A localization method with over-the-air computation

Abstract

The invention is related to a computer implemented method for user localization in wireless communication by utilizing over-the-air computation (OAC).

Description

[0001] A LOCALIZATION METHOD WITH OVER-THE-AIR COMPUTATION

[0002] Technical Field

[0003] The invention is related to a computer implemented method for user localization in wireless communication by utilizing over-the-air computation (OAC).

[0004] Prior Art

[0005] Localization in wireless communication refers to the ability to determine the geographical location of a mobile device or user within a wireless network and it is important for a healthy communication.

[0006] Conventional methods generally take too much time to localize the users in the disclosing version will exploit one time slot or one resource block to perform computation over all transmitted signals within the year so that we can estimate the localization of user within one transmission frame and generally use the energy-based localization or RSSI based localization. Here every transmitter is allocated a specific resource to transmit in time, frequency, or timefrequency. So, if you have too many anchor nodes (ANs) it takes too much time or resources to estimate the localization of the users.

[0007] In the literature, many studies investigate distributed localization for low-complexity sensors. [l]-[4].

[0008] One of the studies [1], the authors propose a range-free localization as a cost-effective solution for low-complexity WSN. The proposed work, however, can only achieve coarse accuracy.

[0009] A voting-based localization is proposed that can withstand malicious beacon nodes in another study [2], However, storage overhead must be maintained because the target node must store all local data.

[0010] A collaborative distributed localization scheme that allows for a trade-off between wireless transmissions and accuracy is also disclosed in another study [5],

[0011] The authors propose a distributed localization algorithm for low-power sensors in Fifth Generation (5G)-enabled loT networks [6], The proposed methods [5][6] require the sensors to access information about the neighboring sensors, which is inconvenient in practice and introduces communication overhead. Another concern with the schemes disclosed [l]-[6] is that the latency increases linearly with the number of sensors.

[0012] As a result, all of the problem mentioned above has made it necessary to provide a novelty in the related field.

[0013] Brief Description and Objects of the Invention

[0014] The main object of the present invention is to establish a computer implemented method that enables localization of the target user devices doesn’t require any complex computation.

[0015] Another aim of the invention is to reduce latency and increase accuracy in localization method.

[0016] To achieve such an aim, the invention proposes the method described in this invention employs over-the-air computation to localize users for a system with multiple transmitters, anchor nodes (ANs), or sensors with known locations continuously transmit signals. These transmitting nodes’ location is mapped to IQ domain, where node will transmit the mapped / assigned complex value. At the receiving end, each user captures the signals transmitted by these nodes. The received signal is the result of combining all the transmitted signals from these nodes. Consequently, a single complex value is obtained on the IQ domain. By utilizing the predefined mapping, the user's location is derived based on the position of the received signal in the IQ map.

[0017] Description of the Figures of the Invention

[0018] The figures and related descriptions necessary for the subject matter of the invention to be understood better are given below.

[0019] Figure 1. Illustration of the system where squares represent ANs while circles represent the targets.

[0020] Figure 2. IQ domain mapping for OAC localization.

[0021] Detailed Description of the Invention

[0022] The invention is related to a computer implemented method for user localization in wireless communication by utilizing over-the-air computation (OAC). Over-the-air computation in wireless communications refers to the concept of performing computational tasks directly at the wireless communication nodes, such as mobile devices or base stations, instead of relying solely on centralized cloud or server-based computation. It leverages the computational capabilities of the wireless nodes to process and analyze data locally, reducing the need for extensive data transmission and offloading computational tasks to remote servers.

[0023] Referring to Figure 1; the system that carried out method comprises multiple anchor nodes has capabilities of continuous transmitting signal and at least one, preferably multiple target device having antenna which is able to receive the signal transmitted the signal of said transmitter and to be localized. The anchor nodes may be transmitter or sensors which can continuously transmit signals. Preferably, transmissions of anchor nodes are synchronized. Furthermore, they may be wired to each and shared common clock. Alternatively, they may wirelessly communicate with each other.

[0024] Furthermore, target device has also capabilities processing the signal received.

[0025] The position of the anchor nodes is known and real word distribution (positions) of the anchor nodes is mapped to the complex IQ domain. The mapping should be one-to-one so that if the complex IQ map is given, the real location can be assumed. Note that, the mapping can follow exactly the real distribution of the ANs in reality, or it can be unique and different. A 4-AN mapping is shown in Figure 2.

[0026] The target device or devices receives signals from multiple anchor nodes which position on IQ domain known. According to calculation carried out based received signals, location of the target devices can be found.

[0027] In preferred embodiment, the formula of is used to calculate location of the target devices. In this formula Skrepresents the signal received at the k-th target device and Qnis the IQ-domain signal transmitted from the n-th anchor node and dk nis the distance between k-th target device and n-th anchor node and e is the pathloss exponent for the given environment and p represents the other losses in received power. So, in the system that Qnand Skare known 2-D (for a complex constellation symbol) and the dk ncan be found and used to find position the target device because the positions of the anchor nodes are already known, as disclosed before. The above-mentioned calculation is preferably carried at the target device. In some cases, randomness of shadowing and small-scale fading is need to be compensated.

[0028] To compensate small-scale fading, channel hardening can be used. Channel hardening refers to a phenomenon in wireless communication systems where the effects of channel fading are mitigated or reduced due to the specific characteristics of the wireless channel. The channel hardening can be achieved by multiple techniques. For example, spatial diversity introduced by multiple antennas of the MIMO system, spatial multiplexing, improving the signal strength at the receiver by beamforming, antenna diversity or cooperative communication can be used. So, both anchor nodes and the target device may have multiple antennas.

[0029] Furthermore, increasing number of anchor nodes reduces of the shadowing effect.

[0030] For synchronization problem, cyclic prefixes are used for transmitted signal by anchor nodes. Here, the cyclic prefix must be larger than is the maximum propagation delay (and delay spread), the signals from the anchor nodes would sum up during the symbol duration which enables us to get the aggregate signal.

[0031] REFENCES

[0032] [1] T. He, C. Huang, B. M. Blum, J. A. Stankovic, and T. Abdelzaher, “Range-free localization schemes for large scale sensor networks,” in Proc. ACM International Conference on Mobile Computing and Networking. New York, NY, USA: Association for Computing Machinery, 2003, pp. 81 — 95.

[0033] [2] D. Liu, P. Ning, and W. K. Du, “Attack-resistant location estimation in sensor networks,” in IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005. IEEE, 2005, pp. 99-106.

[0034] [3] T. Shu, Y. Chen, J. Yang, and A. Williams, “Multi-lateral privacypreserving localization in pervasive environments,” in IEEE INFOCOM 2014-IEEE Conference on Computer Communications. IEEE, 2014, pp. 2319-2327.

[0035] [4] X. Shi, F. Tong, W.-A. Zhang, and L. Yu, “Resilient privacy-preserving distributed localization against dishonest nodes in internet of things,” IEEE Internet of Things Journal, vol. 7, no. 9, pp. 9214-9223, 2020.

[0036] [5] J. Cota-Ruiz, J.-G. Rosiles, P. Rivas-Perea, and E. Sifuentes, “A distributed localization algorithm for wireless sensor networks based on the solutions of spatially-constrained local problems,” IEEE Sensors Journal, vol. 13, no. 6, pp. 2181-2191, 2013.

[0037] [6] S. Safavi, U. A. Khan, S. Kar, and J. M. Moura, “Distributed localization: A linear theory,” Proceedings of the IEEE, vol. 106, no. 7, pp. 1204-1223, 2018.

Claims

CLAIMS1. A computer implemented method that utilize over-the-air computation for localization of at least one target device having receiver in a system having plurality of anchor nodes of which position are known and are one-to-one mapped in IQ domain characterized by Receiving continuously transmitted signals of the anchor nodes by the target device, Calculating the location of the target device by remapping the received signal according to received continuous signals of the anchor nodes.The mapping is one-to-one mapping andA method where the received signal is places in the IQ domain and remapped to get the real location.A method where multiple terminals can localize themselves at the same time independently with no interference.

2. A method according to Claim 1, wherein calculating the location of the target device at the target device according to received continuous signals of the anchor nodes by formula ofwherein Skrepresents the signal received at the Zc-th target device and Qnis the IQ- domain signal transmitted from the n-th anchor node and dk nis the distance between Zc-th target device and n-th anchor node and e is the pathloss exponent for the given environment and p represents the losses in received power.

3. A data processing device comprising means for carrying out the steps of the method of Claim 1 to 7.

4. A computer program comprising instructions which, when the program is executed by a data processing device, cause the data processing device to carry out the steps of the method of Claim 1 to 7.

5. A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the steps of the method of Claim 1 to 7.

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