Strong User Research Articles

Exploiting SWIPT-Enabled IoT-Based Cognitive Nonorthogonal Multiple Access With Coordinated Direct and Relay Transmission

This article proposes a simultaneous wireless information and power transfer (SWIPT)-enabled Internet of Things (IoT)-based cognitive nonorthogonal multiple access (NOMA) with coordinated direct and relay transmission (CDRT) system. It incorporates overlay cognitive radio (CR) and time switching (TS)-based SWIPT technology to enhance spectrum utilization and energy efficiency (EE). The proposed system comprises a primary network having a primary transmitter and its intended NOMA receivers (UE1 and UE2), accompanied by an energy-constrained secondary transmitter (ST) and its designated receiver (IoT-U). The primary transmitter communicates directly with its strong user UE1 and exploits the ST as an IoT relay to communicate with a weak user UE2. The IoT-relay node employs a TS-based receiver architecture and a decode-and-forward (DF) protocol to convey the weak user’s information along with its own information by following the NOMA principle. We evaluate the performance of the proposed system by considering both the perfect and imperfect successive interference cancellation (SIC) at the legitimate users over Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${m}$ </tex-math></inline-formula> fading in terms of outage probability (OP), system throughput, and EE. Moreover, we propose an iterative algorithm to minimize the OP by optimizing the TS factor. Furthermore, the impact of key parameters is also highlighted, which lays the guidelines for the practical design of energy-efficient and spectrum-efficient futuristic wireless communication networks.

Improper Gaussian Signaling for Downlink NOMA Systems With Imperfect Successive Interference Cancellation

Non-orthogonal multiple access (NOMA) exhibits superiority in spectrum efficiency which is particularly essential in the Internet of Things (IoT) system involving massive number of device connections. This paper addresses the achievable rate improvement for the downlink NOMA system, in the context of imperfect successive interference cancellation (SIC), by means of the improper Gaussian signaling (IGS) technique. We investigate a basic scenario where the strong user transmits the conventional proper data, while the weak user adopts an improper signaling scheme. The users’ data rates are first formulated in terms of the impropriety degree of the IGS, under residual interference introduced by the imperfect SIC. In this way, analytical expressions for the best improper transmission can be characterized by jointly optimizing the user’s power and the impropriety degree, where their sufficient and necessary conditions are provided. When the strong user transmits with its maximum power, the IGS scheme always increases the achievable rate of the strong user while the weak user may also benefit. When the weak user transmits with its maximum power, such a scheme enables us optimize the achievable rate of the strong user under various levels of channel-to-noise ratios (CNR) and imperfect SIC. Finally, when both the users are imposed by quality of service (QoS) constraints, a Q-learning based solution is proposed to maximize their sum rate. Simulations on the downlink NOMA system support the analysis.

Cooperative NOMA-Based User Pairing for URLLC: A Max–Min Fairness Approach

In this article, cooperative nonorthogonal multiple access (C-NOMA) is considered in short packet communications with finite blocklength codes. The performance of a decode-and-forward relaying along with selection combining (SC) and maximum ratio combining (MRC) strategies at the receiver side is examined. We explore joint user pairing and resource allocation to maximize fair throughput in a downlink scenario. In each pair, the user with a stronger channel (strong user) acts as a relay for the other one (weak user), and optimal power and blocklength are allocated to achieve max–min throughput. To this end, first, only one pair is considered, and optimal resource allocation is explored. Also, a suboptimal algorithm is suggested, which converges to a near-optimal solution. Finally, the problem is extended to a general scenario, and a suboptimal C-NOMA-based user pairing is proposed. Numerical results show that the proposed C-NOMA scheme in both SC and MRC strategies significantly improves the users’ fair throughput compared to the NOMA and orthogonal multiple access (OMA). It is also investigated that the proposed pairing scheme based on C-NOMA outperforms the hybrid NOMA/OMA scheme from the average throughput perspective, while the fairness index degrades slightly.

Empowering Intelligent Surfaces and User Pairing for IoT Relaying Systems: Outage Probability and Ergodic Capacity Performance

The evolution of Internet of Things (IoT) networks has been studied owing to the associated benefits in useful applications. Although the evolution is highly helpful, the increasing day-to-day demands of mobile users have led to immense requirements for further performance improvements such as efficient spectrum utilization, massive device connectivity, and high data rates. Fortunately, reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) techniques have recently been introduced as two possible current-generation emerging technologies with immense potential of addressing the above-mentioned issues. In this paper, we propose the integration of RIS to the existing techniques (i.e., NOMA and relaying) to further enhance the performance for mobile users. We focus on a performance analysis of two-user group by exploiting two main performance metrics including outage probability and ergodic capacity. We provide closed-form expressions for both performance metrics to highlight how NOMA-aided RIS systems provide more benefits compared with the benchmark based on traditional orthogonal multiple access (OMA). Monte-Carlo simulations are performed to validate the correctness of obtained expressions. The simulations show that power allocation factors assigned to two users play a major role in the formation of a performance gap among two users rather than the setting of RIS. In particular, the strong user achieves optimal outage behavior when it is allocated 35% transmit power.

Using contextual knowledge in interactive fault localization

Tool support for automated fault localization in program debugging is limited because state-of-the-art algorithms often fail to provide efficient help to the user. They usually offer a ranked list of suspicious code elements, but the fault is not guaranteed to be found among the highest ranks. In Spectrum-Based Fault Localization (SBFL) – which uses code coverage information of test cases and their execution outcomes to calculate the ranks –, the developer has to investigate several locations before finding the faulty code element. Yet, all the knowledge she a priori has or acquires during this process is not reused by the SBFL tool. There are existing approaches in which the developer interacts with the SBFL algorithm by giving feedback on the elements of the prioritized list. We propose a new approach called iFL which extends interactive approaches by exploiting contextual knowledge of the user about the next item in the ranked list (e. g., a statement), with which larger code entities (e. g., a whole function) can be repositioned in their suspiciousness. We implemented a closely related algorithm proposed by Gong et al., called Talk. First, we evaluated iFL using simulated users, and compared the results to SBFL and Talk. Next, we introduced two types of imperfections in the simulation: user’s knowledge and confidence levels. On SIR and Defects4J, results showed notable improvements in fault localization efficiency, even with strong user imperfections. We then empirically evaluated the effectiveness of the approach with real users in two sets of experiments: a quantitative evaluation of the successfulness of using iFL, and a qualitative evaluation of practical uses of the approach with experienced developers in think-aloud sessions.

Secure PD-NOMA with Multi-User Cooperation and User Clustering in Both Uplink and Downlink PD-NOMA

The power domain non-orthogonal multiple access (PD-NOMA) scheme has gained tremendous interest with the multiple access behavior for fifth-generation (5G) wireless communication. Although the overall performance is improved through accurate power distribution among users’ signals, it depends on the user clustering strategy. Moreover, the PD-NOMA communication is not completely secured due to its broadcast nature, which is still a major problem. This paper presents a novel low-complexity short code-based technique utilized by the registered users and the 5G base station (gNodeB) for communication. By doing so, the PD-NOMA scheme is made secure from unregistered users or eavesdroppers. We proposed a three-step user clustering strategy that selects the best cluster among all the possible clusters to improve the overall performance. The proposed clustering strategy achieves a low outage probability in PD-NOMA systems. Moreover, it uses a multi-user decode and forward cooperative relaying scheme with PD-NOMA (Cop-PD-NOMA) to increase the coverage range of the gNodeB. In the multi-user Cop-PD-NOMA, the strong users (near users) are used as relay stations to aid the weak users (far users) by the decode and forward (D&amp;F) technique. The proposed work provides a secure PD-NOMA network and the most effective user clustering approach during validation. The bit-error-rate (BER) comparisons demonstrate that multi-user cooperation outperforms single-user cooperation in Cop-PD-NOMA communication.

Implementation of Block-Level Double Encryption Based on Machine Learning Techniques for Attack Detection and Prevention

Cloud computing is one of the most important business models of modern information technology. It provides a minimum of various services to the user interaction and low cost (hardware and software). Cloud services are based on the newline architectures on virtualization by using the multitenancy for better resource management and newline strong isolation between several virtual machines (VMs). The spying on a victim VM is challenging, particularly when one wants to use per-core microarchitectural features as a side channel. For example, the cache contains the most potential for damaging side channels, but shared information across different cores affects the cloud information. To overcome this problem, propose the Secure Block-Level Double Encryption (SBLDE) algorithm for user signature verification in the cloud server. It uses identity-based detection techniques to monitor the colocated VMs to identify abnormal cache data and channel behaviors typically during VM data transformation. The identity-based linear classification (IBLC) method is used for classifying the attacker channel when the data is transferred/retrieved from the VM cloud server. This cloud controller finds the channel misbehavior to block the port or channel, changing other available ports’ communication. The service verification provides strong user access permission on the cloud server when the unknown request to the cloud server suddenly executes the key authentication to verify the user permission. This linear classification trains the existing side-channel attack datasets to the classifier and identifies the VM cloud’s attack channel. The study focused on preventing attacks from interrupting the system and serves as an effective means for cross-VM side-channel attacks. This proposed method protects the cloud data and prevents cross-VM channel attack detection efficiently, compared to other existing methods. In this overall proposed method, SBLDE’s performance is to be evaluated and then compared with the existing method.

Deep learning–based resource allocation for secure transmission in a non-orthogonal multiple access network

Machine learning techniques, especially deep learning algorithms have been widely utilized to deal with different kinds of research problems in wireless communications. In this article, we investigate the secrecy rate maximization problem in a non-orthogonal multiple access network based on deep learning approach. In this non-orthogonal multiple access network, the base station intends to transmit two integrated information: a confidential information to user 1 (the strong user) and a broadcast information to user 1 and user 2. In addition, there exists an eavesdropper that intends to decode the confidential information due to the broadcast nature of radio waves. Hence, we formulate the optimization problem as a secrecy rate maximization problem. We first solve this problem by employing convex optimization technique, then we generate the training, validation, and test dataset. We propose a deep neural network–based approach to learn to optimize the resource allocations. The advantages of the proposed deep neural network are the capabilities to achieve low complexity and latency resource allocations. Simulation results are provided to show that the proposed deep neural network approach is capable of reaching near-optimal secrecy rate performance with significantly reduced computational time, when compared with the benchmark conventional approach.

Safeguarding Non-Orthogonal Multiple Access with Physical Layer Techniques

This article clarifies pivotal security issues in the context of non-orthogonal multiple access (NOMA) technology and presents potential methodologies to address them at the physical layer. Specifically, we first clarify the channel conditions for an external eavesdropper to use successive interference cancellation (SIC) for cancelling interference, which has recently been considered in the literature of physical layer security for NOMA. We then explicitly demonstrate the advantages and drawbacks of using NOMA to achieve wireless communication security; that is, NOMA improves the security of a strong user, but reduces the security of a weak user. Finally, we discuss a strategy to protect the confidentiality of a weak user's information from a strong user, while still allowing the latter to seek SIC for harnessing the benefits of NOMA. Research challenges and future works along the aforementioned three different aspects of security issues in NOMA are presented in this article.

Pilot Allocation and Data Power Optimization Based on Access Point Selection in Cell-Free Massive MIMO

Focusing on the pilot contamination problem of cell-free massive multi-input multi-output (MIMO), a pilot allocation algorithm based on access point (AP) selection is proposed. To improve the system performance further, data power optimization is carried out. First, the AP that serves each user is selected through the user-centered idea and the large-scale fading matrix. Use the same service AP numbers between users to measure the pilot contamination intensity and then assign orthogonal pilots to strong potential pilot contamination users. A spectrum efficiency (SE) scheme to maximize the minimum user is proposed for the fairness problem in data power optimization. It is proved that the objective function of data power optimization accords with linear programming, and a dichotomy is given to solve the problem. Simulation results show that the pilot allocation algorithm based on AP selection can significantly improve the total SE of the system and reduce the computational complexity of the system. At the same time, the data power optimization algorithm improves minimum SE for users in the system.

Сигнатура мятежа: как теория СОК позволяет обнаруживать признаки протестной мобилизации в Сети

The purpose of this study is to detect signs of political mobilization in social networks during the period of intensification of internal political struggle (including street actions of the opposition) at the beginning of 2021 in Russia. This study suggests a new quantitative indicator to reveal online communities (networks) characterized by strong user engagement and high level of political mobilization. VK-communities were mapped and analyzed in order to demonstrate the capability of this tool and determine levels of mobilization. The hypothesis of the study was that mobilized communities are able to turn virtual grievances into street protests. The object of study is a set (cluster) of related protest VK-communities (groups/hubs) through which messages from the most influential information donors are brought to public notice on the Internet. The proposed indicator for the calculation of mobilization level is based on the theory of self-organized criticality (SOC). The theory of SOC was initially created to describe a broad class of natural science phenomena, yet it has recently made its way into humanities and social sciences. Timeline of work: from January 10 to April 30, 2021. It was found that some groups (about 10%) in the considered cluster had a high mobilization index during this period. Many of the mobilized groups were very influential: they were both large-scale information donors and highly specialized protest communities. The practical significance of this study lies in improving the methods of monitoring network activity to identify groups that can influence the behavior of their members (both online and on the streets). This study also has theoretical significance related to the accumulation of knowledge about SOC effects in social systems.

A Secure Two-Factor Authentication Framework in Cloud Computing

Cloud computing technology has brought tremendous evaluation in the arena of IT (information technology). This technology paves the path of starting business with lowest investment by availing infrastructure as a service (IAAS), platform as a service (PAAS) and software as a service (SAAS) pay per uses model. Cloud computing services can be quickly and easily provisioned and discharged with minimum efforts and service provider (SP) relationship. Cloud computing characteristics such as on demand self-service, broad network access, resource pooling, and rapid elasticity lead the demand of computing. Despite these features, this platform is free to security issues and attacks specifically in terms of communication because of unsecure authentication and privacy. However, strong user authentication procedure impedes illegal access to the SP which is the principal requirement for securing cloud computing ecosystem. In this regard, we attempt to propose possible counter measures for the cloud ecosystem. Hence, this paper presented a novel one way hash and nonce-based two-factor secure authentication scheme with traditional user IDs, password, and OTP verification procedure that resist brute force attack, session and account hijacking attack, MITM attacks, and replay attacks.

Joint Adaptive M-QAM Modulation and Power Adaptation for a Downlink NOMA Network

In this paper, we study joint adaptive M-QAM modulation and power adaptation for a downlink two-user non-orthogonal multiple access (NOMA) network. Without sacrificing bit error rate (BER), joint adaptive transmission can fully utilize the time-varying nature of wireless channels, by allowing both power and rate to adapt to channel fading. Two adaptive power allocation strategies, namely, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 1</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 2</i> , each of which guarantees the minimum target rate for one user while supporting the highest possible rate for the other, are first proposed. Then, based on the two power schemes, the performance of joint adaptive transmission in terms of average spectral efficiency (SE) is studied for continuous-rate and discrete-rate modulation, while guaranteeing the minimum required rate and BER requirements. With the focus on practical discrete-rate M-QAM modulation, it is proved that for the strong user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 1</i> and the weak user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 2</i> , their average SEs converge to the minimum target rates. In order to further increase the total transmission rate, we then propose a dynamic rate and power adaptation (DRPA) algorithm, aiming to increase the rate of one user without sacrificing the rate of the other. It is shown that at high SNRs, the DRPA algorithm allows the strong user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 1</i> and the weak user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 2</i> to continue to increase their transmission rates until reaching the highest modulation order that the system can support. Hence, the total transmission rate can be greatly increased at high SNRs due to the adoption of DRPA, by allowing both users in each scheme to reach the highest transmission rate in the system.

Hybrid Beamformer Exploiting Multistream per User Transmission for Millimeter-Wave NOMA Communications

This treatise investigates multistream hybrid beamforming (HBF) for a millimeter-wave non-orthogonal multiple access (NOMA) system deployed in a downlink of an urban microcell environment. Maximization problem is developed to optimize sum-rate. For the sake of ensuring high correlation of users’ channels, user’s clustering and ordering are based on the angle of arrivals and users’ channel-weights, respectively. An optimized analog combiner of each user is obtained from the first <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N_{s}$ </tex-math></inline-formula> column vectors of the left unitary matrix derived from the singular value decomposition of the channel of each user. Analog beamformer is matched to the phase of the strong users ’ composite intermediate analog channel to maximize the beamforming gain. Both the analog combiner and precoder for sub-connected structure (SCS) are formulated via a novel dominant sub-array matrix elements’ extractor. Conventional zero-forcing processing is contemplated for digital precoding. Memory space complexity is evaluated to corroborate the simplicity of the proposed schemes’ computational complexity. Results obtained from the simulation exhibit that HBF-NOMA attain superior sum-rate than HBF-orthogonal multiple access and conventional multiuser schemes in line of sight link. Lastly, the proposed SCS-HBF-NOMA precoding scheme performs higher than fully connected counterpart in terms of energy efficiency.

A cyclic frequency division non‐orthogonal multiple access system

SummaryIn this paper, we have developed a downlink power domain non‐orthogonal multiple access (NOMA) system based on cyclic frequency division, where interleaved frequency division multiple access (IFDMA) is cyclically combined with NOMA. The newly developed cyclic frequency division NOMA (CFD‐NOMA) system has the benefit of both NOMA and IFDMA. The concept of superposed multiuser principle for non‐orthogonal resource allocation is used in each NOMA cluster, and the users' data associated with different clusters are separated based on IFDMA. Extreme channel conditions are considered among the users in each cluster. Based on channel gain, the users are differentiated as strong and cell edge users. At the strong user terminal, successive interference cancelation (SIC) is applied to decode the strong user data with the aid of the cell edge user data found from a hard decision, whereas the cell edge user terminal detects its signal only through the hard decision. The near‐far effect of the users present in a cluster, the amount of difference among their channel gain, and transmission power play an important role in detecting the cell edge and the strong users. The CFD‐NOMA system inherits an effective use of multipath channel, thereby reaps an increased cell edge user performance in terms of bit error rate (BER).

Open-source Software Sustainability Models: Initial White Paper From the Informatics Technology for Cancer Research Sustainability and Industry Partnership Working Group.

BackgroundThe National Cancer Institute Informatics Technology for Cancer Research (ITCR) program provides a series of funding mechanisms to create an ecosystem of open-source software (OSS) that serves the needs of cancer research. As the ITCR ecosystem substantially grows, it faces the challenge of the long-term sustainability of the software being developed by ITCR grantees. To address this challenge, the ITCR sustainability and industry partnership working group (SIP-WG) was convened in 2019.ObjectiveThe charter of the SIP-WG is to investigate options to enhance the long-term sustainability of the OSS being developed by ITCR, in part by developing a collection of business model archetypes that can serve as sustainability plans for ITCR OSS development initiatives. The working group assembled models from the ITCR program, from other studies, and from the engagement of its extensive network of relationships with other organizations (eg, Chan Zuckerberg Initiative, Open Source Initiative, and Software Sustainability Institute) in support of this objective.MethodsThis paper reviews the existing sustainability models and describes 10 OSS use cases disseminated by the SIP-WG and others, including 3D Slicer, Bioconductor, Cytoscape, Globus, i2b2 (Informatics for Integrating Biology and the Bedside) and tranSMART, Insight Toolkit, Linux, Observational Health Data Sciences and Informatics tools, R, and REDCap (Research Electronic Data Capture), in 10 sustainability aspects: governance, documentation, code quality, support, ecosystem collaboration, security, legal, finance, marketing, and dependency hygiene.ResultsInformation available to the public reveals that all 10 OSS have effective governance, comprehensive documentation, high code quality, reliable dependency hygiene, strong user and developer support, and active marketing. These OSS include a variety of licensing models (eg, general public license version 2, general public license version 3, Berkeley Software Distribution, and Apache 3) and financial models (eg, federal research funding, industry and membership support, and commercial support). However, detailed information on ecosystem collaboration and security is not publicly provided by most OSS.ConclusionsWe recommend 6 essential attributes for research software: alignment with unmet scientific needs, a dedicated development team, a vibrant user community, a feasible licensing model, a sustainable financial model, and effective product management. We also stress important actions to be considered in future ITCR activities that involve the discussion of the sustainability and licensing models for ITCR OSS, the establishment of a central library, the allocation of consulting resources to code quality control, ecosystem collaboration, security, and dependency hygiene.

A weighted-beam-superposition method for mmWave massive MIMO-NOMA systems

Millimeter wave (mmWave) massive multiple input multiple output (MIMO) and non-orthogonal multiple access (NOMA) are recognized as key technologies in the forthcoming beyond the fifth-generation (B5G) and the sixth-generation (6G) wireless networks. In this paper, we propose a multi-beam MIMO NOMA scheme where each beam is augmented by weighted beam superposition to focus the beam in a manner targeted at each user. This method exploits the full array of antennas within each beam to maximize the gain of each beam. To guarantee fairness for the weak user (lower channel gain) in each group, we use a method of power allocation, which satisfies the weak user with a minimum demanded for the quality of service (QoS). To improve further the sum rate when the QoS of the weak users is satisfied, the coefficient of strong users are set to the largest value. In system simulations, we compare the performance of differnet multi beam schemes, together with a single beam scheme, and a Time Division Multiple Access (TDMA) scheme at different levels of the signal noise ratio (SNR). Based on the simulation results, the proposed method significantly increases system sum rate.

On the Capacity Enlargement of Gaussian Broadcast Channels With Passive Noisy Feedback

It is well known that the capacity region of an average transmit power constrained Gaussian Broadcast Channel (GBC) with independent noise realizations at the receivers is enlarged by the presence of causal noiseless feedback. When the noise variances at the receivers are identical, even passive feedback via independent memoryless Gaussian links can lead to a capacity region enlargement. The last fact remains true even when the feedback noise variance is very high, and available only from one of the receivers. While such capacity enlargements are feasible for several other feedback models in the Gaussian BC setting, it is also known that feedback does not change the capacity region for physically degraded broadcast channels. In this paper, we consider a two user GBC with independent noise realizations at the receivers, where the feedback links from the receivers are corrupted by independent additive Gaussian noise processes. We investigate the set of four noise variances, two forward and two feedback, for which no capacity enlargement is possible. A sharp characterization of this region is derived, i.e., any quadruple outside the presented region will lead to a capacity enlargement, whereas quadruples inside will leave the capacity region unchanged. Our results lead to the conclusion that when the forward noise variances are different, too noisy a feedback from one of the receivers alone is not always beneficial for enlarging the capacity region, be it from the stronger user or the weaker one, in sharp contrast to the case of equal forward noise variances.

Power Allocation for Reliable SIC Detection of Rectangular QAM-based NOMA Systems

This paper considers the power allocation for non-orthogonal multiple access (NOMA) users to enable using the successive interference cancellation (SIC) while providing reliable error performance. The derived closed-form expressions are applicable for arbitrary number of NOMA users each of which has a square or rectangular quadrature amplitude modulation (QAM) constellation with arbitrary order. The obtained numerical results show that power assignment process at the transmitter for the superposition process and at the receiver for the SIC process should be performed meticulously because the power difference between the weakest and strongest users can be tremendous when the number of users or the modulation orders increase. Moreover, the derived expressions can be used to reduce the computational complexity that is required to obtain the optimal power coefficients using brute force methods by significantly reducing the search space.

Driving digital transformation of comprehensive primary health services at scale in India: an enterprise architecture framework

In its commitment towards Sustainable Development Goals, India envisages comprehensive primary health services as a key pillar in achieving universal health coverage. Embedded in siloed vertical programmes, their lack of...