the conjugate pilot signal of the k-th user to obtain: Thus, the MMSE estimation of the direct link channel is obtained: where is the direct link channel estimation between the m-th access point AP and the k-th user, subject to a normal distribution with a mean of 0 and a variance of , and c mlk is expressed as: where P k is the transmit power of the k-th user, and β mk represents the large-scale fading of the direct link channel between the m-th access point AP and the k-th user, and is related to shadow fading and path loss. The direct link channel estimation error is set as where obeys a normal distribution with a mean of 0 and a variance of C mlk , where C mlk = β mlk - P k β mlk c mlk β mlk ; The MMSE estimation of the indirect link channel: where P k is the transmission power of the k-th user, and R mk represents the large-scale fading of the indirect link channel between the m-th access point AP and the k-th user, and is related to shadow fading and path loss. The indirect link channel estimation error is set where obeys a normal distribution with a mean of 0 and a variance of C mdk , where C mdk = R mdk - P k R mdk c mdk R mdk .

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