Power Domain Research Articles

Optimal power allocation for NOMA-based Internet of things over OFDM sub bands

As a result of continued expansion of 5G technology, the density of IoT devices has increased dramatically.Increasing the throughput of 5G systems is now extremely important. Non-orthogonal multiple access technologiesand Ultra-dense networks have lately attracted a lot of attention in the context of Internet of Things networksbecause to their capacity to multiplex from the space domain and power domain. In order to boost systemthroughput, this article integrates non-orthogonal multiple access technology with ultra-dense network technology,taking into consideration orthogonal frequency division multiplexing non-orthogonal multiple access-based ultradensenetworks with several base stations. The network model and the channel model were created first. As aresult, under the condition of total power, the downlink transmission rate maximization problem is formulated.Then, the problem is divided into two subproblems to solve: device grouping and sub-band power distributionand built the best power allocation strategies by using convex optimization theory to these subproblems. Finally,numerical simulations are undertaken to validate the efficiency of proposed optimal downlink power distributionapproach and the total throughput of the system has substantially enhanced as compared to orthogonal Multipleaccess.

Exploiting hybrid non‐orthogonal multiple access in satellite–terrestrial systems with randomly deployed users

In this letter, a hybrid non-orthogonal multiple access (NOMA) scheme for satellite–terrestrial systems is proposed, which is capable of integrating both power domain NOMA (PD-NOMA) and code domain NOMA (CD-NOMA) design modes. The stochastic geometry method is considered to model the position of the terrestrial NOMA user. Specifically, the closed-form expressions of exact outage probability with imperfect interference cancellation are derived. In order to get more insights, the asymptotic outage probabilities for high SNR conditions are also discussed. Numerical results are provided to confirm the validity of theoretical analysis and reveal the effects of critical parameters on system performance.

Optical Beam Steerable Visible Light Communication (VLC) System Supporting Multiple Users Using RGB and Orthogonal Frequency Division Multiplexed (OFDM) Non-Orthogonal Multiple Access (NOMA).

In order to achieve high-capacity visible light communication (VLC), five dimensions in physics, including frequency, time, quadrature modulation, space, and polarization can be utilized. Orthogonality should be maintained in order to reduce the crosstalk among different dimensions. In this work, we illustrate a high-capacity 21.01 Gbit/s optical beam steerable VLC system with vibration mitigation based on orthogonal frequency division multiplexed (OFDM) non-orthogonal multiple access (NOMA) signals using red, green, and blue (RGB) laser-diodes (LDs). The OFDM-NOMA can increase the spectral efficiency of VLC signal by allowing high overlapping of different data channel spectra in the power domain to maximize the bandwidth utilization. In the NOMA scheme, different data channels are digitally multiplexed using different levels of power with superposition coding at the transmitter (Tx). Successive interference cancellation (SIC) is then utilized at the receiver (Rx) to retrieve different power multiplexed data channels. The total data rates (i.e., Data 1 and Data 2) achieved by the R/G/B OFDM-NOMA channels are 8.07, 6.62, and 6.32 Gbit/s, respectively, achieving an aggregated data rate of 21.01 Gbit/s. The corresponding average signal-to-noise ratios (SNRs) of Data 1 in the R, G, and B channels are 9.05, 9.18 and 8.94 dB, respectively, while that of Data 2 in the R, G, and B channels are 14.92, 14.29, and 13.80 dB, respectively.

The effect of quantized ETF, grouping, and power allocation on non-orthogonal multiple accesses for wireless communication networks

Nonorthogonal multiple access (NOMA) is a significant technology in radio resource sharing and it has been recognized as a favorable method in fifth-generation (5G) wireless networks to meet the requirements of system capacity, service latency, and user connectivity. Many schemes for NOMA have been proposed in the last few years. such as transmitter linear spreading-based NOMA as a code domain, as well as a linear minimum mean square error (LMMSE), parallel interference cancellation (PIC), and serial interference cancellation (SIC) with power allocation and grouping as a power domain at the receiver side for uplink NOMA. This work aims to evaluate the performance of multiple types of linear spreading-based NOMA schemes. Simulations are achieved for the error-rate performance evaluation of these NOMA schemes, received signal after detection, and received signal and effect of every user on the other. Evaluating the performance of these technologies with comparison is also achieved through using grouping and power allocation. Simulations are achieved for the sum rate and spectral efficiency. For the future, 5G NOMA development, an equiangular tight frame (ETF) is suggested for improving performance and suggests grouping with 64qam-quantized Grassmannian for improving performance favorite about grouping with Generalized welch-bound equality (GWBE)

NOMA -Spatial Modulation: Solving Power Allocation Issue via Improved Black Widow Optimization

Developing next-generation multiple access (MA) schemes that can provide high spectral efficiency (SE) and a higher connection scale is crucial for managing the unpredictable traffic expansion of next-generation wireless interactions. Non-orthogonal multiple access (NOMA) in the power domain has recently been the subject of in-depth research. To minimize either the average or maximum symbol error rate (SER), this work develops a novel NOMA-based SM system that considers power allocation. The new perception, which guarantees higher throughput, is NOMA-APM with scrambling in this context. A more advanced or better optimization approach addresses this optimization problem. Here, Black Widow Optimization with New Mating Behavior (BWO-NMB) is deployed for attaining minimal error and power utilization. Eventually, the enhancement of BWO-NMB based technique is confirmed over other schemes as well as for with and without AS.

Analysis of Peak to Average Power in the 5G NOMA-FBMC Waveform

Objectives: In this work, we investigate suitable techniques to reduce the Peak to Average Power Ratio (PAPR) for advanced modulation schemes in order to obtain better performance than current or commonly used modulation schemes for Fourth Generation (4G) and Fifth Generation (5G). Methods: The proposed scheme incorporates a combination of Selective Mapping (SLM) and Partial Transmission Scheme (PTS) and thereby efficiently minimizes the PAPR and the complexity of the framework. Further, it is seen that the proposed algorithm is crucial to achieving better spectral and power characteristics compared with the existing waveforms. Findings: The comparative results of the bit error rate (BER) and PAPR of the advanced SLM-PTS when applied to the OFDM, FBMC, NOMA, and NOMA-FBMC structures are shown, and it is found that the power and complexity are significantly decreased in the advanced waveforms, which makes the proposed algorithm efficient for the advanced waveforms. Novelty: A natural motivation for future modulation schemes is to harmoniously merge the newer modulation technique, Filter Bank Multi Carrier (FBMC), with the Non-Orthogonal Multiple Access (NOMA) framework. This has led to a recent modulation paradigm called FBMC-NOMA, wherein the NOMA power domain principle is applied to a group of FMBC modulated signals. The proposed SLM-PTS-based NOMA-FBMC structure efficiently enhances the throughput and PAPR performance for 5G and beyond 5G systems. Keywords: PAPR; FBMC; SLM; PTS; NOMA

Towards Low-Power Machine Learning Architectures Inspired by Brain Neuromodulatory Signalling

We present a transfer learning method inspired by modulatory neurotransmitter mechanisms in biological brains and explore applications for neuromorphic hardware. In this method, the pre-trained weights of an artificial neural network are held constant and a new, similar task is learned by manipulating the firing sensitivity of each neuron via a supplemental bias input. We refer to this as neuromodulatory tuning (NT). We demonstrate empirically that neuromodulatory tuning produces results comparable with traditional fine-tuning (TFT) methods in the domain of image recognition in both feed-forward deep learning and spiking neural network architectures. In our tests, NT reduced the number of parameters to be trained by four orders of magnitude as compared with traditional fine-tuning methods. We further demonstrate that neuromodulatory tuning can be implemented in analog hardware as a current source with a variable supply voltage. Our analog neuron design implements the leaky integrate-and-fire model with three bi-directional binary-scaled current sources comprising the synapse. Signals approximating modulatory neurotransmitter mechanisms are applied via adjustable power domains associated with each synapse. We validate the feasibility of the circuit design using high-fidelity simulation tools and propose an efficient implementation of neuromodulatory tuning using integrated analog circuits that consume significantly less power than digital hardware (GPU/CPU).

An Ultra-Low-Voltage Bit-Interleaved Synthesizable 13T SRAM Circuit

Standard-cell-based memory (SCM) circuits with fully digital signals are attractive for power-/energy-constrained edge devices due to the strong voltage scaling capability, fast design iteration, and flexibility in integration. In this article, a 13-transistor (13T) static-random access memory (SRAM) circuit with ultra-wide range voltage scaling capability is proposed for ultra-low-power applications. By adopting the concept of SCM, the 13T SRAM cell is custom-designed, while providing fully digital inputs and outputs. Without any analog circuitry, the 13T memory array is fully synthesizable and compatible with the commercial semi-custom design flow. A specialized circuitry is employed in the 13T SRAM cell to enable cell-level bit-interleaving. An 8-kb 13T SRAM bank is fabricated in the UMC 55-nm low power CMOS technology, achieving an area density of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5 \mu \text{m}$ </tex-math></inline-formula> 2/bit. The minimum operational voltage for the 13T SRAM circuit is 324 mV, while the data retention voltage is down to 279 mV. The 13T SRAM circuit achieves the minimum energy point at 0.4 V for both the read (32.8 fJ/bit) and write (54.1 fJ/bit) operations, providing a good opportunity to perform voltage scaling together with logic blocks when embedded in the same power domain.

Optimal transmit antenna selection for non‐orthogonal multiple access with improved lion algorithm

SummaryIn the realm of 5G mobile wireless communication, cognitive radio (CR) plays an important role in improving radio spectrum efficiency by overcoming challenges such as spectrum shortage versus under‐utilization associated with the traditional fixed frequency assignment. “Interweave CR, underlay CR, and overlay CR” are the three primary paradigmatics in general. The present study focuses on the overlay CR paradigm, wherein secondary users (SUs) have all been expected to be provided with superior “encoding and signal processing techniques” to improve primary users' (PUs') communication. Furthermore, to address concerns associated with inefficient spectrum usage, multiplexing methods like “non‐orthogonal multiple access (NOMA) and spatial modulation (SM)” have been implemented. NOMA makes use of the power domain to maximize spectrum usage, whereas SM makes use of the spatial domain. Multiple antennas, on the other hand, are expensive in terms of energy, magnitude, and equipment. Antenna selection is a low‐cost, low‐complexity method of capturing many of the NOMA system's advantages. As a consequence, this study offers the fitness familiarized lion algorithm (FFLA), a novel methodology for selecting the best antennas. Furthermore, the selection procedure involves identifying the stated objectives, which include energy usage and error minimization. Indeed, the suggested technique is an enhanced version of the lion algorithm (LA). Ultimately, the suggested work's performance is compared to and proven against other traditional models.

Exile’s Home as a Domain of Power in Gao Xingjian’s Soul Mountain

With the key objective to contest the grand narrative of Chinese home as a seat of Confucian order and harmony, this paper intends to explore home as a tyrannical site in the novel Soul Mountain by Gao Xingjian, the Chinese self-exile writer in France. That Gao’s fiction deals with political oppression in the country under Mao’s rule is a truism. However, the fact that home at personal level plays an equally oppressive role has so far been overlooked in critical debates. Aiming to fill this gap in literature, this study highlights the tyranny that home exerts over individuals to “subjectify” and “territorialize” them to its set norms. Drawing on Michel Foucault’s theory of power and subjectivity, and Gilles Deleuze and Félix Guattari’s notion of “de-territorialization” of the subject, I argue that where home as a “regime of power” is oppressive, there it is also counter-productive; particularly so for an artist in whom it triggers an urge to dislocate or “de-territorialize.” Deploying critical and Foucauldian discourse analyses as tools to analyze data mainly from Gao’s first novel Soul Mountain, this study is directed toward attaining a power-resistant subjective autonomy, an area generally neglected in Asian cultures.

A new approach of successive interference cancellation decoder in power domain non-orthogonal multiple access transmission

A new approach of successive interference cancellation decoder in power domain non-orthogonal multiple access transmission

Measurement-Based Wideband Space-Time Channel Models for 77GHz Automotive Radar in Underground Parking Lots

In recent years, with the rapid development of Advanced Driver Assistance Systems (ADAS), vehicular millimeter-wave (mmWave) radar plays an important role in urban intelligent transportation system. Self-interference caused by multipath in radar channel is a widely concerned problem. However, the research on radar channel propagation characteristics is very limited and there are few models for radar channel available. In this paper, we propose a pioneering research for radar channel model. Based on measurement data, channel characteristics are analysed using the space-alternating generalized expectation-maximization (SAGE) algorithm. An empirical statistical model is established for the 77GHz mmWave radar channel in the underground parking lot scenario, which is one of the most challenging environments because of time-variation and abundant multipaths, filling the gap in the field. A path-association algorithm is used to obtain multipath component (MPC) trajectories in delay, Doppler frequency and power domains. Additionally, some trajectory (in range domain) features are analysed. Moreover, based on geometric analysis of trajectories in range domain, the deterministic component of trajectories is modeled, and then a novel method for discrimination between actual targets and ghost images is proposed and verified by simulation and measurement data.

Leveraging Continuous Prompt for Few-Shot Named Entity Recognition in Electric Power Domain with Meta-Learning

ABSTRACT Conventional named entity recognition methods usually assume that the model can be trained with sufficient annotated data to obtain good recognition results. However, in Chinese named entity recognition in the electric power domain, existing methods still face the challenges of lack of annotated data and new entities of unseen types. To address these challenges, this paper proposes a meta-learning-based continuous cue adjustment method. A generative pre-trained language model is used so that it does not change its own model structure when dealing with new entity types. To guide the pre-trained model to make full use of its own latent knowledge, a vector of learnable parameters is set as a cue to compensate for the lack of training data. In order to further improve the model's few-shot learning capability, a meta-learning strategy is used to train the model. Experimental results show that the proposed approach achieves the best results in a few-shot electric Chinese power named entity recognition dataset compared to several traditional named entity approaches.

Practice and reflection on data-driven modeling in electric power domain

Practice and reflection on data-driven modeling in electric power domain

Design and performance evaluation of successive interference cancellation based Slotted Aloha MAC protocol

As a result of densification, the performance of the wireless networks has become highly interference-limited and energy inefficient. To overcome this problem, interference mitigation techniques such as Successive Interference Cancellation (SIC) can be used to decode multiple packets simultaneously at the receiver. In this context, we analyze a SIC-based Slotted Aloha (SIC-SA) Medium Access Control (MAC) protocol for wireless networks. We derive expressions for packets decoding probability and optimal transmission probability of the nodes of the SIC-SA MAC protocol. Our derivation is based on the order statistics of Independent and Identical/non-Identical exponentially distributed received-signal-powers from the nodes under the Rayleigh channel condition. Throughput, delay, and energy efficiency of the SIC-SA MAC protocol have been derived and validated against simulation. The effect of path loss exponent, SINR threshold, and the number of nodes on the performance of SIC-SA have been studied. The performance of SIC-SA in a network of nodes distributed randomly according to the Poisson Point Process has been analyzed. Extension of our analysis to Power Domain Non-Orthogonal Multiple Access (NOMA) has been demonstrated. We also analyzed the impact of imperfect estimation of channel state information and imperfect SIC at the receiver. Results show an improvement in performance metrics of SIC-SA over the traditional Slotted Aloha.

Design of Power Location Coefficient System for 6G Downlink Cooperative NOMA Network

Cooperative non-orthogonal multiple access (NOMA) is a technology that addresses many challenges in future wireless generation networks by delivering a large amount of connectivity and huge system capacity. The aim of this paper is to design the varied distances and power location coefficients for far users. In addition, this paper aims to evaluate the outage probability (OP) performance against a signal-to-noise ratio (SNR) for a 6G downlink (DL) NOMA power domain (PD) and DL cooperative NOMA PD networks. We combine a DL cooperative NOMA with a 16 × 16, a 32 × 23, and a 64 × 64 multiple-input multiple-output (MIMO) and a 128 × 128, a 256 × 256, and a 512 × 512 massive MIMO in an innovative method to enhance OP performance rate and mitigate the power location coefficient’s effect for remote users. The results were obtained from Rayleigh fading channels using the MATLAB simulation software program. According to the outcomes, increasing the power location coefficients for the far user from 0.6 to 0.8 reduces the OP rate because increasing the power location coefficient for the far user decreases the power location coefficient for the near user, which results in less interference between them. In terms of the OP performance rate, the DL cooperative NOMA outperforms the NOMA. According to the findings, the DL cooperative NOMA OP rate outperforms the DL NOMA by a rate of 10−0.5. Whereas the 16 × 16 MIMO enhances the OP for the far user by 78.0 × 10−4, the 32 × 32 MIMO increases the OP for the far user by 19.0 × 10−4, and the 64 × 64 MIMO decreases the OP rate for the far user by 5.0 × 10−5. At a SNR of 10 dB, the 128 × 128 massive MIMO improves the OP for the far user by 1.0 × 10−5. The 256 × 256 massive MIMO decreases the OP for the far user by 43.0 × 10−5, and the 512 × 512 massive MIMO enhances the OP for the far user by 8.0 × 10−6. The MIMO techniques improve the OP performance, while the massive MIMO technology enhances the OP performance dramatically.

Deep Learning Based Power Allocation Schemes for NOMA System with Imperfect SIC

Non-orthogonal multiple access (NOMA) has been a promising technology for 5G communication system. NOMA allows more than one user to utilize the same resource at the same time, which can lead to high performance in terms of spectral efficiency, energy efficiency or fairness. NOMA enables power domain multiplexing and separates the multiplexed signal by using successive interference cancellation (SIC). Therefore, the full benefit of NOMA depends on power allocation. However, in practical system, residual interference caused by SIC process can severely degrade a system performance. In this paper, we propose two power allocation schemes based on deep learning to alleviate the effect of imperfect SIC for downlink NOMA system, including a deep learning-based sum rate power allocation scheme (DL-SRPAS) and a deep learning-based energy-efficient power allocation scheme (DL-EEPAS). our two proposed schemes learn two optimal power allocation schemes provided through exhaustive search. We search the solution of the optimization problems, where two optimization problems are formulated to maximize the sum rate and the energy efficiency subject to a minimum user data rate requirement. The simulation results verify that our two proposed schemes can alleviate the effect of imperfect SIC and outperform two conventional power allocation schemes which maximize the sum rate and the energy efficiency without considering imperfect SIC. In addition, our proposed schemes achieve near-optimal performance with very low computational time.

Hybrid 3DMA for multi-user MIMO-VLC

In this paper, we propose and investigate a hybrid three-dimensional multiple access (3DMA) scheme for multi-user multiple-input multiple-output visible light communication (MU-MIMO-VLC) systems that can fully exploit the 3D resources of the system including frequency, space, and power. Particularly, all users in the MU-MIMO-VLC system applying hybrid 3DMA are first divided into multiple user groups (UGs) in the spatial domain, and users within each UG are further divided into multiple user pairs (UPs) in the frequency domain. In each UP, two users are multiplexed in the power domain via superposition coding. Due to the efficient 3D resource allocation in the MU-MIMO-VLC system applying hybrid 3DMA, the available bandwidth of each user can be substantially increased. Moreover, the impact of error propagation caused by imperfect successive interference cancellation (SIC) is considered, and the optimal power allocation (OPA) strategy is also derived to maximize the achievable sum rate of each UP. The feasibility and superiority of the proposed hybrid 3DMA with OPA have been successfully verified by the obtained analysis and simulation results. It is shown that the achievable average sum rate of an indoor 4 × 4 MU-MIMO-VLC system can be substantially improved by applying the proposed hybrid 3DMA with OPA, in comparison to benchmark schemes such as orthogonal frequency division multiple access and space division multiple access. Moreover, it is further revealed that hybrid 3DMA with OPA exhibits high tolerance against imperfect SIC induced error propagation, which also shows excellent robustness and performance consistency to support multiple randomly located users.

Radio Resource Management for Eicic, Comp, Relaying and Back-hauls Techniques in LTE-advanced Networks: Concepts and a Literature Survey

Frequency reuse in cells is one of the strategies that LTE (Long Term Evolution) uses to maximize the spectrum efficiency. However, it leads to an interference among the cells, especially at the cell edges where the probability for a cell-edge user to be scheduled on a resource block that is being transmitted by the neighbouring cell is high; consequently, the interference is high. In-order to mitigate Inter-Cell Interference (ICI), Inter-Cell Interference Coordination (ICIC) was proposed by the Third Generation Partnership Project (3GPP) standards for the LTE network, and later on, the enhanced Inter-Cell Interference Coordination (eICIC) was proposed for the LTE-Advanced network. ICIC reduces cell-edge interference on traffic channels from neighbouring cells by the use of three interference reduction schemes that works in the power and frequency domain, and they are based on lowering the power of some channels to limit their reception to the users that are close to the base station, and by reducing the chance of frequency overlap. eICIC was proposed to handle ICI in Heterogeneous Network (HetNet) deployments. It reduces the interference on both the traffic and control channels. It uses power, frequency and also time domain to mitigate intra-frequency interference in HetNets. Another technique that was proposed by the 3GPP for the LTE-Advanced network that can reduce the ICI and improve the cell average and cell-edge user throughput is the Coordinated Multi-Point (CoMP) transmission/reception technique. CoMP can increase the cell average and cell edge user throughput in both the uplink and downlink transmission by joint scheduling and data processing in multiple cells/eNBs. Another technique that was proposed by the 3GPP for the LTE-Advanced network that can improve the LTE network coverage in difficult conditions is to deploy Relay Nodes (RNs). In this paper, we survey Radio Resource Management (RRM) for some of the techniques that are used with LTE-A. The included techniques in this paper are; the ICIC, eICIC, CoMP, Relaying and Back-hauls. We start by explaining the concepts of these techniques. Then, by summarizing the radio resource management approaches that were proposed in the literature for these techniques. And finally, we provide some concluding remarks in the last section.

Effect of Lesion of Central Amygdala on Heart Rate Variability in Albino Wistar Rats

Background and Aim: Heart rate variability (HRV) reflects the pre-frontal cortex (PFC) and amygdalar connections. HRV is also influenced by emotions, which is controlled by limbic system. Thus, amygdala-limbic connection is suggested to be the major integrator of HRV and the alterations in the regulation lead to cardiometabolic risks. The present study was conducted to assess the central amygdala in the heart rate variability in albino Wistar rats. Methods: A total of 8 albino Wistar rats were taken for the study. Stereotaxic procedure was performed and lesion was made into the central amygdalar nuclei bilaterally. HRV was assessed before and after lesion of central amygdala. Results: Following lesion of central amygdala, there was decrease in total power (TP), high frequency (HF), and other time domain indices of HRV, while there was increase in low frequency (LF) and LF-HF ratio. Conclusion: Lesion of central amygdala decreased TP indicating the crucial role of central amygdala in the control of HRV. The control of central amygdala on sympathovagal balance is profound.