Communication-Aware Integration Method and System for Uplink and Downlink Coexistence Based on NOMA

Abstract

The present invention discloses a communication and sensing integration method and system for uplink and downlink coexistence based on NOMA. The method includes: the base station receives a first communication signal; the downlink user terminal receives a second communication signal; the first communication signal and the second communication signal are decoded respectively, and the corresponding first signal-to-interference-plus-noise ratio and second signal-to-interference-plus-noise ratio are calculated; meanwhile, based on the echo signal, the interference of the base station to sensing and the null hypothesis and alternative hypothesis of the existence of the target echo signal are calculated; the communication outage probability of the uplink user terminal is calculated according to the first signal-to-interference-plus-noise ratio, and the communication outage probability of the downlink user terminal is calculated according to the second signal-to-interference-plus-noise ratio; meanwhile, the sensing probability of the communication and sensing integrated base station is calculated based on the null hypothesis and alternative hypothesis. The communication and sensing integration system for uplink and downlink coexistence proposed by the present invention can simultaneously realize the target sensing and communication functions, and reduce the cross-interference between communication and sensing; it can also serve multiple users simultaneously, improving the system spectrum utilization rate.

Description

Technical Field

[0001] The present invention belongs to the field of communication technologies, and particularly relates to a communication and sensing integrated system for coexistence of uplink and downlink based on NOMA. Background Art

[0002] At present, the new radio of the fifth-generation mobile communication system has been deployed and commercialized, and the future development of the sixth-generation mobile communication system urgently needs to be developed. Emerging industries such as intelligent transportation, telemedicine, and smart home are driving 6G into new areas, and these wonderful visions require strong wireless signal transmission and sensing capabilities, as well as a clever combination of communication and sensing. In addition, it is speculated that the access density of 6G Internet of Things devices will reach 10 million per square kilometer, and the peak data rate will reach 1 Tbps. The addition of a large number of Internet of Things devices to the communication system makes the original spectrum resources unable to meet the communication needs, further accelerating the combination of communication and sensing. Therefore, communication and sensing integration is considered a feasible solution to effectively alleviate this situation. The communication and sensing integrated system uses unified hardware resources to simultaneously complete the functions of communication and sensing, and can also greatly save the hardware cost.

[0003] Currently, the research on integrated communication and sensing systems mainly focuses on the following aspects: Reference 1 (S. Biswas, K. Singh, O. Taghizadeh, and T. Ratnarajah, “Design and analysis of FD MIMO cellular systems in coexistence with MIMO radar,” IEEE Trans. Wireless Commun., vol. 19, no. 7, pp. 4727–4743, Jul. 2020.) proposed a communication and sensing coexistence system, in which the communication base station and the sensing station independently perform their respective functions, which results in mutual interference between communication and sensing and reduces their performance. Reference 2 (F. Liu, C. Masouros, A. Li, H. Sun, and L. Hanzo, “MU-MIMO communications with MIMO radar: From co-existence to joint transmission,” IEEE Trans. Wireless Commun., vol. 17, no. 4, pp. 2755–2770, Apr. 2018) studied the performance of communication and sensing in both communication and sensing coexistence systems and integrated communication and sensing systems respectively, and compared the two. The results show that under the same power consumption, the performance of the integrated communication and sensing system is better than that of the communication and sensing coexistence scheme. Reference 3 (Z. Wang, Y. Liu, X. Mu, Z. Ding and O. A. Dobre, “NOMA Empowered Integrated Sensing and Communication,” IEEE Commun. Lett., vol. 26, no. 3, pp. 677-681, Mar. 2022) and Reference 4 (C. Ouyang, Y. Liu and H. Yang, “On the Performance of Uplink ISAC Systems,” IEEE Commun. Lett., pp. 1-4, May 2022) independently studied the downlink and uplink integrated communication and sensing systems based on NOMA respectively.

[0004] However, the existing communication and sensing coexistence schemes still have the following drawbacks:

[0005] (1) As the communication frequency band increases, the waveforms of communication and sensing in the existing communication and sensing coexistence schemes will generate serious cross-interference in the case of the same frequency, thus reducing the communication performance and sensing performance;

[0006] (2) Most of the existing communication and sensing integration solutions adopt traditional OMA technology, which can only serve a single user at the same time / frequency band / code domain, which is undoubtedly a waste of the increasingly scarce spectrum resources;

[0007] (3) Most of the existing literature separately studies the uplink and downlink communication and sensing integration systems. However, in actual scenarios, the uplink and downlink coexist simultaneously, and the interference of the uplink users to the downlink users cannot be ignored. Summary of the Invention

[0008] To solve the above problems existing in the prior art, the present invention provides a communication and sensing integration method and system based on NOMA for uplink and downlink coexistence. The technical problems to be solved by the present invention are realized through the following technical solutions:

[0009] In a first aspect, the present invention provides a communication and sensing integration system based on NOMA for uplink and downlink coexistence, including a communication and sensing integration base station, an uplink user terminal, and a downlink user terminal; the uplink user terminal includes at least one uplink proximal user and one uplink distal user; the downlink user terminal includes at least one downlink proximal user and one downlink distal user; wherein,

[0010] The communication and sensing integration base station is used to implement communication between the uplink user terminal and the downlink user terminal based on NOMA technology; and is also used to implement target detection and sensing.

[0011] In a second aspect, based on the above communication and sensing integration system, the present invention provides a communication and sensing integration method based on NOMA for uplink and downlink coexistence, including:

[0012] The base station receives a first communication signal and sends a second transmission signal to the downlink user terminal based on NOMA technology; wherein, the first communication signal includes a first transmission signal sent by the uplink user terminal based on NOMA technology and / or an echo signal reflected by the target;

[0013] The downlink user terminal receives a second communication signal; wherein, the second communication signal includes a first transmission signal sent by the uplink user terminal and a second transmission signal sent by the base station;

[0014] The SIC technology is used to decode the first communication signal and the second communication signal at the base station and the downlink user terminal respectively, and calculate the corresponding first signal-to-interference-plus-noise ratio and second signal-to-interference-plus-noise ratio; at the same time, the interference of the base station to sensing and the null hypothesis and alternative hypothesis of the presence of the target echo signal are calculated based on the echo signal; wherein, the first signal-to-interference-plus-noise ratio is the signal-to-interference-plus-noise ratio of each signal at the uplink user, and the second signal-to-interference-plus-noise ratio is the signal-to-interference-plus-noise ratio of each signal at the downlink user;

[0015] Calculate the communication interruption probability of the uplink user terminal according to the first signal-to-interference-plus-noise ratio, and calculate the communication interruption probability of the downlink user terminal according to the second signal-to-interference-plus-noise ratio; meanwhile, calculate the sensing probability of the communication and sensing integrated base station based on the null hypothesis and the alternative hypothesis.

[0016] In an embodiment of the present invention, the first communication signal is expressed as:

[0017]

[0018] where y BS represents the first communication signal, respectively represent the first transmission signals sent by the uplink remote user and the uplink proximal user, and y S represents the second transmission signal sent by the base station; represents the actual channel state information, represents the estimated channel state information, e represents the channel estimation error, and the subscripts SU f 、SU n 、SS respectively represent that the signal is transmitted from the uplink remote user to the base station, from the uplink proximal user to the base station, and the signal transmitted by the base station reaches the base station after being reflected by the target; and all channels are Rayleigh channels, and the cumulative distribution function of the channel gain is expressed as where represents the actual channel state information, d i represents the distance between two nodes, v represents the path loss exponent, respectively represent the hardware impairment coefficients; κ represents the hardware impairment level, represents the transmission power of the uplink remote user, represents the transmission power of the uplink proximal user, P S represents the transmission power of the base station; and respectively represent the interference channels of the first transmission signals sent by the uplink remote user and the uplink proximal user reaching the base station after being reflected by the target; represents a complex Gaussian distribution with mean a and variance b; δ represents the target reflection coefficient; h LI represents the self-interference channel caused by the base station's two antennas simultaneously transmitting and receiving signals; represents the additive white Gaussian noise at the base station.

[0019] In an embodiment of the present invention, the second communication signal is expressed as:

[0020]

[0021]

[0022] where and respectively represent the second communication signals received by the downlink far - end user and the downlink near - end user, represents the actual channel state information, with the subscript SD f 、SD n 、ff, nf, fn, nn respectively represent that the signal is transmitted from the base station to the downlink far - end user, from the base station to the downlink near - end user, from the uplink far - end user to the downlink far - end user, from the uplink near - end user to the downlink far - end user, from the uplink far - end user to the downlink near - end user, from the uplink near - end user to the downlink near - end user, and all channels are Rayleigh channels; respectively represent the hardware impairment coefficients, and respectively represent the interference channels where the signals transmitted by the base station reach the communication users after passing through the target reflection; and respectively represent the additive white Gaussian noise at the downlink far - end user and the near - end user.

[0023] In an embodiment of the present invention, the SIC technology is adopted to decode the first communication signal and the second communication signal at the base station and the downlink user end respectively, and calculate the corresponding first signal - to - interference - plus - noise ratio and second signal - to - interference - plus - noise ratio, including:

[0024] At the base station, first decode the transmission signal s n of the uplink near - end user, and then use the SIC technology to eliminate it, and then decode the transmission signal s f of the uplink far - end user. Then, the first signal - to - interference - plus - noise ratios of each signal at the uplink near - end user and the uplink far - end user at the base station are respectively expressed as:

[0025]

[0026]

[0027] Among them, and respectively represent the first signal - to - interference - plus - noise ratios of the uplink near - end user and the uplink far - end user; γ S 、 respectively represent the transmission signal - to - noise ratios of the base station, the uplink far - end user and the near - end user;

[0028]

[0029]

[0030]

[0031] ρ represents the channel gain, with the subscript SU f, SU n , SS respectively represent that the signal is transmitted from the uplink remote user to the base station, from the uplink proximal user to the base station, and the signal transmitted by the base station reaches the base station through the target transmitter; ε ∈ [0, 1] represents the non-perfect SIC coefficient.

[0032] In an embodiment of the present invention, using the SIC technology to decode the first communication signal and the second communication signal at the base station and the downlink user terminal respectively, and calculating the corresponding first signal-to-interference-plus-noise ratio and second signal-to-interference-plus-noise ratio further includes:

[0033] At the downlink user terminal, first decode the desired signal x of the downlink remote user f , and then use the SIC technology to eliminate it, and then decode the desired signal x of the downlink proximal user n ; then the second signal-to-interference-plus-noise ratios of each signal at the downlink proximal user and the downlink remote user are respectively:

[0034]

[0035]

[0036]

[0037] Among them,

[0038]

[0039]

[0040]

[0041]

[0042]

[0043]

[0044] represents the SINR of the downlink remote user receiving its own desired signal, represents the SINR of the downlink proximal user receiving the signal of the remote user, represents the SINR of the downlink proximal user receiving its own desired signal, a f and a n respectively represent the power allocation coefficients of the downlink remote user and the downlink proximal user, and satisfy a n + a f = 1, a n < a f .

[0045] In one embodiment of the present invention, calculating the interference perceived by the base station based on the echo signal, and the null hypothesis and alternative hypothesis for the presence of the target echo signal include:

[0046]

[0047]

[0048] Wherein, represents the null hypothesis, represents the alternative hypothesis.

[0049] In one embodiment of the present invention, calculating the communication interruption probability of the uplink user terminal according to the first signal-to-interference-plus-noise ratio includes:

[0050] When s n cannot be successfully decoded, the uplink proximal user will experience an interruption, and its interruption probability is expressed as:

[0051]

[0052] Wherein, represents the interruption threshold of signal s n ;

[0053]

[0054] A2 = γ S φ

[0055]

[0056]

[0057]

[0058] erfc(·) represents the complementary error function;

[0059] When s n or s f cannot be successfully decoded, the uplink distal user will experience an interruption, and its interruption probability is expressed as:

[0060]

[0061] Wherein,

[0062]

[0063] B2 = γ S ζ,

[0064]

[0065]

[0066] In one embodiment of the present invention, calculating the communication interruption probability of the downlink user terminal according to the second signal-to-interference-plus-noise ratio includes:

[0067] When x cannot be successfully decoded f the downlink remote user will experience an interruption, and its interruption probability is expressed as:

[0068]

[0069] wherein, represents the interruption threshold of signal x f ;

[0070]

[0071]

[0072]

[0073]

[0074] When x cannot be successfully decoded f or x n the downlink proximal user will experience an interruption, and its interruption probability is expressed as:

[0075]

[0076] wherein, represents the interruption threshold of signal x n ;

[0077]

[0078]

[0079]

[0080] χ = max(χ1, χ2)

[0081]

[0082]

[0083] In one embodiment of the present invention, calculating the sensing probability of the communication and sensing integrated base station based on the null hypothesis and the alternative hypothesis includes:

[0084] Calculate the false alarm probability of the base station according to the following formula:

[0085]

[0086] Calculate the detection probability of the base station according to the following formula:

[0087]

[0088] where ξ is the detection threshold, and Q(·,·) represents the Marcum Q function.

[0089] Advantages of the present invention:

[0090] 1. The communication and sensing integrated system for uplink and downlink coexistence proposed by the present invention is more practical. It can achieve communication functions while performing target sensing, without occupying radar spectrum resources, improving spectrum utilization, reducing cross-interference between the communication system and the radar sensing system, and enhancing communication performance and sensing performance. At the same time, the present invention introduces the NOMA technology into the system, which can serve multiple users simultaneously on the premise of ensuring user service fairness, further improving the spectrum utilization of the system;

[0091] 2. The present invention also considers the influence of actual factors such as hardware impairment, channel estimation error, and imperfect SIC on system performance, which has more practical reference value compared with the traditional ideal situation.

[0092] The following will further elaborate on the present invention in conjunction with the drawings and embodiments. Description of the Drawings

[0093] Figure 1 is a schematic diagram of a communication and sensing integrated system model for uplink and downlink coexistence based on NOMA provided by an embodiment of the present invention;

[0094] Figure 2 is a flowchart of a communication and sensing integrated method for uplink and downlink coexistence based on NOMA provided by an embodiment of the present invention;

[0095] Figure 3 is a schematic diagram showing the variation of the downlink user outage probability with the base station transmission signal-to-noise ratio in the ideal and non-ideal cases;

[0096] Figure 4 is a schematic diagram showing the variation of the uplink user outage probability with the base station transmission SNR in the ideal and non-ideal cases;

[0097] Figure 5 is a schematic diagram showing the variation of the downlink user outage probability with the imperfect SIC parameter;

[0098] Figure 6 is a schematic diagram showing the variation of the uplink user outage probability with hardware impairment and channel estimation error;

[0099] Figure 7It is a schematic diagram of the detection probability of the system varying with the base station transmission SNR. Specific Embodiments

[0100] The following further describes the present invention in detail with reference to specific embodiments, but the implementation manners of the present invention are not limited thereto.

[0101] Embodiment 1

[0102] Please refer to Figure 1 , Figure 1 which is a schematic diagram of a communication and sensing integrated system model for coexistence of uplink and downlink based on NOMA provided by an embodiment of the present invention. It includes: a communication and sensing integrated base station, an uplink user terminal, and a downlink user terminal; the uplink user terminal includes at least one uplink proximal user and one uplink distal user; the downlink user terminal includes at least one downlink proximal user and one downlink distal user; wherein,

[0103] The communication and sensing integrated base station is used to implement communication between the uplink user terminal and the downlink user terminal based on NOMA technology; and is also used to implement target detection and sensing.

[0104] Specifically, in this embodiment, it is considered that the system model includes a communication and sensing integrated base station, an uplink proximal communication user, an uplink distal communication user, a downlink proximal communication user, and a downlink distal communication user. The integrated base station has two antennas, one antenna is used to transmit signals, and the other antenna is used to receive signals, while all users have only one antenna. At the same time, it is considered that all channels are Rayleigh channels, and the cumulative distribution function of the channel gain is expressed as where represents the actual channel state information, d i represents the distance between two nodes, and v represents the path loss exponent.

[0105] Based on the above communication and sensing integrated system, this embodiment also provides a communication and sensing integration method for coexistence of uplink and downlink based on NOMA. Please refer to Figure 2 , Figure 2 which is a flowchart of the communication and sensing integration method for coexistence of uplink and downlink based on NOMA provided by an embodiment of the present invention. It includes:

[0106] Step 1: The base station receives the first communication signal and sends the second transmission signal to the downlink user terminal based on NOMA technology; wherein, the first communication signal includes the first transmission signal sent by the uplink user terminal based on NOMA technology and / or the echo signal reflected by the target.

[0107] Specifically, the uplink user terminal includes an uplink proximal user and an uplink distal user, which respectively send the first transmission signal and Transmit to the integrated communication and sensing base station, establish communication with the base station. Meanwhile, the base station conducts target detection and sensing, and the receiving antenna receives the target echo signal. This echo signal contains the second transmission signal y emitted by the base station itself S The echo after being reflected by the target and the first transmission signal emitted by the uplink user and The echo after being reflected by the target. Therefore, the first communication signal received by the base station can be expressed as:

[0108]

[0109] where y BS represents the first communication signal, respectively represent the first transmission signals sent by the uplink remote user and the uplink proximal user, and y S represents the second transmission signal sent by the base station; represents the actual channel state information, represents the estimated channel state information, represents the channel estimation error, and the subscripts SU f 、SU n 、SS respectively represent that the signal is transmitted from the uplink remote user to the base station, from the uplink proximal user to the base station, and the signal transmitted by the base station reaches the base station after being reflected by the target, and all channels are Rayleigh channels. The cumulative distribution function of the channel gain is expressed as where represents the actual channel state information, d i represents the distance between two nodes, and v represents the path loss exponent; respectively represent the hardware impairment coefficients; κ represents the hardware impairment level, represents the transmission power of the uplink remote user, represents the transmission power of the uplink proximal user, and P S represents the transmission power of the base station; and respectively represent the interference channels when the first transmission signals sent by the uplink remote user and the uplink proximal user reach the base station after being reflected by the target; represents a complex Gaussian distribution with mean a and variance b; δ represents the target reflection coefficient; h LI represents the self-interference channel caused by the simultaneous transmission and reception of signals by two antennas of the base station; represents the additive Gaussian white noise at the base station.

[0110] Step 2: The downlink user terminal receives the second communication signal; where the second communication signal includes the first transmission signal sent by the uplink user terminal and the second transmission signal sent by the base station.

[0111] Specifically, the base station transmits to the downlink users, where P S represents the transmission power of the base station, and x f and x n respectively represent the desired signals of the remote user and the proximal user, and a f and a n respectively represent the power allocation coefficients of the downlink remote user and the proximal user, and satisfy a n +a f = 1, a n < a f . In addition, the downlink users will also receive the transmission signals of the uplink remote user and the transmission signals of the uplink proximal user where s f and respectively represent the transmission signal and power of the remote uplink user, and s n and respectively represent the transmission signal and power of the remote downlink user.

[0112] Therefore, the received second communication signal at the downlink user end, that is, the received signals of the downlink remote user and the proximal user, can be respectively expressed as:

[0113]

[0114]

[0115] where, represents the actual channel state information, represents the estimated channel state information, represents the channel estimation error, respectively represent the hardware impairment coefficients, and the subscripts SD f , SD n , ff, nf, fn, nn respectively represent that the signal is transmitted from the base station to the downlink remote user, the base station to the downlink proximal user, the uplink remote user to the downlink remote user, the uplink proximal user to the downlink remote user, the uplink remote user to the downlink proximal user, the uplink proximal user to the downlink proximal user, and all the channels are Rayleigh channels; and respectively represent the interference channels where the signals transmitted by the base station reach the communication users after passing through the target reflection. and respectively represent the additive white Gaussian noise at the downlink remote user and the proximal user.

[0116] Step 3: Use SIC technology to decode the first communication signal and the second communication signal at the base station and the downlink user end respectively, and calculate the corresponding first signal-to-interference-plus-noise ratio (SINR) and second signal-to-interference-plus-noise ratio; at the same time, calculate the interference perceived by the base station based on the echo signal and the null hypothesis and alternative hypothesis of the existence of the target echo signal; where the first signal-to-interference-plus-noise ratio is the signal-to-interference-plus-noise ratio of each signal at the uplink user, and the second signal-to-interference-plus-noise ratio is the signal-to-interference-plus-noise ratio of each signal at the downlink user.

[0117] Specifically, for uplink signal transmission, in order to ensure the high sensitivity of SIC, it is considered that the transmission power of the uplink proximal user is higher than that of the distal user. Therefore, first decode the transmission signal s of the uplink proximal user n , and then use SIC technology to eliminate it, and then decode the transmission signal s of the uplink distal user f . Then the first signal-to-interference-plus-noise ratios of each signal at the base station for the uplink proximal user and the uplink distal user are respectively expressed as:

[0118]

[0119]

[0120] Among them, and respectively represent the first signal-to-interference-plus-noise ratios of the uplink proximal user and the uplink distal user; γ S , respectively represent the transmission signal-to-noise ratios of the base station, the uplink distal user and the proximal user;

[0121]

[0122]

[0123]

[0124] ρ represents the channel gain, and the subscripts SU f , SU n , SS respectively represent that the signal is transmitted from the uplink distal user to the base station, from the uplink proximal user to the base station, and the signal transmitted by the base station reaches the base station through the target transmitter; ε∈[0,1] represents the non-perfect SIC coefficient.

[0125] Furthermore, according to the NOMA scheme, for the downlink distal user, only decode its own desired signal x f , for the downlink proximal user, first decode the desired signal x of the distal user f , and then use SIC technology to eliminate it, and then decode its own desired signal x n . Therefore, the second signal-to-interference-plus-noise ratios of each signal at the downlink proximal user and the downlink distal user are respectively:

[0126]

[0127]

[0128]

[0129] Among them,

[0130]

[0131]

[0132]

[0133]

[0134]

[0135]

[0136] Among them, represents the SINR for the downlink far - end user to receive its desired signal, represents the SINR for the downlink near - end user to receive the far - end user's signal, represents the SINR for the downlink near - end user to receive its desired signal, γ S =P S / N0, respectively represent the transmission signal - to - noise ratios of the base station, the uplink far - end and near - end users, and ε ∈ [0, 1] represents the non - perfect SIC coefficient.

[0137] For sensing, the received signal at the base station can be divided into the signal without the target echo signal and the signal with the target echo signal. Therefore, the null hypothesis and the alternative hypothesis are respectively expressed as:

[0138]

[0139]

[0140] Step 4: Calculate the communication outage probability of the uplink user terminal according to the first signal - to - interference - plus - noise ratio, and calculate the communication outage probability of the downlink user terminal according to the second signal - to - interference - plus - noise ratio; meanwhile, calculate the sensing probability of the communication - sensing integrated base station based on the null hypothesis and the alternative hypothesis.

[0141] First, calculate the communication outage probability of the uplink user terminal, specifically as follows:

[0142] When the uplink near - end user cannot successfully decode s nWhen the proximal user experiences an interruption, the interruption probability is expressed as:

[0143]

[0144] where, represents the interruption threshold of signal s n ;

[0145]

[0146] A2 = γ S φ

[0147]

[0148]

[0149]

[0150] erfc(·) represents the complementary error function.

[0151] When the uplink remote user fails to successfully decode s n or s f , the remote user experiences an interruption, and the interruption probability is expressed as

[0152]

[0153] where,

[0154]

[0155] B2 = γ S ζ,

[0156]

[0157]

[0158] Then, calculate the communication interruption probability at the downlink user side as follows:

[0159] For the downlink user, when the remote user fails to successfully decode x f , the remote user experiences an interruption, and the interruption probability is expressed as:

[0160]

[0161] where, represents the interruption threshold of signal x f ;

[0162]

[0163]

[0164]

[0165]

[0166] When x cannot be successfully decoded f or x n a downlink near-end user will experience an interruption, and the interruption probability is expressed as:

[0167]

[0168] where represents the interruption threshold of signal x n ;

[0169]

[0170]

[0171]

[0172] χ = max(χ1, χ2)

[0173]

[0174]

[0175] For sensing, according to the null hypothesis and the alternative hypothesis, it can be obtained that and the base station received powers in the

[0176]

[0177]

[0178] cases are all random variables following a non-central chi-square distribution with five degrees of freedom. Therefore, the false alarm probability and the detection probability can be expressed as where ξ is the detection threshold, and Q(·, ·) represents the Marcum Q function.

[0179] According to the calculated interruption probability, false alarm probability, and detection probability, the communication performance and sensing performance of the system can be reflected.

[0180] The communication and sensing integration system for uplink and downlink coexistence proposed by the present invention is more practical. While the base station of this system performs target sensing, it also realizes the communication function, that is, the uplink users transmit signals to the base station, and at the same time the base station transmits signals to the downlink users, without occupying the radar spectrum resources, improving the spectrum utilization rate and reducing the cross-interference between the communication system and the radar system. At the same time, the present invention introduces the NOMA technology into the system, which can serve multiple users simultaneously on the premise of ensuring the fairness of user services, further improving the spectrum utilization rate of the system. For the uplink, the proposed NOMA scheme can improve the SIC ability and the decoding ability of the proximal users. For the downlink, the NOMA scheme can improve the fairness of user services. For sensing, it can reduce the self-interference caused by multiple transmissions of communication signals.

[0181] Furthermore, the present invention also considers the impacts of actual factors such as hardware impairments, channel estimation errors, and imperfect SIC on the system performance. Compared with the traditional ideal situation, it has more practical reference value.

[0182] In addition, the parameters of the non-ideal factors considered in the present invention are converted into the parameters under the ideal state, and the system model is then converted into the system under the ideal situation. However, the system model under the ideal situation cannot be converted into the non-ideal situation of the present invention, further indicating that the system scheme proposed by the present invention has more practical reference value.

[0183] Embodiment 2

[0184] Next, the beneficial effects of the present invention will be verified and illustrated through simulation experiments.

[0185] 1. Simulation conditions:

[0186] Adopt the system model shown in Embodiment 1 above Figure 1 where the distance normalization parameter d ST = d TS = 0.5, d fn = d nf = 0.95, the SNR threshold parameter the power allocation parameter a f = 0.8, a n = 0.2, and the other parameters are v = 2, β LI = 0.1, δ = 0.9, N0 = 1, α = 1, Ρ fa = 10 -6 .

[0187] 2. Simulation content:

[0188] Experiment 1

[0189] Using the system and method of the present invention ( Figure 3 and 4 the ISAC NOMA in Figure 3 and 4 ), the downlink user outage probability as a function of the base station transmission signal-to-noise ratio (SNR) and the uplink user outage probability as a function of the base station transmission SNR are simulated for the ideal case (κ = σ = ε = 0) and the non-ideal case (κ = σ = ε = 0.1), respectively. To demonstrate the superiority of the proposed NOMA-based communication and sensing integration scheme, the outage performance of the traditional communication and sensing integration scheme (

[0190] Experiment 2

[0191] The outage probability of the downlink users as a function of the non-perfect SIC parameter, the outage probability of the uplink users as a function of the hardware impairment and channel estimation error, and the detection probability of the system as a function of the base station transmission SNR are simulated.

[0192] 3. Simulation Results and Analysis:

[0193] Please refer to Figure 3 , Figure 3 which shows the schematic diagram of the downlink user outage probability as a function of the base station transmission SNR for the ideal case (κ = σ = ε = 0) and the non-ideal case (κ = σ = ε = 0.1). Among them, Among them, in the low and medium SNR cases, the outage performance of the downlink communication users improves with the increase of the base station transmission power. However, due to the effects of hardware impairment, channel estimation error, non-perfect SIC, and the interference of the uplink users to the downlink users, there is a lower bound of the outage probability in the high SNR region. In addition, compared with the traditional communication and sensing integration scheme, the proposed NOMA-based communication and sensing integration scheme can improve the outage performance of the downlink communication users.

[0194] Figure 4 which shows the schematic diagram of the uplink user outage probability as a function of the base station transmission SNR for the ideal case (κ = σ = ε = 0) and the non-ideal case (κ = σ = ε = 0.1). Among them, Since the transmission power of the remote uplink users is low and the channel conditions are poor, their outage probability is higher than that of the proximal users. Hardware impairment, channel estimation error, and non-perfect SIC also reduce the outage performance of the uplink users. If the target is not within the sensing range of the base station, the interference to the communication only includes self-interference, and if a target appears, the target echo will also generate additional interference to the decoding of the communication signal.

[0195] Figure 5 which shows the schematic diagram of the outage probability of the downlink users as a function of the non-perfect SIC parameter, where PS = 35 dBm, It can be seen from the figure that the outage probability of the downlink far - end user is independent of the non - perfect SIC parameter. This is because for downlink users, the decoding of the far - end user's signal is independent of the SIC performance. For the near - end user, the outage probability increases with the degradation of SIC performance.

[0196] Figure 6 Fig. shows the schematic diagram of the uplink user outage probability varying with hardware impairment and channel estimation error, where it can be seen that channel estimation error, hardware impairment, and non - perfect SIC all affect the outage performance of users. Benefiting from high transmit power and good channel conditions, the outage performance of near - end communication users is better than that of far - end users. For the uplink, since SIC is not adopted for signal decoding of near - end communication users, changing the non - perfect SIC parameter will not affect their outage performance. From Figure 6 the distribution region, it can be seen that compared with hardware impairment, the outage probability of communication users in the considered communication - sensing integrated NOMA system is more sensitive to channel estimation error.

[0197] Figure 7 Fig. shows the schematic diagram of the detection probability of the system varying with the base - station transmission SNR, where Obviously, with the increase of the base - station transmission power, the detection performance is improved. From Figure 7 it can be seen that both hardware impairment and channel estimation error affect the sensing ability of the base station. Compared with channel estimation error, the impact of hardware impairment on the system detection performance is weaker. In addition, it can also be observed that under the same detection probability, the traditional communication - sensing integrated system consumes more resources than the NOMA - based communication - sensing integrated system proposed in this scheme. The simulation results further confirm the superiority of the NOMA - based communication - sensing integrated scheme in sensing.

[0198] The above content is a further detailed description of the present invention in combination with specific preferred embodiments. It cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention belongs, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should all be regarded as belonging to the protection scope of the present invention.

Claims

1. A communication and sensing integration method for coexistence of uplink and downlink based on NOMA, characterized in that, Including: The base station receives the first communication signal and sends the second transmission signal to the downlink user terminal based on the NOMA technology; wherein, the first communication signal includes the first transmission signal sent by the uplink user terminal based on the NOMA technology and / or the echo signal reflected by the target; the expression of the first communication signal is: where y BS represents the first communication signal, respectively represent the first transmission signals sent by the uplink far - end user and the uplink near - end user, and y S represents the second transmission signal sent by the base station; represents the actual channel state information, represents the estimated channel state information, e represents the channel estimation error, and the subscripts SU f 、SU n 、SS respectively represent that the signal is transmitted from the uplink far - end user to the base station, from the uplink near - end user to the base station, and the signal transmitted by the base station reaches the base station after reflection by the target. And all channels are Rayleigh channels, and the cumulative distribution function of the channel gain is expressed as where represents the actual channel state information, d i represents the distance between two nodes, v represents the path loss exponent, respectively represent the hardware impairment coefficients, κ represents the hardware impairment level, P Uf represents the transmission power of the uplink far - end user, represents the transmission power of the uplink near - end user, and P S represents the transmission power of the base station; respectively represent the interference channels where the first transmission signals sent by the uplink far - end user and the uplink near - end user reach the base station after reflection by the target; represents a complex Gaussian distribution with mean a and variance b; δ represents the target reflection coefficient; h LI represents the self - interference channel caused by the base station's two antennas simultaneously transmitting and receiving signals; represents the additive white Gaussian noise at the base station; The downlink user terminal receives the second communication signal; wherein, the second communication signal includes the first transmission signal sent by the uplink user terminal and the second transmission signal sent by the base station; the expression of the second communication signal is: Among them, and respectively represent the second communication signals received by the downlink far - end user and the downlink near - end user, represents the actual channel state information, with the subscript SD f , SD n , ff, nf, fn, nn respectively represent that the signal is transmitted from the base station to the downlink far - end user, from the base station to the downlink near - end user, from the uplink far - end user to the downlink far - end user, from the uplink near - end user to the downlink far - end user, from the uplink far - end user to the downlink near - end user, from the uplink near - end user to the downlink near - end user, and all channels are Rayleigh channels; respectively represent the hardware impairment coefficients, and respectively represent the interference channels where the signals transmitted by the base station reach the communication users after target reflection; and respectively represent the additive white Gaussian noise at the downlink far - end user and the downlink near - end user. Using the SIC technology to decode the first communication signal and the second communication signal at the base station and the downlink user terminal respectively, and calculating the corresponding first signal-to-interference-plus-noise ratio and second signal-to-interference-plus-noise ratio; at the same time, calculating the interference perceived by the base station based on the echo signal and the null hypothesis and alternative hypothesis of the existence of the target echo signal; wherein, the first signal-to-interference-plus-noise ratio is the signal-to-interference-plus-noise ratio of each signal at the uplink user, and the second signal-to-interference-plus-noise ratio is the signal-to-interference-plus-noise ratio of each signal at the downlink user; Calculating the communication outage probability of the uplink user terminal according to the first signal-to-interference-plus-noise ratio, and calculating the communication outage probability of the downlink user terminal according to the second signal-to-interference-plus-noise ratio; at the same time, calculating the sensing probability of the communication-sensing integrated base station based on the null hypothesis and alternative hypothesis.

2. The communication and sensing integration method for coexistence of uplink and downlink based on NOMA according to claim 1, characterized in that, Using the SIC technology to decode the first communication signal and the second communication signal at the base station and the downlink user terminal respectively, and calculating the corresponding first signal-to-interference-plus-noise ratio and second signal-to-interference-plus-noise ratio includes: At the base station, first decode the transmission signal s of the uplink proximal user n , then use SIC technology to eliminate it, and then decode the transmission signal s of the uplink distal user f , then the first signal-to-interference-plus-noise ratios of the signals at the uplink proximal user and the uplink distal user at the base station are respectively expressed as: Among them, and respectively represent the SINR of the uplink proximal user and the uplink distal user; γ S 、 respectively represent the transmission signal-to-noise ratios of the base station, the uplink distal user and the proximal user; $\rho$ represents the channel gain, with the subscript SU f , SU n , SS respectively represent that the signal is transmitted from the uplink far - end user to the base station, from the uplink near - end user to the base station, and the signal transmitted by the base station reaches the base station through the target transmitter; $\varepsilon\in[0,1]$ represents the non - perfect SIC coefficient.

3. The communication and sensing integration method for coexistence of uplink and downlink based on NOMA according to claim 2, characterized in that, Using the SIC technology to decode the first communication signal and the second communication signal at the base station and the downlink user terminal respectively, and calculating the corresponding first signal-to-interference-plus-noise ratio and second signal-to-interference-plus-noise ratio further includes: At the downlink user side, first decode the desired signal x of the downlink remote user f , then use SIC technology to eliminate it, and then decode the desired signal x of the downlink proximal user n ; then the second signal-to-interference-plus-noise ratios of the signals at the downlink proximal user and the downlink remote user are respectively: Wherein, Indicates the SINR for the downlink remote user to receive its desired signal, Indicates the SINR for the downlink proximal user to receive the signal of the remote user, Indicates the SINR for the downlink proximal user to receive its desired signal, a f and a n respectively represent the power allocation coefficients of the downlink remote user and the downlink proximal user, and satisfy a n + a f = 1, a n < a f .

4. The communication and sensing integration method for coexistence of uplink and downlink based on NOMA according to claim 3, characterized in that, Calculating the interference perceived by the base station based on the echo signal and the null hypothesis and alternative hypothesis of the existence of the target echo signal includes: Among them, represents the null hypothesis, represents the alternative hypothesis.

5. The communication and sensing integration method for coexistence of uplink and downlink based on NOMA according to claim 4, characterized in that, Calculating the communication outage probability of the uplink user terminal according to the first signal-to-interference-plus-noise ratio includes: When s cannot be successfully decoded n the uplink proximal user will experience an interruption, and its interruption probability is expressed as: where β represents the channel parameter, represents the signal s n interruption threshold; erfc(·) represents the complementary error function; When s cannot be successfully decoded n or s f the uplink remote user will experience an interruption, and its interruption probability is expressed as: Wherein, 6. The communication and sensing integration method for coexistence of uplink and downlink based on NOMA according to claim 5, wherein, Calculating the communication outage probability of the downlink user terminal according to the second signal-to-interference-plus-noise ratio includes: When x cannot be successfully decoded f downlink remote users will experience interruptions, and the interruption probability is expressed as: Among them, represents the interruption threshold of signal x f ; When x cannot be successfully decoded f or x n a downlink near-end user will experience an interruption, and its interruption probability is expressed as: Among them, represents the interruption threshold of signal x n ; 7. The communication and sensing integration method for coexistence of uplink and downlink based on NOMA according to claim 6, wherein, Calculating the sensing probability of the communication-sensing integrated base station based on the null hypothesis and alternative hypothesis includes: Calculating the false alarm probability of the base station according to the following formula: Calculating the detection probability of the base station according to the following formula: wherein, ξ is the detection threshold, and Q(·,·) represents the Marcum Q function.

8. A communication and sensing integration system for coexistence of uplink and downlink based on NOMA, which is used to implement the method according to any one of claims 1-7, wherein, The system includes a communication-sensing integrated base station, an uplink user terminal and a downlink user terminal; the uplink user terminal includes at least one uplink proximal user and one uplink distal user; the downlink user terminal includes at least one downlink proximal user and one downlink distal user; wherein, The communication-sensing integrated base station is used to realize the communication between the uplink user terminal and the downlink user terminal based on the NOMA technology; and is also used to realize target detection and sensing.

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