TECHNICAL FIELD

The invention is a wireless communication design, for achieving perfect secrecy without encryption using dual artificial signal injection for downlink scenarios.

BACKGROUND

The most popular form of security utilized in current systems is cryptography, where public and private keys are generated and managed. For example, the length of keys used by major banks to protect client financial data is 2048 bits. On the other hand, various physical layer security models have also been proposed in the literature, closely related techniques to the proposed model that involve AN injection include. Lemayian, J. P., & Hamamreh, J. M. (2020) sent signals to two users using time diversity, where auxiliary signals are calculated from user channel and added to the user data before transmission (A Novel Small-Scale Nonorthogonal Communication Technique Using Auxiliary Signal Superposition with Enhanced Security for Future Wireless Networks. RS Open Journal on Innovative Communication Technologies, 1 (2).). Moreover, Zia, M. F., & Hamamreh, J. M. (2020) use auxiliary matrices calculated from the user channel and multiplied by the user data before transmission. They use the degree of freedom provided by the use of multiple antennas to intelligently generate AN used to degrade the eavesdropper's channel while the users receive their intended signal (An Advanced Non-Orthogonal Multiple Access Security Technique for Future Wireless Communication Networks. RS Open Journal on Innovative Communication Technologies).

Zhongwu Xiang et al (2019) propose a PLS design in cognitive radio inspired NOMA network with multiple primary and secondary users. The scheme pairs primary and secondary users according to their channel gain and then power-domain NOMA is used to transmit the signal. According to the authors, secrecy levels can be improved by pairing the primary users with the best channel gains or by reducing the number of secondary users (Physical layer security in cognitive radio inspired NOMA network”. In: IEEE Journal of Selected Topics in Signal Processingl 3.3(2019), pp. 700-714). Additionally, Lu Lv et al (2018) propose a new secrecy beamforming (SBF) scheme by exploiting the use of artificial noise to protect confidential information of two NOMA users. The paradigm is designed for multiple-input single-output non-orthogonal multiple access (MISO-NOMA) systems such that only the eavesdropper's signal gets degraded. However, the proposed power-domain schemes still sufferers from signal- to-interference-plus-noise ratio (SINR) degradation. In the case of using beamforming for security, the eavesdropper simply needs to get close enough to the user to get and decode the signal. Also, they propose Waveform-Domain NOMA. The paradigm proposes the utilization of multiple waveforms in the same resource element (RE), where relevant waveforms are assigned to each user and then decoded at the receiver side. The drawback to this system is that it contains additional processing at the receiver. Which increases power consumption as well as complexity (Secure MISONOMA transmission with artificial noise. In: IEEE Transactions on vehiculartechnology 67.7 (2018), pp. 6700-6705).

There are numerous advantages of using PLS (Used in the proposed invention) over conventional cryptography methods (Li Sun and Qinghe Du. “Physical layer security with its applications in 5G networks: A review”. In: China Communications14.12 (2017), pp. 1-14.). Firstly, PLS can utilize a commonly used channel between legitimate users to disrupt the received signal at the eavesdropper's antenna. Hence eliminating the need to share and manage keys. Secondly, most PLS design techniques require simple signal processing methods. This is beneficial to services with limited processing and low power requirements (Haji M Furqan, Jehad Hamamreh, Huseyin Arslan, et al. “Physical Layer Security for NOMA: Requirements, Merits, Challenges, and Recommendations”. In: arxiv preprint arxiv: 1905.05064(2019)). Finally, according to Jehad M Hamamreh, Haji M Furqan, and Huseyin Arslan. (“Classifications and applications of physical layer security techniques for confidentiality: A comprehensive survey”. In: IEEE Communications Surveys & Tutorials21 .2 (2018), pp. 1773-1828), channel-dependent resource allocation and link adaptation schemes in PLS can be employed to design adaptive security models that are dependent on specific occurrences.

Wireless media is becoming the dominant access type for most of the internetbased services; however, serious security risks have been experienced on the wireless signal due to their broadcast nature. Therefore, security ensuring precautions have emerge as a critical need for wireless services. In specific, users require confidential transmission of their wireless data such as private messages, calls, videos, financial transactions, etc. As a matter of fact, secure communication systems are desirable without just relying on the traditional encryption and key-sharing methods. The proposed technology has been motivated by the following problems faced in practical scenarios,

• The key distribution management process for the legitimate parties is extremely challenging, especially in large-scale heterogeneous and decentralized wireless networks. Furthermore, longer key length results in more waste of resources, apart from the fact that implementing security methods with Shannon’s perfect secrecy is not practical in today’s data volume.

• The fast developments and advances of computing power devices reveal the fact that current secret key-based techniques can be cracked, no matter how much mathematically complex they are, especially when quantum computing is used.

• Users with sensitive applications like those related to financial and personal secret information can never compromise security, even if it was at the expense of small degradation in throughput and reliability.

• Encryption-based systems add extra delay and complexity to applications that require high level of security such as autonomous driving, remote surgery, and controlling unmanned aerial vehicles (UAVs).

Encryption and physical layer security are the most popular wireless security techniques currently used to try and mitigate the above-mentioned challenges. In specific, encryption is the most widely used form of security currently used in many wireless communications industries to secure user data. This security technique involves public and private key sharing and management in the following way:

• Wireless security against second layer vulnerabilities is done using multiple controls. IEEE 802.1X addresses these problems using a set of protocols to improve and standardize wireless encryption. These protocols include extensible authentication protocol (EAP), Protected EAP (PEAP), and tunneled transport layer security (TTLS), which is better than the weak wired equivalent privacy (WEP) keys utilized by 1 G wireless local area networks (WLANs).

• Moreover, the 802.11 i standard directs for the use of temporal key integrity protocol (TKIP) as well as advanced encryption standard (AES) to encrypt data on the wireless network. TKIP used RC4 encryption algorithm and addresses the weak key problems in WEP by forcing a new key to be generated every 10,000 packets. Moreover, TKIP hashes the values of the initialization vector, which was sent as plain text by EAP, as well as use a message integrity check (MIC) function to validate the integrity of a packet to prevent hackers from injecting messages that can be used to obtain encryption keys. AES is a strong data encryption standard that is a replacement for WEP and RC4 encryption.

• Besides, wireless networks are also secured using virtual private networks (VPN), this technique uses a combination of tunneling, encryption, authentication, and access control.

IEEE considers 802.1x as an enhanced port-based control method used to control access to network ports. 802.1x does not demand a specific verification technique, even though EAP is the most popular method for WLANs, which is a basis for many verification methods. The client and the access point determine the specific validation method during the verification process, where the EAP client communicates to the access point which prompts the client for verification information. After the validator has received the information from the client it sends it to a verification server for verification. Further communication with the client is not permitted until the server has verified the access request. If the access request is positively verified, the server generates a WEP key which is sent to the client through the access point, therefore, the client can access the network through the access point. Numerous available implementations of EAP include:

• Transport Layer Security (EAP-TLS): This implementation used in 802.1X clients for Windows XP was developed by Microsoft. It is powerful but it requires every WLAN user to install a client certificate.

• Lightweight EAP (LEAP): Realized by CISCO and utilized in their Aironet solution, it not only provides for dynamic WEP key production but also fixed password user verification.

• Protected EAP (PEAP): founded by RSA Security, CISCO, and Microsoft, it does not demand certificates for verifications, however, it allows for dynamic WEP key generation and provide opportunities for a password, token, or digital certificate-based user verification. • Tunneled Transport Layer Security (EAP-TTLS): This implementation was developed by Funk Software and Certicom as an alternative to REAP, it provides opportunities for a password, token, or digital certificate-based user verification. Moreover, it needs only the server to be certified, unlike EAP-TLS. WEP and Wi-Fi protected access (WPA) are the most common types of wireless security used by the industry. However, as earlier noted WEP is a weak security standard where private user information can be illegally obtained using a basic laptop computer and cheap off-the-shelf software tools. Nevertheless, WEP can still be used as the first line of defense against attacks and possibly delay intrusion by eavesdroppers. WEP is an old IEEE 802.11 standard that was suspended in 2003 and replaced by WPA which was a quick security fix for the drawbacks of its predecessor and whose current standard is WPA2. WPA2 uses an encryption device to encrypt the network with a 256-bit key which provides better security than WPA. Also, Lemayian, J. P., & Hamamreh, J. M. and Zia, M. F., & Hamamreh, J. M. introduce security for both non-standalone and the standalone NR 5G systems. In this newly proposed 5G system, public and private keys are still employed to protect user data. However, the emergence of supercomputers makes cryptography-based technique more vulnerable, as security breach is just a matter of time, where private keys can be obtained in a short time by supercomputers using brute force iteration method.

LIST OF FIGURES

Figure 1 . The model of the System

Figure 2a. The algorithm implementation at the base station

Figure 2b. The algorithm implementation at both the legitimate user (Bob) and the eavesdropper (Eve)

Figure 3. Hardware implementation of the proposed technology

The correspondings of the letters used in the figures: DB: Data bits

DETAILED DESCRIPTION OF THE INVENTION

Figure 1 represents the system model of the proposed wireless communication design, for achieving perfect secrecy without encryption using dual artificial signal injection for downlink scenarios, where two transmit antennas (Tx1 and Tx2) located at two different cells (multi-cell) are simultaneously communicating with a single user (Bob) (B) in the presence of an eavesdropper (Eve) (E) with respect to the following steps:

1. Two signals, Ri(n) and R2(n)) that are depended on the channel of the user (Bob) (B) are generated according the following equations: is the artificial noise (AN), hl and hl are Bob’s (B) channels from base station 1 and 2 respectively as shown in Figure 1 . AN is used to introduce randomness and protect the transmitted signal while Bob’s (B) channels are used because they are unique only to Bob (B) hence, only Bob (B) can remove the effects of the channel on the communicated signal. R ₁ and R ₂ are designed this way so that the channel characteristics cancel each other only when the total signal from antenna 1 and 2 is received at the legitimate user Bob (B).

2. At antenna 1 , R ₁ is added to user data and at antenna 2 R ₂ is subtracted from the user data. This stage will ensure that the channel effect is completely removed for the total received signal from antenna 1 and antenna 2 at Bob (B) while completely degrading the signal at the eavesdropper (Eve) (E).

3. The user then receives the signal and divides it by (Process known as zero forcing) to obtain the original transmitted signal from the base stations. The received signal is expected to be better than the signal transmitted in additive white Gaussian noise (AWGN) because the zero forcing process reduces the noise in the system.

Moreover, no private or public keys are needed to secure the information. The user directly receives their data without doing any extra processing. The special userchannel depended signals provides perfect secrecy and perfect network secrecy, where the former term means zero information leakage against external eavesdroppers (Eve) (E), while the latter means zero information leakage against both external and internal eavesdroppers.

Figure 2A and Figure 2B represents the technical implementation of the proposed system's algorithm, part (A) shows the algorithm implementation at the base station while part (B) of the figure shows the algorithm implementation of the received signal at both the legitimate user (Bob) (B) and the eavesdropper (Eve) (E). For the base station side (Figure 2A) the algorithm implementation follows the following steps:

1 . Data bits (DB) are generated.

2. The same bits are shared with two different base stations in two different cells where the data bits (DB) are modulated. The two different cells will make sure that Bob’s (B) channels are very different, therefore providing better protection.

3. The modulated data symbols on each base station are then added to the auxiliary signals.

4. The inverse fast furrier transform (IFFT) of the resulting signal from step 3 above is taken to change the signal from frequency to time domain.

5. Finally, a cyclic prefix is added to the resulting signal from step 4 above at each base station to prevent inter-symbol interference before transmission.

At the receiver, (See figure 2B)), the reception process is as follows:

1 . The cyclic prefix is first removed immediately after the signal has been received.

2. The resulting signal from step 1 above is then transformed to time domain using fast furrier transform (FTT).

3. Equalization (zero forcing) is then performed on the signal in time domain to remove the channel effects.

4. The signal is then demodulated to obtain the transmitted data bits.

This technology is modeled when the two transmit antennas are at different cells, however, the technology is applicable to any scenario where dual transmission is employed and in systems that provide diversity such as multiple input multiple output (MIMO), massive-MIMO (mMIMO), Cooperative Multi-Point (CoMP), and Multi-cells transmission.

The proposed invention will provide solutions to all the mentioned limitations of current wireless communication systems by using multi-cell dual transmission. The software design of the proposed algorithm is as follows:

Given that:

Q and W are chosen to be Bernoulli-distributed random variables with values one or zero, (1) and (2) are then used to calculate R1 and R2 as shown in (3) and (4). where and are the frequency channel responses of Tx1 to Bob (B) and Tx2 to

Bob (B) respectively.

Signal at Bob’s (B) receiver (Legitimate user).

The received signal at Bob (B) from Tx1 is shown in (5) as y _b (ri). where, is the data intended for Bob (B) and is the added auxiliary signal from (3). Similarly, the received signal at Bob (B) from Tx2 is shown in (6) as where R ₂ (n) is the subtracted auxiliary signal from (4). The total received signal at Bob from both Tx1 and Tx2 is shown at (7). where w _b (n) is the additive white Gaussian noise (AWGN) between Tx1 , Tx2, and Bob (B). Substituting (5) and (6) to (7) results in (8).

To obtain the signal intended for Bob (B) (x(n)) zero forcing is performed on (8) by dividing (8) by to get the actual received data at Bob in (9) is the decoded signal at Bob’s (B) terminal. Signal at Eve’s (E) receiver.

The received signal at Eve (E) from Tx1 is shown in (10) as yl(ri). where, x(n) is the data intended for Bob (B), hl is the frequency channel responses of the channel between Tx1 and Bob (B), and is the added auxiliary signal from (3). Similarly, the received signal at Eve (E) from Tx2 is shown in (11 ) as where is the subtracted auxiliary signal from (4) and h ² is the frequency channel responses of the channel between Tx2 and Eve (E). The total received signal at Eve from both Tx1 and Tx2 is shown at (12). where w _e (ri) is the AWGN between Tx1 , Tx2, and Eve (E). Substituting (10) and (11) to (12) results in (13).

To obtain the signal intended for Bob (B) (x(n)) but received by Eve (E) zero forcing is performed on (13) by dividing (13) by (hl + hl~) to get the actual received data at Eve (E) (x _e (n)).

As observed in (14) the noise is too large such that the eavesdropper (Eve) (E) can never be able to decipher the data send to Bob (B).

Hardware implementation

The proposed technology can be implemented using ESP32 modules (M) as shown in figure 3. ESP32 module (M) has many attractive qualities that makes it very desirable and best suited for this technology. For example, it is highly integrated with the following in-built features:

1 . Antenna switches.

2. RF balun.

3. Power amplifier.

4. Low-noise receive amplifier.

5. Filters.

6. Power management modules. 7. Low power requirements.

Other features include hybrid Wi-Fi and Bluetooth connectivity for a wide range of applications. As shown in figure 3, data bits (DB) from the base stations (BS) are transmitted to two ESP32 modules (M) located in two different cells (Cell 1 (C1 ) and Cell 2 (C2)). The ESP32 modules (M) are then used to implement the software of the proposed technology described above.

Advantages of the proposed technique over the state of the art include:

- Low complexity: It is structurally simple but very effective, and it does not require to be supported by a complicated transceiver architecture. More importantly, it does not require any changes or extra processing at the receiver side thanks to the proper design of the added AN, which can be perfectly canceled during the MRC process.

- Low power: Since no processing is required at the receiver, there is no use of high-power during communication which usually is a big consumer of energy in conventional systems. All the processing is done at the base station.

- High security: The use of added signals R1 and R2 to the transmitted user signal makes sure that the signal can only be received at the legitimate user and is completely degraded at the receiver, hence providing complete secrecy.

- It can provide secrecy in one of the most challenging scenarios, where there is no spatial degree of freedom (no null-space) and the channel is flat fading (i.e., no much randomness).

- The proposed design creates an extra degree of freedom in the power domain due to the added AN, which can be utilized not only to enhance secrecy but also for other purposes alongside secrecy such as reducing PAPR and mitigating out-of-band emission (OOBE) of orthogonal frequency-division multiplexing (OFDM)-based systems. In other words, the scheme increases system design flexibility.

- The maximum benefit and best operating condition of the proposed scheme can be obtained when it is used with OFDM-based waveforms over dispersive channels. This is due to two reasons: 1 ) the AN vector’s randomness becomes not only a function of the generated signal at the source but also of the dispersive channel randomness. 2) the possibility of redesigning the AN to solve some of the major drawbacks of OFDM.