Low Complexity Power Research Articles

An Optimum Weighted Energy Efficiency Approach for Low Complexity Power Allocation in Downlink NOMA

Non-orthogonal multiple access (NOMA) has emerged as a significant technique for 5G wireless networks because it increases device connectivity, spectral efficiency, and energy efficiency. The advantages of the NOMA system rely on the employed resource allocation schemes, which include power allocation (PA) and subcarrier user assignment (SUA). Therefore, this paper concentrates on suggesting a PA approach called a weighted energy efficiency power allocation (WEE-PA) approach to maximize the total weighted energy efficiency (WEE) in the NOMA system. Also, the proposed WEE-PA approach boosts the fairness between users, the minimum user rate in the system, the outage probability, and the average data rate per weak user. Therefore, the PA optimization problem defines as an optimization problem with a total power constraint and a set of dynamic PA parameters to maximize the WEE and ensure user fairness. The original optimization problem separates into two sub-problems, and an iterative approach is employed to solve these two sub-problems alternatingly and reduce the computational complexity. Since the optimization problem is non-convex, the sequential quadratic programming (SQP) technique is applied to resolve it and find the corresponding optimal solution. Our simulations confirm that using our proposed WEE-PA algorithm to allocate mutual resources furnishes better results than existing PA schemes.

Low-Complexity Power Allocation in Pilot-Pouring Superimposed-Training Over CB-FMT

Pilot-pouring superimposed training (PPST) is a novel channel estimation technique specially designed for cyclic block filtered multi-tone (CB-FMT), where the pilot symbols are poured into the subcarriers taking advantage of the power left unused by the data symbols. Hence, since this technique is based on superimposed training (ST) principles, the data rate is not reduced, unlike the pilot symbol assisted modulation (PSAM). Besides, it exploits a weighted average at the receiver side that is capable of minimizing the mean squared error (MSE) of the channel estimation, and then enhancing the performance of the system. However, the existing proposal on PPST is limited to the minimization of the MSE to improve channel estimation for a given power allocation factor, without solving the joint optimization of channel estimation and data detection procedures. With this aim, this work addresses the whole problem to reach the best performance for both tasks, thus taking into account also the power allocation factor in the optimization process, where the spectral efficiency must be maximized through the signal-to-interference plus noise ratio (SINR). Two optimization approaches are proposed, where the first one, referred as pilot-pouring optimization (PPO), is focused on performance at the expense of a high complexity, while the second one, denoted as low-complexity PPO (LPPO), is able to trade-off between performance and execution time. Numerical results are provided in order to show the validity of our proposal, where the different optimization problems are compared in terms of SINR and execution time.

Low-Complexity Transmit Power Control for Secure Communications in Wireless-Powered Cognitive Radio Networks.

In this study, wireless-powered cognitive radio networks (WPCRNs) are considered, in which N sets of transmitters, receivers and energy-harvesting (EH) nodes in secondary networks share the same spectrum with primary users (PUs) and none of the EH nodes is allowed to decode information but can harvest energy from the signals. Given that the EH nodes are untrusted nodes from the point of view of information transfer, the eavesdropping of secret information can occur if they decide to eavesdrop on information instead of harvesting energy from the signals transmitted by secondary users (SUs). For secure communications in WPCRNs, we aim to find the optimal transmit powers of SUs that maximize the average secrecy rate of SUs while maintaining the interference to PUs below an allowable level, while guaranteeing the minimum EH requirement for each EH node. First, we derive an analytical expression for the transmit power via dual decomposition and propose a suboptimal transmit power control algorithm, which is implemented in an iterative manner with low complexity. The simulation results confirm that the proposed scheme outperforms the conventional distributed schemes by more than 10% in terms of the average secrecy rate and outage probability and can also considerably reduce the computation time compared with the optimal scheme.

An Efficient High SFDR PDDS Using High-Pass-Shaped Phase Dithering

This brief proposes a high spurious-free dynamic range (SFDR) pulse output direct digital frequency synthesizer (PDDS) with low complexity and low power consumption. Independent and uniformly distributed (IUD) high-pass-shaped dither is added to the phase accumulator output, resulting in a wideband spurious-free and low close-in noise floor. The power efficiency and speed are increased by reducing the sampling frequency of the ${m}$ -sequence generator and the high-pass filter (HPF). The SFDR improves by 29 dB as a result of the HPF, which is confirmed with a field-programmable gate array (FPGA) implementation. The application specified integrated circuit (ASIC) occupies $1168~{\mu \text {m}^{2}}$ on nangate 45-nm CMOS process and consumes 80.2 and $398~{\mu }\text{W}$ from a 1.2-V supply with the dither generator running at ${({1}/{4})f_{\text {clk}}}$ and ${f_{\text {clk}}}$ ( ${f_{\text {clk}}}=2$ GHz), respectively.

Low Complexity Hybrid Precoding Designs for Multiuser mmWave/THz Ultra Massive MIMO Systems.

Millimeter-wave and terahertz technologies have been attracting attention from the wireless research community since they can offer large underutilized bandwidths which can enable the support of ultra-high-speed connections in future wireless communication systems. While the high signal attenuation occurring at these frequencies requires the adoption of very large (or the so-called ultra-massive) antenna arrays, in order to accomplish low complexity and low power consumption, hybrid analog/digital designs must be adopted. In this paper we present a hybrid design algorithm suitable for both mmWave and THz multiuser multiple-input multiple-output (MIMO) systems, which comprises separate computation steps for the digital precoder, analog precoder and multiuser interference mitigation. The design can also incorporate different analog architectures such as phase shifters, switches and inverters, antenna selection and so on. Furthermore, it is also applicable for different structures, namely fully-connected structures, arrays of subarrays (AoSA) and dynamic arrays of subarrays (DAoSA), making it suitable for the support of ultra-massive MIMO (UM-MIMO) in severely hardware constrained THz systems. We will show that, by using the proposed approach, it is possible to achieve good trade-offs between spectral efficiency and simplified implementation, even as the number of users and data streams increases.

X-law detection scheme for monobit transmitted-reference ultra wideband receivers

<p>In ultra-wideband (UWB) communications, monobit receivers offer a low complexity implementation but at the same time exhibit a great performance loss. In this paper, a novel detection scheme, denoted as <em>x</em>-law detection (XLD), is proposed to diminish the performance loss caused by employing monobit analog-to-digital converters in transmitted-reference (TR) UWB receivers. Simulation results show that if the optimal value is employed for <em>x</em>, the XLD-based monobit weighted TR (MWTR) receiver can achieve 14.2~15.5 dB and 8~9.2 dB performance gain over the conventional MWTR receiver in LOS and NLOS scenarios, respectively. Moreover, the XLD-based MWTR receiver performance with the optimal value of <em>x</em> is only 1.6~3 dB away from the optimum MWTR receiver performance in intra-vehicle UWB channels. Additionally, the XLD-based MWTR receiver is not sensitive to the summation interval. This feature decreases the receiver complexity and guarantees a robust performance over different multipath channels. The significant performance improvement of the XLD scheme comes at a limited complexity increase. Thus, the XLD approach is a good candidate for TR-based and other training-based monobit receivers requiring low complexity, high performance, and low power consumption.</p>

A novel low-complexity power allocation algorithm based on the NOMA system in a low-speed environment

For future wireless communication systems, Power Domain Non-Orthogonal Multiple Access (PD-NOMA) using an advanced receiver has been considered as a promising radio access technology candidate. Power allocation plays an important role in the PD-NOMA system because it considerably affects the total throughput and Geometric Mean User Throughput (GMUT) performance. However, most existing studies have not completely accounted for the computational complexity of the power allocation process when the User Terminals (UTs) move in a slow fading channel environment. To resolve such problems, a power allocation method is proposed to considerably reduce the search space of a Full Search Power (FSP) allocation algorithm. The initial power reallocation coefficients will be set to start with former optimal values by the proposed Lemma before searching for optimal power reallocation coefficients based on total throughput performance. Step size and correction granularity will be adjusted within a much narrower power search range while invalid power combinations may be reasonably discarded during the search process. The simulation results show that the proposed power reallocation scheme can greatly reduce computational complexity while the total throughput and GMUT performance loss are not greater than 1.5% compared with the FSP algorithm.

A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy

A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy

High selectivity and sharp roll-off filtenna array for Ku-band application

ABSTRACT A (1 × 2) filtenna array inspired by an inter-digital-based bandpass filter is presented in this paper for simultaneous radiation and filtration. The feed line of the proposed antenna array resonating at 14 GHz with fractional bandwidth of 5.72% is modified in such a way that it acts like an inter-digital-based bandpass filter. The equivalent lumped circuit model of the proposed structure is analysed and detail synthesis procedure is presented. To study the impact of dimensional variations on the performance of proposed filtenna array, various parametric studies of filtenna and corresponding antenna array are performed and compared. The design strategy involves (N-1) filter circuits for realising a (1 × N) element filtenna array. The proposed array exhibits advantageous features such as low circuit complexity, compact size and low operational power over other reported filtenna arrays. The presented filtenna possesses fractional bandwidth and peak gain of 3.85% and 8.14 dB respectively at resonating frequency of 14 GHz, which covers the standards of Ku-band. The physical size of the filtenna array in terms of free space wave length is 1.96λ0 × 1.96λ0 × 0.073λ0 at 14 GHz. The radiation patterns are omni-directional in E-plane and nearly omni-directional in nature at H-plane at resonance frequency of 14 GHz.

Hybrid MIMO: A New Transmission Method For Simultaneously Achieving Spatial Multiplexing and Diversity Gains in MIMO Systems

Multiple input multiple output (MIMO) technology has evolved over the past few years into a technology with great potential to drive the direction of future wireless communications. MIMO technology has become a solid reality when massive MIMO systems (MIMO with large number of antennas and transceivers) were commercially deployed in several countries across the world in the recent past. Moreover, MIMO has been integrated into state-of-the-art paradigms such as fifth-generation (5G) networks as one of the main enabling technologies. MIMO possesses many attractive and highly desirable properties such as spatial multiplexing, diversity gains, and adaptive beamforming gains that leads to high data rates, enhanced reliability, and other enhancements. Nevertheless, beyond 5G technologies demand wireless communication systems with, among other properties, immensely higher data rates and better reliability simultaneously at the same time. In this work, a new, novel MIMO technique for simultaneously achieving multiplexing and diversity gains as well as completely eliminating any processing at the MIMO receiver, leading to advantages such as low complexity and low power consumption, is proposed. The proposed technique employs the design of interference-canceling matrices, which are calculated from the channels between the transceiver antennas, where the matrices are employed at the base station to help achieve multiplexing and diversity gains simultaneously. The novelty and efficiency of the introduced paradigm is demonstrated via mathematical models and validated by Monte Carlo simulations. Results indicate that the proposed system outperforms conventional MIMO models.

High Throughput Low Complexity and Low Power ePiBM RS Decoder Using Fractional Folding

This brief proposes a novel generalized Fractional Folding (FF) architecture for digital signal processing integrated circuits. With this new structure, a Fractional Folding based enhanced Parallel Inversionless Berlekamp-Massey (FF-ePIBM) Reed-Solomon Decoder is presented of which the number of processing element (PE) can be reduced to only one, resulting in ultra-low hardware complexity. The FF-ePIBM VLSI architecture can greatly reduce the hardware cost by about 60% compare to the fully expanded parallel ePIBM architecture. With FF-ePIBM architecture, syndrome calculation (SC) block and Chien search & error evaluation (CSEE) block are able to operate at a lower frequency resulting in about 14.8% power saving. A polyphase clock signal is needed in order to achieve fractional folding function according to specific fractional-factor. It is generated from Delay Locked Loop (DLL) at little or no extra cost in different SoCs. To maximize the throughput of decoder, pipelined architecture is adopted to optimize critical path delay. The RS (255, 239) decoder with FF-ePIBM architecture is finally implemented with 40nm CMOS technology. The synthesized results demonstrate that the decoder has a gate count of 12.9k and can operate at 3.1GHz to achieve a highest throughput of 24.8Gb/s and a best TSNT FoM value of 592 to this date.

ENERGY-EFFICIENT POWER ALLOCATION FOR IMPERFECT CSI DOWNLINK NOMA SYSTEM

The fifth generation (5G) networks must provide the massively increased number of users by thousand times higher data rate at lower power consumption. Thus, optimizing the energy efficiency (EE) becomes an essential issue that has to be researched from the green communication perspective. Non-orthogonal multiple access (NOMA) is considered one of the high potential techniques in fifth-generation systems. This technology is favorable to maximize the energy efficiency and the spectrum efficiency by composing different signals at the same time on the same carrier at different power levels. In this paper, a low complexity power allocation algorithm is proposed in imperfect channel state information (CSI) downlink NOMA cellular system, where obtaining full CSI at the base station is considered a challenge. The proposed algorithm relies on the fact that the allocated power is inversely proportional to the channel strength of the user to implement the successive interference cancellation (SIC) technique at the user terminal to reconstruct the desired signal. The performance of the system is analyzed in terms of energy efficiency and outage probability and compared to the conventional orthogonal multiple access (OMA) system. Results show that the proposed algorithm increases the energy efficiency by about 50% compared to the conventional OMA technology, and an improvement in the outage probability has been achieved. Furthermore, the effect of the error in the channel estimation on the energy efficiency in imperfect CSI NOMA system is evaluated. The simulation shows that the energy efficiency reduces when the channel estimation error increases; and the best performance is achieved in the perfect CSI case where the channel estimation error is zero.

NOMA for Energy-Efficient LiFi-Enabled Bidirectional IoT Communication

In this paper, we consider a light fidelity (LiFi)-enabled bidirectional Internet of Things (IoT) communication system, where visible light and infrared light are used in the downlink and uplink, respectively. In order to improve the energy efficiency (EE) of the bidirectional LiFi-IoT system, non-orthogonal multiple access (NOMA) with a quality-of-service (QoS)-guaranteed optimal power allocation (OPA) strategy is applied to maximize the EE of the system. We derive a closed-form OPA set based on the identification of the optimal decoding orders in both downlink and uplink channels, which can enable low-complexity power allocation. Moreover, we propose an adaptive channel and QoS-based user pairing approach by jointly considering users' channel gains and QoS requirements. We further analyze the EE of the bidirectional LiFi-IoT system and the user outage probabilities (UOPs) of both downlink and uplink channels of the system. Extensive analytical and simulation results demonstrate the superiority of NOMA with OPA in comparison to orthogonal multiple access (OMA) and NOMA with typical channel-based power allocation strategies. It is also shown that the proposed adaptive channel and QoS-based user pairing approach greatly outperforms individual channel/QoS-based approaches, especially when users have diverse QoS requirements.

Energy-Efficient Decoupled Access Scheme for Cellular-Enabled UAV Communication Systems

This article proposes a decoupled access scheme with enhanced energy efficiency (EE) for cellular networks serving a mix of randomly distributed ground and areal users. While unmanned aerial vehicles (UAVs) benefit from line-of-sight (LOS) dominant channels with their serving base-stations (BSs), their omnidirectional antennas could cause high interference to ground users (GUEs). To overcome this, a downlink (DL) and uplink (UL) decoupled (DUDe) access scheme is proposed in which the UAVs’ control and nonpayload communication links are separated from the high-capacity data links by connecting to different BSs and transmitting over different frequency bands in the UL and DL directions. The GUE-BS channels are also decoupled in tandem to minimize interference. Moreover, as battery life is a major constraint for UL transmissions, an optimal low-complexity power allocation algorithm—based on fractional programming and successive convex approximation—is proposed for optimizing the EE of this DUDe scheme. Our numerical results demonstrate that the proposed scheme can achieve several times higher sum-rates in both UL and DL directions than its coupled benchmark counterparts. Moreover, it will be shown that in addition to improving the GUE sum-rate by 15%, the devised power allocation algorithm achieves twice higher GUE EE than conventional fractional power control.

Wideband User Grouping for Uplink Multiuser mmWave MIMO Systems With Hybrid Combining

Analog-digital hybrid precoding and combining schemes constitute an interesting approach to millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems due to the low hardware complexity and/or low power required for its deployment. However, the design of the hybrid precoders and combiners of a wideband multiuser (MU) mmWave MIMO system is challenging because the signal processing in the analog domain is constrained to be frequency flat. Furthermore, the number of radio frequency (RF) chains limits the number of individual streams that a common base station (BS) can simultaneously serve. This work jointly addresses the user scheduling, the user precoder design, and the BS hybrid combining design for the uplink of wideband MU mmWave MIMO systems. On the one hand, user precoding and BS hybrid combining are jointly designed to minimize the impact of having frequency-flat RF components. On the other hand, a number of users larger than the number of RF chains are served at the BS by employing a distributed quantizer linear coding (DQLC)-based non-orthogonal multiple access (NOMA) scheme. The use of this encoding strategy also allows exploiting the spatial correlation between the source information. Simulation results show remarkable performance gains of the proposed approaches for wideband mmWave MIMO hardware-constrained systems.

Capacity Loss From Localization Error in MIMO Channel Using Leaky Coaxial Cable

Leaky coaxial (LCX) cable has been employed as antennas for wireless traffic over many linear-cell scenarios such as railway station, tunnels and shopping malls. In addition, LCX can be used for user localization and wireless power transfer (WPT). Compared with the equal power allocation method, the power allocation method for LCX system using positional information (PI) can improve its capacity with the same level of computational complexity. In this paper, we will investigate the level of capacity loss on the 2.4 GHz and 5 GHz band for the conventional equal power (EP) allocation method, the water-filling (WF) based power allocation, and our proposed low-complexity power allocation method for LCX system with PI. The results show that LCX system with our proposed method using PI can reduce the capacity loss due to localization error than that of others.

Wireless Power Transfer with Information Asymmetry: A Public Goods Perspective

Wireless power transfer (WPT) technology enables a cost-effective and sustainable energy supply in wireless networks. However, the broadcast nature of wireless signals makes them non-excludable public goods, which leads to potential free-riders among energy receivers. In this study, we formulate the wireless power provision problem as a public goods provision problem, aiming to maximize the social welfare of a system of an energy transmitter (ET) and all the energy users (EUs), while considering their heterogeneous valuations, private information, and self-interested behaviors. We propose a two-phase all-or-none scheme involving a low-complexity Power And Taxation (PAT) mechanism, which ensures voluntary participation, truthfulness, budget balance, and social optimality at every Nash equilibrium (NE). We propose a distributed PAT (D-PAT) algorithm to reach an NE, and prove its convergence by connecting the structure of NEs and that of the optimal solution to a related optimization problem. We further extend the analysis to a multi-channel system, which brings a further challenge of non-strictly concave agents' payoffs. We propose a Multi-Channel PAT (M-PAT) mechanism and a distributed M-PAT (D-MPAT) algorithm to address the challenge. Simulation results show that, our design is most beneficial when there are more EUs and more homogeneous channel gains.

Low-Complexity Power Allocation for Network-Coded User Scheduling in Fog-RANs

Consider a Fog Radio Access Network (FRAN) in which a cloud base station (CBS) is responsible for scheduling user-equipments (UEs) to a set of radio resource blocks (RRBs) of Fog Access Points (F-APs) and for allocating power to the RRBs. The conventional graphical approach for solving the coordinated scheduling and power control problem in FRAN requires prohibitive computational complexity. This letter, instead, proposes a low-complexity solution to the problem under the constraint that all the scheduled UEs can decode the requested files sent by their associated RRBs/F-APs. Unlike previous solution that requires constructing the total power control graph, the proposed computationally efficient solution is developed using a single power control subgraph. Numerical results reveal a close-to-optimal performance of the proposed method in terms of throughput maximization for correlated channels with a significant reduction in the computational complexity.

Efficient Downlink Power Allocation Algorithms for Cell-Free Massive MIMO Systems

Cell-free Massive MIMO systems consist of a large number of geographically distributed access points (APs) that serve the users by coherent joint transmission. The spectral efficiency (SE) achieved by each user depends on the power allocation: which APs that transmit to which users and with what power. In this article, we revisit the max-min and sum-SE power allocation policies, which have previously been approached using high-complexity general-purpose solvers. We develop and compare several different high-performance low-complexity power allocation algorithms that are appropriate for use in large systems. We propose two new algorithms for sum-SE power optimization inspired by weighted minimum mean square error (WMMSE) minimization and fractional programming (FP). Further, one new FP-based algorithm is proposed for max-min fair power allocation. The alternating direction method of multipliers (ADMM) is used to solve specific convex subproblems in the proposed algorithms. Our ADMM reformulations lead to multiple small-sized subproblems with closed-form solutions. The proposed algorithms find global or local optimal power allocation solutions for large-scale systems but with reduced computational time compared to previous work.

Development of a Test-Bench for Evaluating the Embedded Implementation of the Improved Elephant Herding Optimization Algorithm Applied to Energy-Based Acoustic Localization

The present work addresses the development of a test-bench for the embedded implementation, validity, and testing of the recently proposed Improved Elephant Herding Optimization (iEHO) algorithm, applied to the acoustic localization problem. The implemented methodology aims to corroborate the feasibility of applying iEHO in real-time applications on low complexity and low power devices, where three different electronic modules are used and tested. Swarm-based metaheuristic methods are usually examined by employing high-level languages on centralized computers, demonstrating their capability in finding global or good local solutions. This work considers iEHO implementation in C-language running on an embedded processor. Several random scenarios are generated, uploaded, and processed by the embedded processor to demonstrate the algorithm’s effectiveness and the test-bench usability, low complexity, and high reliability. On the one hand, the results obtained in our test-bench are concordant with the high-level implementations using MatLab® in terms of accuracy. On the other hand, concerning the processing time and as a breakthrough, the results obtained over the test-bench allow to demonstrate a high suitability of the embedded iEHO implementation for real-time applications due to its low latency.