Pub Date : 2023-03-01DOI: 10.1109/WCNC55385.2023.10118899
Fathima Jesbin, Sandesh Rao Mattu, A. Chockalingam
Traditional orthogonal time frequency space (OTFS) channel estimation schemes dedicate an entire frame or a part of the frame for accommodating pilot and guard symbols to avoid pilot-data interference, which compromises spectral efficiency. This spectral efficiency loss can be avoided using superimposed pilots, where delay-Doppler (DD) bins in the OTFS frame carries both data and pilot symbols. In this paper, we propose a sparse superimposed pilot scheme for channel estimation, where all the DD bins in a frame carry data symbols and pilot symbols are superimposed over some of them, sparsely. The proposed scheme does not suffer spectral efficiency loss due to pilot/guard symbols. It also has the advantage of more localized pilot-data interference profile that leads to better performance. We derive the minimum mean square error (MMSE) channel estimator for the proposed scheme. We obtain optimum number of pilot symbols per frame and power distribution among data and pilot symbols through simulations. Simulation results show that the proposed scheme achieves better performance at a lesser complexity compared to existing superimposed pilot scheme. An iterative scheme that further improves performance is also proposed.
{"title":"Sparse Superimposed Pilot Based Channel Estimation in OTFS Systems","authors":"Fathima Jesbin, Sandesh Rao Mattu, A. Chockalingam","doi":"10.1109/WCNC55385.2023.10118899","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118899","url":null,"abstract":"Traditional orthogonal time frequency space (OTFS) channel estimation schemes dedicate an entire frame or a part of the frame for accommodating pilot and guard symbols to avoid pilot-data interference, which compromises spectral efficiency. This spectral efficiency loss can be avoided using superimposed pilots, where delay-Doppler (DD) bins in the OTFS frame carries both data and pilot symbols. In this paper, we propose a sparse superimposed pilot scheme for channel estimation, where all the DD bins in a frame carry data symbols and pilot symbols are superimposed over some of them, sparsely. The proposed scheme does not suffer spectral efficiency loss due to pilot/guard symbols. It also has the advantage of more localized pilot-data interference profile that leads to better performance. We derive the minimum mean square error (MMSE) channel estimator for the proposed scheme. We obtain optimum number of pilot symbols per frame and power distribution among data and pilot symbols through simulations. Simulation results show that the proposed scheme achieves better performance at a lesser complexity compared to existing superimposed pilot scheme. An iterative scheme that further improves performance is also proposed.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133014761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1109/WCNC55385.2023.10119026
Rubing Yao, Zhiqing Wei, Liyan Su, L. Wang, Zhiyong Feng
This paper designs a low peak-to-average power ratio (PAPR) Integrated Sensing and Communication (ISAC) waveform based on OFDM. Firstly, we propose an ISAC waveform structure, in which radar subcarriers within the OFDM symbols are randomly located anywhere within non-contiguous Physical Resource Blocks (PRBs). Using this OFDM-based ISAC waveform structure, the sensing mutual information (MI) between the radar channel and the received waveform is derived and maximized under the constraints of communication data information rate (DIR), PAPR, and transmit power. Then, an optimization algorithm is proposed to obtain the optimal power allocation of subcarriers. Finally, simulation results verify the effectiveness and flexibility of our designed waveform.
{"title":"Low-PAPR Integrated Sensing and Communication Waveform Design","authors":"Rubing Yao, Zhiqing Wei, Liyan Su, L. Wang, Zhiyong Feng","doi":"10.1109/WCNC55385.2023.10119026","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10119026","url":null,"abstract":"This paper designs a low peak-to-average power ratio (PAPR) Integrated Sensing and Communication (ISAC) waveform based on OFDM. Firstly, we propose an ISAC waveform structure, in which radar subcarriers within the OFDM symbols are randomly located anywhere within non-contiguous Physical Resource Blocks (PRBs). Using this OFDM-based ISAC waveform structure, the sensing mutual information (MI) between the radar channel and the received waveform is derived and maximized under the constraints of communication data information rate (DIR), PAPR, and transmit power. Then, an optimization algorithm is proposed to obtain the optimal power allocation of subcarriers. Finally, simulation results verify the effectiveness and flexibility of our designed waveform.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"606 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132150265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1109/WCNC55385.2023.10118824
Philipp Geuer, Alexandros Palaios, Roman Zhohov
Cellular networks evolve towards future generations, facing unprecedented levels of device and network programmability. At the same time, the new vision of the cyber-physical continuum will rely on diverse network architectures in extremely dense deployments. The emergence of new types of cells, like mobile and drone ones, would rely on instantly available AI/ML algorithms to provide a service within a few seconds after being powered on, avoiding long periods of data collection and training.In this work, we discuss how cell-specific characteristics, like the radio environment, can impact area-based ML models. Even though area-based models simplify the management of ML workflows considerably, there is also a need for cell-based models as these tend to provide better performance. Moreover, we show that area-based models can be part of ML workflow as they can complement cell-based ones. We finalize our work by discussing the possibility of reusing available ML models from other cells as a way of reducing the time needed for applying ML algorithms in newly deployed cells. We provide initial insights on the model re-usability and performance assessment and highlight the need for more research in this direction.In our work, we utilize the data from a test network, allowing us to explore the dynamics of real networks and provide results with increased confidence.
{"title":"Cell- and Area-based ML Models: Unlocking High Precision Models for Radio Access Networks","authors":"Philipp Geuer, Alexandros Palaios, Roman Zhohov","doi":"10.1109/WCNC55385.2023.10118824","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118824","url":null,"abstract":"Cellular networks evolve towards future generations, facing unprecedented levels of device and network programmability. At the same time, the new vision of the cyber-physical continuum will rely on diverse network architectures in extremely dense deployments. The emergence of new types of cells, like mobile and drone ones, would rely on instantly available AI/ML algorithms to provide a service within a few seconds after being powered on, avoiding long periods of data collection and training.In this work, we discuss how cell-specific characteristics, like the radio environment, can impact area-based ML models. Even though area-based models simplify the management of ML workflows considerably, there is also a need for cell-based models as these tend to provide better performance. Moreover, we show that area-based models can be part of ML workflow as they can complement cell-based ones. We finalize our work by discussing the possibility of reusing available ML models from other cells as a way of reducing the time needed for applying ML algorithms in newly deployed cells. We provide initial insights on the model re-usability and performance assessment and highlight the need for more research in this direction.In our work, we utilize the data from a test network, allowing us to explore the dynamics of real networks and provide results with increased confidence.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"279 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130797580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we investigate the reliability of intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) communications in the case of limited UAV energy. Under constraints of the UAV energy and the channel decoding error rate, we formulate a reliability maximization problem by jointly optimizing the IRS’s scheduling, the UAV’s trajectory, the IRS’s phase shift, and the UAV’s transmit power. Since the partial constraints of the problem are strictly nonconvex and its variables are coupling, the problem is difficult to convert to a nonconvex problem. Therefore, we propose a chaotic adaptation hybrid whale optimization algorithm (CAHWOA) to solve the problem. CAHWOA is implemented by using alternately the chaotic adaptation whale optimization algorithm (CAWOA) and the binary optimization algorithm (BWOA). Simulation results demonstrate that the joint optimization of IRS and UAV can improve the system communication reliability by almost 32% compared with the two baseline schemes. CAHWOA can improve the convergence rate by nearly 20% and enhance the optimization-seeking accuracy by about 0.04 compared with the three baseline algorithms.
{"title":"Intelligent Reflecting Surfaces Assisted UAV Reliable Communication","authors":"Haiying Peng, Yu Zheng, Peng He, Yaping Cui, Ruyang Wang, Dapeng Wu, Luo Chen","doi":"10.1109/WCNC55385.2023.10119055","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10119055","url":null,"abstract":"In this paper, we investigate the reliability of intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) communications in the case of limited UAV energy. Under constraints of the UAV energy and the channel decoding error rate, we formulate a reliability maximization problem by jointly optimizing the IRS’s scheduling, the UAV’s trajectory, the IRS’s phase shift, and the UAV’s transmit power. Since the partial constraints of the problem are strictly nonconvex and its variables are coupling, the problem is difficult to convert to a nonconvex problem. Therefore, we propose a chaotic adaptation hybrid whale optimization algorithm (CAHWOA) to solve the problem. CAHWOA is implemented by using alternately the chaotic adaptation whale optimization algorithm (CAWOA) and the binary optimization algorithm (BWOA). Simulation results demonstrate that the joint optimization of IRS and UAV can improve the system communication reliability by almost 32% compared with the two baseline schemes. CAHWOA can improve the convergence rate by nearly 20% and enhance the optimization-seeking accuracy by about 0.04 compared with the three baseline algorithms.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130945017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1109/WCNC55385.2023.10118941
Bin Zhang, Dongheng Zhang, Yang Hu, Yan Chen
Human gesture recognition with WiFi signals has attained acclaim due to the omnipresence, privacy protection, and broad coverage nature of WiFi signals. These gesture recognition systems rely on neural networks trained with a large number of labeled data. However, the recognition model trained with data under certain conditions would suffer from significant performance degradation when applied in practical deployment, which limits the application of gesture recognition systems. In this paper, we propose UDAWiGR, an unsupervised domain adaptation framework for WiFi-based gesture recognition aiming to enhance the performance of the recognition model in new conditions by making effective use of the unlabeled data from new conditions. We first propose a pseudo-labeling method with confidence control constraint to utilize unlabeled data for model training. We then utilize consistency regularization to align the output distribution for enhancing the robustness of neural network under signal perturbations. Furthermore, we propose a cross-match loss to combine the pseudo-labeling and consistency regularization, which makes the whole framework simple yet effective. Extensive experiments demonstrate that the proposed framework could achieve 4.35% accuracy improvement comparing with the state-of-the-art methods on public dataset.
{"title":"Unsupervised Domain Adaptation for WiFi Gesture Recognition","authors":"Bin Zhang, Dongheng Zhang, Yang Hu, Yan Chen","doi":"10.1109/WCNC55385.2023.10118941","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118941","url":null,"abstract":"Human gesture recognition with WiFi signals has attained acclaim due to the omnipresence, privacy protection, and broad coverage nature of WiFi signals. These gesture recognition systems rely on neural networks trained with a large number of labeled data. However, the recognition model trained with data under certain conditions would suffer from significant performance degradation when applied in practical deployment, which limits the application of gesture recognition systems. In this paper, we propose UDAWiGR, an unsupervised domain adaptation framework for WiFi-based gesture recognition aiming to enhance the performance of the recognition model in new conditions by making effective use of the unlabeled data from new conditions. We first propose a pseudo-labeling method with confidence control constraint to utilize unlabeled data for model training. We then utilize consistency regularization to align the output distribution for enhancing the robustness of neural network under signal perturbations. Furthermore, we propose a cross-match loss to combine the pseudo-labeling and consistency regularization, which makes the whole framework simple yet effective. Extensive experiments demonstrate that the proposed framework could achieve 4.35% accuracy improvement comparing with the state-of-the-art methods on public dataset.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129020206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1109/WCNC55385.2023.10118684
Zhuyin Li, Xu Zhu
Localization has always been one of the key issues for security applications. As security systems are turning more intelligent together with the development of smart information technologies, critical requirements for wireless target localization have challenged the traditional positioning techniques, including flexibility, portability, deployment cost, computational efficiency, and estimation accuracy, to name a few. Although the widely- accepted classical algorithm, MUltiple SIgnal Classification (MUSIC), has been proven to be an effective tool for the space-time estimation, it can hardly satisfy localization requirements under such security scenarios due to the high complexity and the bias error led by grid searching. Thus, in this paper, we propose a Joint Angle and Delay Estimation (JADE)-based localization algorithm using only one single portable base station, which eliminates the grid bias with low computational complexity. First, a MUSIC-based coarse JADE approach is proposed; then, a Taylor-series-based refinement method is introduced to eliminate the grid bias; and finally, the target mobile station is localized by the estimated time delay and angle information. The performance is evaluated by numerical simulations under various conditions, compared with five different existing algorithms. Our proposed MT-2D algorithm is proven to achieve a better estimation accuracy for the time delay, angle and position with a relatively low computational cost.
本地化一直是安全应用的关键问题之一。随着智能信息技术的发展，安防系统越来越智能化，对无线目标定位的关键要求对传统的定位技术提出了挑战，包括灵活性、可移植性、部署成本、计算效率和估计精度等。尽管被广泛接受的经典算法多信号分类(MUltiple SIgnal Classification, MUSIC)已被证明是一种有效的时空估计工具，但由于其高复杂度和网格搜索导致的偏置误差，难以满足此类安全场景下的定位要求。因此，在本文中，我们提出了一种基于联合角度和延迟估计(JADE)的定位算法，该算法仅使用一个便携式基站，以较低的计算复杂度消除了网格偏差。首先，提出了一种基于音乐的粗JADE方法;然后，引入基于泰勒级数的细化方法消除网格偏差;最后利用估计的时延和角度信息对目标移动站进行定位。通过各种条件下的数值模拟，比较了五种不同的现有算法的性能。实验证明，本文提出的MT-2D算法对时延、角度和位置有较好的估计精度，且计算成本相对较低。
{"title":"A Portable Base Station Assisted Localization with Grid Bias Elimination","authors":"Zhuyin Li, Xu Zhu","doi":"10.1109/WCNC55385.2023.10118684","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118684","url":null,"abstract":"Localization has always been one of the key issues for security applications. As security systems are turning more intelligent together with the development of smart information technologies, critical requirements for wireless target localization have challenged the traditional positioning techniques, including flexibility, portability, deployment cost, computational efficiency, and estimation accuracy, to name a few. Although the widely- accepted classical algorithm, MUltiple SIgnal Classification (MUSIC), has been proven to be an effective tool for the space-time estimation, it can hardly satisfy localization requirements under such security scenarios due to the high complexity and the bias error led by grid searching. Thus, in this paper, we propose a Joint Angle and Delay Estimation (JADE)-based localization algorithm using only one single portable base station, which eliminates the grid bias with low computational complexity. First, a MUSIC-based coarse JADE approach is proposed; then, a Taylor-series-based refinement method is introduced to eliminate the grid bias; and finally, the target mobile station is localized by the estimated time delay and angle information. The performance is evaluated by numerical simulations under various conditions, compared with five different existing algorithms. Our proposed MT-2D algorithm is proven to achieve a better estimation accuracy for the time delay, angle and position with a relatively low computational cost.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129228190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1109/WCNC55385.2023.10118608
Jingyuan Zhang, D. Blough
Reconfigurable intelligent surfaces (RISs) have been a promising technology to maintain connection performance for millimeter wave (mmWave) communication in non-line-of-sight (NLoS) case by providing an indirect link between access point and user. In this paper, we explore the advantage of multi-RIS deployment to improve connection probability in a scenario with randomly distributed obstacles by solving a modified thinnest covering problem. Optimal RIS deployment in 3D scenario up to six RISs and selection of RIS number based on room size are investigated analytically. A heuristic optimization method of RIS size and orientation is also proposed to guarantee adequate received signal strength. The proposed deployment strategy is validated by simulation that connection probability is significantly improved with only very few RISs.
{"title":"Optimal Placement of Reconfigurable Intelligent Surfaces with Random Obstacle Distribution","authors":"Jingyuan Zhang, D. Blough","doi":"10.1109/WCNC55385.2023.10118608","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118608","url":null,"abstract":"Reconfigurable intelligent surfaces (RISs) have been a promising technology to maintain connection performance for millimeter wave (mmWave) communication in non-line-of-sight (NLoS) case by providing an indirect link between access point and user. In this paper, we explore the advantage of multi-RIS deployment to improve connection probability in a scenario with randomly distributed obstacles by solving a modified thinnest covering problem. Optimal RIS deployment in 3D scenario up to six RISs and selection of RIS number based on room size are investigated analytically. A heuristic optimization method of RIS size and orientation is also proposed to guarantee adequate received signal strength. The proposed deployment strategy is validated by simulation that connection probability is significantly improved with only very few RISs.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126685011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1109/WCNC55385.2023.10118826
Amani Benamor, Oussama Habachi, I. Kammoun, J. Cances
Attracted by the advantages of Non-Orthogonal Multiple Access (NOMA) in accommodating multiple users within the same resources, this paper jointly addresses the resource allocation and power control problem for Machine Type Devices (MTDs) in a Hybrid NOMA system. Particularly, we model the problem using a Mean Field Game (MFG) framework underlying a Multi-Armed Bandit (MAB) approach. Firstly, the devices invoke the MAB tool to arrange themselves into multiple NOMA coalitions. Then, within each coalition, the MTDs apply the MFG approach to autonomously adjust their transmit power based on limited feedback received from the Base Station (BS). Simulation results are given to illustrate the equilibrium behavior of the proposed resource allocation algorithm and to underline its robustness compared to existing works in the literature.
{"title":"Multi-Armed Bandit Framework for Resource Allocation in Uplink NOMA Networks","authors":"Amani Benamor, Oussama Habachi, I. Kammoun, J. Cances","doi":"10.1109/WCNC55385.2023.10118826","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118826","url":null,"abstract":"Attracted by the advantages of Non-Orthogonal Multiple Access (NOMA) in accommodating multiple users within the same resources, this paper jointly addresses the resource allocation and power control problem for Machine Type Devices (MTDs) in a Hybrid NOMA system. Particularly, we model the problem using a Mean Field Game (MFG) framework underlying a Multi-Armed Bandit (MAB) approach. Firstly, the devices invoke the MAB tool to arrange themselves into multiple NOMA coalitions. Then, within each coalition, the MTDs apply the MFG approach to autonomously adjust their transmit power based on limited feedback received from the Base Station (BS). Simulation results are given to illustrate the equilibrium behavior of the proposed resource allocation algorithm and to underline its robustness compared to existing works in the literature.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126221476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the rapid development of wireless communications, integrated sensing and communication (ISAC) has attracted considerable attentions, which enables both data transmission and target detection simultaneously by spectrum sharing. The adaptive Orthogonal Frequency Division Multiplexing (OFDM) shared waveform design can dynamically adjust power allocation based on the preferences of the radar or communication system, which achieves optimal ISAC performance with given static channel conditions. For the perfect channel state information (CSI) is hard to obtain due to the feedback errors, we then propose a robust OFDM shared waveform design, which achieves better performance under the worst-case channel states. The Karush-Kuhn-Tucker (KKT) conditions are formulated and an improved greedy algorithm is introduced to adjust the bit and power allocation on each subcarrier adaptively. Theoretical analysis and simulation results verify the effectiveness of the proposed algorithm for the joint optimization of both radar and communication systems.
{"title":"Robust OFDM Shared Waveform Design and Resource Allocation for the Integrated Sensing and Communication System","authors":"Xinyue Cao, Liang Tang, Fei Shen, Yueyue Zhang, Feng Yan, Chao Wang","doi":"10.1109/WCNC55385.2023.10118730","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118730","url":null,"abstract":"With the rapid development of wireless communications, integrated sensing and communication (ISAC) has attracted considerable attentions, which enables both data transmission and target detection simultaneously by spectrum sharing. The adaptive Orthogonal Frequency Division Multiplexing (OFDM) shared waveform design can dynamically adjust power allocation based on the preferences of the radar or communication system, which achieves optimal ISAC performance with given static channel conditions. For the perfect channel state information (CSI) is hard to obtain due to the feedback errors, we then propose a robust OFDM shared waveform design, which achieves better performance under the worst-case channel states. The Karush-Kuhn-Tucker (KKT) conditions are formulated and an improved greedy algorithm is introduced to adjust the bit and power allocation on each subcarrier adaptively. Theoretical analysis and simulation results verify the effectiveness of the proposed algorithm for the joint optimization of both radar and communication systems.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121445653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1109/WCNC55385.2023.10118636
Elmehdi Illi, M. Qaraqe, Faissal El Bouanani, S. Al-Kuwari
In this paper, the secrecy of a dual-hop unmanned aerial vehicle-based wireless communication system, in the presence of mobility and imperfect channel state information (CSI), is investigated. The system consists of a decode-and-forward relay connecting a source and destination node. The transmission is performed under the presence of two eavesdroppers aiming to intercept independently the source-relay and source-destination communication channels. It is assumed that the transmitters are equipped with one transmit antenna, while the receivers have multiple receive antennas. Based on the statistical properties of the per-hop signal-to-noise ratio (SNR), a closed-form formula for the network’s secrecy intercept probability (IP) is derived, in terms of the main system and channel parameters. The results correlate the impact of such parameters on the secrecy level of the system, where the latter can be enhanced by increasing the number of antennas at the legitimate receivers and the average SNRs of the legitimate links. Furthermore, it is shown that as the CSI imperfection level, nodes’ speed, delay, and carrier frequency increase, the system’s secrecy degrades. All the derived results are verified through Monte Carlo simulations.
{"title":"Secrecy Analysis of a Dual-Hop Wireless Network with Independent Eavesdroppers and Outdated CSI","authors":"Elmehdi Illi, M. Qaraqe, Faissal El Bouanani, S. Al-Kuwari","doi":"10.1109/WCNC55385.2023.10118636","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118636","url":null,"abstract":"In this paper, the secrecy of a dual-hop unmanned aerial vehicle-based wireless communication system, in the presence of mobility and imperfect channel state information (CSI), is investigated. The system consists of a decode-and-forward relay connecting a source and destination node. The transmission is performed under the presence of two eavesdroppers aiming to intercept independently the source-relay and source-destination communication channels. It is assumed that the transmitters are equipped with one transmit antenna, while the receivers have multiple receive antennas. Based on the statistical properties of the per-hop signal-to-noise ratio (SNR), a closed-form formula for the network’s secrecy intercept probability (IP) is derived, in terms of the main system and channel parameters. The results correlate the impact of such parameters on the secrecy level of the system, where the latter can be enhanced by increasing the number of antennas at the legitimate receivers and the average SNRs of the legitimate links. Furthermore, it is shown that as the CSI imperfection level, nodes’ speed, delay, and carrier frequency increase, the system’s secrecy degrades. All the derived results are verified through Monte Carlo simulations.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126279458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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