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Secret Communication
Secret Communication
In recent years, information-theoretic security (also known as physical-layer security) that exploits the physical characteristics of the wireless channel has attracted considerable attention as an alternative security solution or additional layer of security [1]. The theoretical basis for this information-theoretic security was laid by Wyner [2] and later by Csiszar and Korner [3], who proved that there exist channel codes guaranteeing both robustness to transmission errors and a prescribed degree of data confidentiality. To quantify the security performance at physical layer, one important metric, named secrecy capacity (Cs = [Cb - Ce]+) which is the difference of intended receiver and eavesdropper's capacities [1], is used. For slow fading, a detailed characterizations of the outage secrecy capacity of slow fading channels is provided in [4]. It has been shown that fading alone guarantees that information-theoretic security is achievable, even when the eavesdropper has a higher average signal-to-noise ratio (SNR) than the legitimate receiver. For fast fading, the ergodic secrecy capacity of fading channels is independently studied in [5].
In recent years, information-theoretic security (also known as physical-layer security) that exploits the physical characteristics of the wireless channel has attracted considerable attention as an alternative security solution or additional layer of security [1]. The theoretical basis for this information-theoretic security was laid by Wyner [2] and later by Csiszar and Korner [3], who proved that there exist channel codes guaranteeing both robustness to transmission errors and a prescribed degree of data confidentiality. To quantify the security performance at physical layer, one important metric, named secrecy capacity (Cs = [Cb - Ce]+) which is the difference of intended receiver and eavesdropper's capacities [1], is used. For slow fading, a detailed characterizations of the outage secrecy capacity of slow fading channels is provided in [4]. It has been shown that fading alone guarantees that information-theoretic security is achievable, even when the eavesdropper has a higher average signal-to-noise ratio (SNR) than the legitimate receiver. For fast fading, the ergodic secrecy capacity of fading channels is independently studied in [5].
Intuitively, the secrecy capacity (Cs) is guaranteed by simply providing the SNR advantage to intended recipient over eavesdropper. For that reason, various techniques are applied, which is listed below:
Intuitively, the secrecy capacity (Cs) is guaranteed by simply providing the SNR advantage to intended recipient over eavesdropper. For that reason, various techniques are applied, which is listed below:
1. Adaptation Rate and Power Strategy [6].
1. Adaptation Rate and Power Strategy [6].
2. Artificial Noise interfering with secret information signal at eavesdropper; however, not affecting the intended receiver [7].
2. Artificial Noise interfering with secret information signal at eavesdropper; however, not affecting the intended receiver [7].
3. Cooperative and Jamming Relay [8].
3. Cooperative and Jamming Relay [8].
4. Interference Channels, Multiple Access Channels or Multi-user Broadcast Channels [8], [9].
4. Interference Channels, Multiple Access Channels or Multi-user Broadcast Channels [8], [9].
Also, the implementation of these techniques into the large scale systems, such as adhoc network, cognitive radio network or sensor network, are intensively studied [9].
Also, the implementation of these techniques into the large scale systems, such as adhoc network, cognitive radio network or sensor network, are intensively studied [9].
Recently, many articles exploit the CSI advantage to the intended receiver over eavesdropper since CSI knowledge at receiver's side is important to perform coherent detection. Thus, without CSI leakage to eavesdropper, the intended recipient has advantage of coherent detection whereas eavesdropper needs to detect incoherently.
Recently, many articles exploit the CSI advantage to the intended receiver over eavesdropper since CSI knowledge at receiver's side is important to perform coherent detection. Thus, without CSI leakage to eavesdropper, the intended recipient has advantage of coherent detection whereas eavesdropper needs to detect incoherently.
While the performance of the secret communication can be measured in terms of the secrecy rate, which is the number of information bits reliably transmitted to the intended users without being leaked to the adversary.. As energy use and costs for communications continue to rise, the energy efficiency of secure and reliable communications, called secrecy energy efficiency (SEE), is emerging as another important figure-of-merit. Hence, energy efficiency is also studied in [11].
While the performance of the secret communication can be measured in terms of the secrecy rate, which is the number of information bits reliably transmitted to the intended users without being leaked to the adversary.. As energy use and costs for communications continue to rise, the energy efficiency of secure and reliable communications, called secrecy energy efficiency (SEE), is emerging as another important figure-of-merit. Hence, energy efficiency is also studied in [11].
References:
References:
[1] H. V. Poor, “Information and inference in the wireless physical layer,” IEEE Wireless Communications, vol. 19, no. 1, pp. 40–47, 2012. (Click here!)
[1] H. V. Poor, “Information and inference in the wireless physical layer,” IEEE Wireless Communications, vol. 19, no. 1, pp. 40–47, 2012. (Click here!)
[2] A. D. Wyner, “The wire-tap channel,” The bell system technical journal, vol. 54, no. 8, pp. 1355–1387, 1975. (Click here!)
[2] A. D. Wyner, “The wire-tap channel,” The bell system technical journal, vol. 54, no. 8, pp. 1355–1387, 1975. (Click here!)
[3] I. Csiszar and J. Korner, “Broadcast channels with confidential messages,” IEEE transactions on information theory, vol. 24, no. 3, pp. 339– 348, 1978. (Click here!)
[3] I. Csiszar and J. Korner, “Broadcast channels with confidential messages,” IEEE transactions on information theory, vol. 24, no. 3, pp. 339– 348, 1978. (Click here!)
[4] M. Bloch, J. Barros, M. R. Rodrigues, and S. W. McLaughlin, “Wireless information-theoretic security,” IEEE Transactions on Information Theory, vol. 54, no. 6, pp. 2515–2534, 2008. (Click here!)
[4] M. Bloch, J. Barros, M. R. Rodrigues, and S. W. McLaughlin, “Wireless information-theoretic security,” IEEE Transactions on Information Theory, vol. 54, no. 6, pp. 2515–2534, 2008. (Click here!)
[5] Y. Liang, H. V. Poor, and S. Shamai, “Secrecy capacity region of fading broadcast channels,” in 2007 IEEE International Symposium on Information Theory, pp. 1291–1295, IEEE, 2007. (Click here!)
[5] Y. Liang, H. V. Poor, and S. Shamai, “Secrecy capacity region of fading broadcast channels,” in 2007 IEEE International Symposium on Information Theory, pp. 1291–1295, IEEE, 2007. (Click here!)
[6] P. K. Gopala, L. Lai, and H. El Gamal, “On the secrecy capacity of fading channels,” IEEE Transactions on Information Theory, vol. 54, no. 10, pp. 4687–4698, 2008. (Click here!)
[6] P. K. Gopala, L. Lai, and H. El Gamal, “On the secrecy capacity of fading channels,” IEEE Transactions on Information Theory, vol. 54, no. 10, pp. 4687–4698, 2008. (Click here!)
[7] S.Goel and R.Negi,“Guaranteeing secrecy using artificial noise,”IEEE Transactions on Wireless Communications, vol. 7, no. 6, pp. 2180–2189, 2008. (Click here!)
[7] S.Goel and R.Negi,“Guaranteeing secrecy using artificial noise,”IEEE Transactions on Wireless Communications, vol. 7, no. 6, pp. 2180–2189, 2008. (Click here!)
[8] E. Tekin, A. Yener, "The general Gaussian multiple-access and two-way wiretap channels: Achievable rates and cooperative jamming," IEEE Trans. Info. Theory, vol. 54 no. 6 pp. 2735-2751 2008. (Click here!)
[8] E. Tekin, A. Yener, "The general Gaussian multiple-access and two-way wiretap channels: Achievable rates and cooperative jamming," IEEE Trans. Info. Theory, vol. 54 no. 6 pp. 2735-2751 2008. (Click here!)
[9] A. Mukherjee, "Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey," IEEE Commun. Surveys Tutorials, vol. 16 no. 3 pp. 1550-73 2014. (Click here!)
[9] A. Mukherjee, "Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey," IEEE Commun. Surveys Tutorials, vol. 16 no. 3 pp. 1550-73 2014. (Click here!)
[10] T.-Y. Liu, P.-H. Lin, S.-C. Lin, Y.-W. P. Hong, E. A. Jorswieck, "To avoid or not to avoid CSI leakage in physical layer secret communication system," IEEE Commun. Mag., vol. 53 no. 12 pp. 19-25 Dec. 2015. (Click here!)
[10] T.-Y. Liu, P.-H. Lin, S.-C. Lin, Y.-W. P. Hong, E. A. Jorswieck, "To avoid or not to avoid CSI leakage in physical layer secret communication system," IEEE Commun. Mag., vol. 53 no. 12 pp. 19-25 Dec. 2015. (Click here!)
[11] Hien Ta, Sang Wu Kim, "Adapting Rate and Power for Maximizing Secrecy Energy Efficiency", IEEE Communications Letters, 2017. (Click here!)
[11] Hien Ta, Sang Wu Kim, "Adapting Rate and Power for Maximizing Secrecy Energy Efficiency", IEEE Communications Letters, 2017. (Click here!)
Covert Communication
Covert Communication
(Low Probability of Detection)
(Low Probability of Detection)
The broadcast nature of the wireless medium allows wireless networks to be easily monitored, which creates a serious concern about the privacy of wireless communications. Covert or low probability of detection communication is crucial to protect user privacy and provide a strong security. It has great implications for many practical applications ranging from covert military and national security operations to privacy protection for users of commercial wireless networks.
The broadcast nature of the wireless medium allows wireless networks to be easily monitored, which creates a serious concern about the privacy of wireless communications. Covert or low probability of detection communication is crucial to protect user privacy and provide a strong security. It has great implications for many practical applications ranging from covert military and national security operations to privacy protection for users of commercial wireless networks.
Recent work shows that robust detection of signal transmission is impossible, even if the detector takes an infinite number of samples, if the signal-to-noise ratio (SNR) at the energy detector input is below a threshold, known as the SNR wall [1]. This SNR wall, caused by the inherent mismatch between the true noise power and its estimate, which is referred to as the noise uncertainty, can be leveraged to hide the signal transmission. In the realistic situation of uncertain knowledge of the noise power, a positive covert rate, i.e. reliable transmission of O(N) bits in N channel uses, is possible while guaranteeing that the adversary cannot detect the signal transmission [2]. The idea of exploiting the noise uncertainty was extended to jamming the adversary by varying the jamming signal power [3] or generating artificial noise by the full-duplex legitimate recipient [4].
Recent work shows that robust detection of signal transmission is impossible, even if the detector takes an infinite number of samples, if the signal-to-noise ratio (SNR) at the energy detector input is below a threshold, known as the SNR wall [1]. This SNR wall, caused by the inherent mismatch between the true noise power and its estimate, which is referred to as the noise uncertainty, can be leveraged to hide the signal transmission. In the realistic situation of uncertain knowledge of the noise power, a positive covert rate, i.e. reliable transmission of O(N) bits in N channel uses, is possible while guaranteeing that the adversary cannot detect the signal transmission [2]. The idea of exploiting the noise uncertainty was extended to jamming the adversary by varying the jamming signal power [3] or generating artificial noise by the full-duplex legitimate recipient [4].
More recently, the impact of channel uncertainty on covert communication has been studied in [5]. Recently, an information theoretic analysis of embedding the covert signal in an innocent signal transmission has been developed in [6]. This work is motivated by [7] where a dirty constellation (hardware imperfection) is exploited to hide the transmission of information. Other work considered covertly sending a covert message in amplify-and-forward relay network while forwarding the source message to the destination [8].
More recently, the impact of channel uncertainty on covert communication has been studied in [5]. Recently, an information theoretic analysis of embedding the covert signal in an innocent signal transmission has been developed in [6]. This work is motivated by [7] where a dirty constellation (hardware imperfection) is exploited to hide the transmission of information. Other work considered covertly sending a covert message in amplify-and-forward relay network while forwarding the source message to the destination [8].
Intuitively, covert communication is guaranteed by exploiting the sources of uncertainty at Willie:
Intuitively, covert communication is guaranteed by exploiting the sources of uncertainty at Willie:
1. Imperfect knowledge of noise power (noise uncertainty) [9].
1. Imperfect knowledge of noise power (noise uncertainty) [9].
2. Imperfect knowledge of channel state information (channel uncertainty) [5].
2. Imperfect knowledge of channel state information (channel uncertainty) [5].
3. Hiding under a covert (camouflage) transmission [6, 8].
3. Hiding under a covert (camouflage) transmission [6, 8].
4. Unknown transmission time [10].
4. Unknown transmission time [10].
While the performance of the secret communication can be measured in terms of the secrecy throughput, covert communication is measured via the covert rate, which is the number of information bits reliably transmitted to the intended users without being detected by the adversary. Another measure also concerned in covert communication is the detection error probability, i.e. sum of false alarm and missed detection probability, at the adversary. This measure is to quantify the ability of detecting the presence of message transmission.
While the performance of the secret communication can be measured in terms of the secrecy throughput, covert communication is measured via the covert rate, which is the number of information bits reliably transmitted to the intended users without being detected by the adversary. Another measure also concerned in covert communication is the detection error probability, i.e. sum of false alarm and missed detection probability, at the adversary. This measure is to quantify the ability of detecting the presence of message transmission.
References:
References:
[1] R. Tandra and A. Sahai, “SNR walls for signal detection,” IEEE Journal of selected topics in Signal Processing, vol. 2, no. 1, pp. 4–17, 2008. (Click here!)
[1] R. Tandra and A. Sahai, “SNR walls for signal detection,” IEEE Journal of selected topics in Signal Processing, vol. 2, no. 1, pp. 4–17, 2008. (Click here!)
[2] S. Lee, R. J. Baxley, J. B. McMahon, and R. S. Frazier, “Achieving positive rate with undetectable communication over MIMO rayleigh channels,” in Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014 IEEE 8th, pp. 257–260, IEEE, 2014. (Click here!)
[2] S. Lee, R. J. Baxley, J. B. McMahon, and R. S. Frazier, “Achieving positive rate with undetectable communication over MIMO rayleigh channels,” in Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014 IEEE 8th, pp. 257–260, IEEE, 2014. (Click here!)
[3] T. V. Sobers, B. A. Bash, S. Guha, D. Towsley, and D. Goeckel, “Covert communication in the presence of an uninformed jammer,” IEEE Transactions on Wireless Communications, vol. 16, pp. 6193–6206, Sept 2017. (Click here!)
[3] T. V. Sobers, B. A. Bash, S. Guha, D. Towsley, and D. Goeckel, “Covert communication in the presence of an uninformed jammer,” IEEE Transactions on Wireless Communications, vol. 16, pp. 6193–6206, Sept 2017. (Click here!)
[4] J. Hu, K. Shahzad, S. Yan, X. Zhou, F. Shu, and J. Li, “Covert communications with a full-duplex receiver over wireless fading channels,” in 2018 IEEE International Conference on Communications (ICC), pp. 1– 6, IEEE, 2018. (Click here!)
[4] J. Hu, K. Shahzad, S. Yan, X. Zhou, F. Shu, and J. Li, “Covert communications with a full-duplex receiver over wireless fading channels,” in 2018 IEEE International Conference on Communications (ICC), pp. 1– 6, IEEE, 2018. (Click here!)
[5] H. Q. Ta and S. W. Kim, “Covert communication under channel uncertainty and noise uncertainty,” in ICC 2019 - 2019 IEEE International Conference on Communications (ICC) , pp. 1–6, May 2019. (Click here!)
[5] H. Q. Ta and S. W. Kim, “Covert communication under channel uncertainty and noise uncertainty,” in ICC 2019 - 2019 IEEE International Conference on Communications (ICC) , pp. 1–6, May 2019. (Click here!)
[6] K. S. K. Arumugam and M. R. Bloch, “Embedding covert information in broadcast communications,” IEEE Transactions on Information Forensics and Security , 2019. (Click here!)
[6] K. S. K. Arumugam and M. R. Bloch, “Embedding covert information in broadcast communications,” IEEE Transactions on Information Forensics and Security , 2019. (Click here!)
[7] A. Dutta, D. Saha, D. Grunwald, and D. Sicker, “Secret agent radio: Covert communication through dirty constellations,” in International Workshop on Information Hiding, pp. 160–175, Springer, 2012. (Click here!)
[7] A. Dutta, D. Saha, D. Grunwald, and D. Sicker, “Secret agent radio: Covert communication through dirty constellations,” in International Workshop on Information Hiding, pp. 160–175, Springer, 2012. (Click here!)
[8] J. Hu, S. Yan, X. Zhou, F. Shu, J. Li, and J. Wang, “Covert communication achieved by a greedy relay in wireless networks,” IEEE Transactions on Wireless Communications, vol. 17, no. 7, pp. 4766–4779, 2018. (Click here!)
[8] J. Hu, S. Yan, X. Zhou, F. Shu, J. Li, and J. Wang, “Covert communication achieved by a greedy relay in wireless networks,” IEEE Transactions on Wireless Communications, vol. 17, no. 7, pp. 4766–4779, 2018. (Click here!)
[9] B. He, S. Yan, X. Zhou, and V. K. N. Lau, “On covert communication with noise uncertainty,” IEEE Communications Letters, vol. 21, pp. 941–944, April 2017. (Click here!)
[9] B. He, S. Yan, X. Zhou, and V. K. N. Lau, “On covert communication with noise uncertainty,” IEEE Communications Letters, vol. 21, pp. 941–944, April 2017. (Click here!)
[10] B. A. Bash, D. Goeckel, and D. Towsley, “LPD communication when the warden does not know when,” in Proc. IEEE Int. Symp. Inf. Theory , Honolulu, HI, USA, Jul. 2014, pp. 606–610. (Click here!)
[10] B. A. Bash, D. Goeckel, and D. Towsley, “LPD communication when the warden does not know when,” in Proc. IEEE Int. Symp. Inf. Theory , Honolulu, HI, USA, Jul. 2014, pp. 606–610. (Click here!)
NB-IoT Random Access
NB-IoT Random Access
Internet of Things (IoT) plays an important role in the future wireless network where every-thing will be connected [1]. There are two classes of IoT transmission technologies, low-power wide-area (LPWA) and cellular IoT. Generally, LPWA operates in an unlicensed spectrum, while cellular IoT operates in a licensed spectrum. Recently, narrow band in IoT (NB-IoT) has been considered to be a promising technology that provides large coverage and low power consumption for low-throughput low-cost devices in several delay-tolerant applications [2]. As an initial fundamental network function, random access aims to identify a set of active users and to establish resource allocation for transmissions. The random access procedure (RAP) is categorized into two types: the contention-based and the contention-free.
Internet of Things (IoT) plays an important role in the future wireless network where every-thing will be connected [1]. There are two classes of IoT transmission technologies, low-power wide-area (LPWA) and cellular IoT. Generally, LPWA operates in an unlicensed spectrum, while cellular IoT operates in a licensed spectrum. Recently, narrow band in IoT (NB-IoT) has been considered to be a promising technology that provides large coverage and low power consumption for low-throughput low-cost devices in several delay-tolerant applications [2]. As an initial fundamental network function, random access aims to identify a set of active users and to establish resource allocation for transmissions. The random access procedure (RAP) is categorized into two types: the contention-based and the contention-free.
Contention-based random access
Contention-based random access
The contention-based random access procedure (RAP) in LTE consists of four steps [3], where user’s activity is detected in step 2 one while collision and user’s identity are detected in step three. By intentionally repeating preamble transmission in a virtual frame, [4] proposed the expanded-code random access to allow users select a code-word consisting of randomly chosen preamble, which can increase number of available contention resources and then, reduce the number of collision. Later, [5] proposed the signature-based random access to enable detection of user’s identity at the first step and then, helps removing steps two and three. The basic idea is establishing a specific transmission of preamble at users to help BS detect simultaneously user activity and identity and optimize the random access with two-step RAP.
The contention-based random access procedure (RAP) in LTE consists of four steps [3], where user’s activity is detected in step 2 one while collision and user’s identity are detected in step three. By intentionally repeating preamble transmission in a virtual frame, [4] proposed the expanded-code random access to allow users select a code-word consisting of randomly chosen preamble, which can increase number of available contention resources and then, reduce the number of collision. Later, [5] proposed the signature-based random access to enable detection of user’s identity at the first step and then, helps removing steps two and three. The basic idea is establishing a specific transmission of preamble at users to help BS detect simultaneously user activity and identity and optimize the random access with two-step RAP.
Contention-free random access
Contention-free random access
There is some cases that these kind of contention is not acceptable due to some reason (e.g, timing restriction) and these contention can be prevented. Usually in this case, the Network informs each of the user of exactly when and which preamble signature it has to use. Of course, in this case Network will allocate these preamble signature so that it would not collide. This kind of process is called "Contention Free". To initiate the "Contention Free", the user should be in Connected Mode before RAP as in Handover case.
There is some cases that these kind of contention is not acceptable due to some reason (e.g, timing restriction) and these contention can be prevented. Usually in this case, the Network informs each of the user of exactly when and which preamble signature it has to use. Of course, in this case Network will allocate these preamble signature so that it would not collide. This kind of process is called "Contention Free". To initiate the "Contention Free", the user should be in Connected Mode before RAP as in Handover case.
Random access preamble
Random access preamble
The random access preamble is designed such that the base station is able to efficiently detect the transmitting user and estimate any timing offset between the user and base-station (BS) from the received signal. Different from LTE random access where the preamble sequence design is centered on the Zadoff-Chu (ZC) orthogonal sequences [3], the preamble sequence in NB-IoT random access is designed by the single-tone frequency hopping technique [2], [6]. To guarantee a certain preamble detection performance under low transmission power, transmission repetition is required in NB-IoT. Preamble detection in NB-IoT has been studied in [6]–[8], where the algorithm to jointly detect the preamble and estimate the time of arrival (ToA) was proposed in [6], the ToA estimation was later improved in [7] by modifying the hopping pattern and the partial preamble transmission with trade-off between the preamble detection performance and collision was considered in [8]. Recently, the user activity detection has been improved by having massive antennas in multiple-input multiple-output (MIMO) system [9] or having multiple base stations (BSs) in C-RAN system with limited-capacity fronthaul in [10] for contention-free random access and [11] for contention-based random access. The basic idea is to exploit the diversity of multiple BSs and BS's antennas to reduce the transmission power and number of transmission repetition for NB-IoT.
The random access preamble is designed such that the base station is able to efficiently detect the transmitting user and estimate any timing offset between the user and base-station (BS) from the received signal. Different from LTE random access where the preamble sequence design is centered on the Zadoff-Chu (ZC) orthogonal sequences [3], the preamble sequence in NB-IoT random access is designed by the single-tone frequency hopping technique [2], [6]. To guarantee a certain preamble detection performance under low transmission power, transmission repetition is required in NB-IoT. Preamble detection in NB-IoT has been studied in [6]–[8], where the algorithm to jointly detect the preamble and estimate the time of arrival (ToA) was proposed in [6], the ToA estimation was later improved in [7] by modifying the hopping pattern and the partial preamble transmission with trade-off between the preamble detection performance and collision was considered in [8]. Recently, the user activity detection has been improved by having massive antennas in multiple-input multiple-output (MIMO) system [9] or having multiple base stations (BSs) in C-RAN system with limited-capacity fronthaul in [10] for contention-free random access and [11] for contention-based random access. The basic idea is to exploit the diversity of multiple BSs and BS's antennas to reduce the transmission power and number of transmission repetition for NB-IoT.
References:
References:
[1] M. R. Palattella, M. Dohler, A. Grieco, G. Rizzo, J. Torsner, T. Engel, and L. Ladid, “Internet of things in the 5G era: Enablers, architecture, and business models,” IEEE Journal on Selected Areas in Communications , vol. 34, no. 3, pp. 510–527, 2016. (Click here!)
[1] M. R. Palattella, M. Dohler, A. Grieco, G. Rizzo, J. Torsner, T. Engel, and L. Ladid, “Internet of things in the 5G era: Enablers, architecture, and business models,” IEEE Journal on Selected Areas in Communications , vol. 34, no. 3, pp. 510–527, 2016. (Click here!)
[2] O. Liberg, M. Sundberg, E. Wang, J. Bergman, and J. Sachs, Cellular Internet of Things: Technologies, Standards, and Performance. Academic Press, 2017. (Click here!)
[2] O. Liberg, M. Sundberg, E. Wang, J. Bergman, and J. Sachs, Cellular Internet of Things: Technologies, Standards, and Performance. Academic Press, 2017. (Click here!)
[3] S. Sesia, M. Baker, and I. Toufik, LTE-the UMTS long term evolution: from theory to practice. John Wiley & Sons, 2011. (Click here!)
[3] S. Sesia, M. Baker, and I. Toufik, LTE-the UMTS long term evolution: from theory to practice. John Wiley & Sons, 2011. (Click here!)
[4] N. K. Pratas, H. Thomsen, ˇC. Stefanovíc, and P. Popovski, “Code-expanded random access for machine-type communications,” in 2012 IEEE Globecom Workshops, pp. 1681–1686, IEEE, 2012. (Click here!)
[4] N. K. Pratas, H. Thomsen, ˇC. Stefanovíc, and P. Popovski, “Code-expanded random access for machine-type communications,” in 2012 IEEE Globecom Workshops, pp. 1681–1686, IEEE, 2012. (Click here!)
[5] N. K. Pratas, C. Stefanovic, G. C. Maduẽno, and P. Popovski, “Random access for machine-type communication based on bloom filtering,” CoRR , vol. abs/1511.04930, 2015. (Click here!)
[5] N. K. Pratas, C. Stefanovic, G. C. Maduẽno, and P. Popovski, “Random access for machine-type communication based on bloom filtering,” CoRR , vol. abs/1511.04930, 2015. (Click here!)
[6] X. Lin, A. Adhikary, and Y. P. E. Wang, “Random access preamble design and detection for 3GPP narrowband IoT systems,” IEEE Wireless Communications Letters, vol. 5, pp. 640–643, Dec 2016. (Click here!)
[6] X. Lin, A. Adhikary, and Y. P. E. Wang, “Random access preamble design and detection for 3GPP narrowband IoT systems,” IEEE Wireless Communications Letters, vol. 5, pp. 640–643, Dec 2016. (Click here!)
[7] W. S. Jeon, S. B. Seo, and D. G. Jeong, “Effective frequency hopping pattern for ToA estimation in NB-IoT random access,” IEEE Transactions on Vehicular Technology, pp. 1–1, 2018. (Click here!)
[7] W. S. Jeon, S. B. Seo, and D. G. Jeong, “Effective frequency hopping pattern for ToA estimation in NB-IoT random access,” IEEE Transactions on Vehicular Technology, pp. 1–1, 2018. (Click here!)
[8] T. Kim, D. M. Kim, N. Pratas, P. Popovski, and D. K. Sung, “An enhanced access reservation protocol with a partial preamble transmission mechanism in NB-IoT systems,” IEEE Communications Letters, vol. 21, pp. 2270–2273, Oct 2017. (Click here!)
[8] T. Kim, D. M. Kim, N. Pratas, P. Popovski, and D. K. Sung, “An enhanced access reservation protocol with a partial preamble transmission mechanism in NB-IoT systems,” IEEE Communications Letters, vol. 21, pp. 2270–2273, Oct 2017. (Click here!)
[9] L. Liu and W. Yu, “Massive connectivity with massive MIMO - Part I: Device activity detection and channel estimation,” IEEE Transactions on Signal Processing, vol. 66, pp. 2933–2946, June 2018. (Click here!)
[9] L. Liu and W. Yu, “Massive connectivity with massive MIMO - Part I: Device activity detection and channel estimation,” IEEE Transactions on Signal Processing, vol. 66, pp. 2933–2946, June 2018. (Click here!)
[10] Z. Utkovski, O. Simeone, T. Dimitrova, and P. Popovski, “Random access in C-RAN for user activity detection with limited-capacity fronthaul,” IEEE Signal Processing Letters, vol. 24, no. 1, pp. 17–21, 2017. (Click here!)
[10] Z. Utkovski, O. Simeone, T. Dimitrova, and P. Popovski, “Random access in C-RAN for user activity detection with limited-capacity fronthaul,” IEEE Signal Processing Letters, vol. 24, no. 1, pp. 17–21, 2017. (Click here!)
[11] Hien Ta, Sang Wu Kim, Zhengdao Wang, Jimmy J. Nielsen and Petar Popovski, 'Preamble detection in NB-IoT random access with limited-capacity backhaul' IEEE Conference on Communications, May 2019 - Click here!.
[11] Hien Ta, Sang Wu Kim, Zhengdao Wang, Jimmy J. Nielsen and Petar Popovski, 'Preamble detection in NB-IoT random access with limited-capacity backhaul' IEEE Conference on Communications, May 2019 - Click here!.
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