scholarly journals Energy-Spectral Efficiency Trade-Offs in Full-Duplex MU-MIMO Cloud-RANs with SWIPT

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Xuan-Xinh Nguyen ◽  
Ha Hoang Kha
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Optimization Problems ◽  
Iterative Algorithms ◽  
Full Duplex ◽  
Total Power ◽  
Achievable Rate ◽  
Power Splitting ◽  
Radio Access ◽  
Trade Offs

The present paper investigates the trade-offs between the energy efficiency (EE) and spectral efficiency (SE) in the full-duplex (FD) multiuser multi-input multioutput (MU-MIMO) cloud radio access networks (CRANs) with simultaneous wireless information and power transfer (SWIPT). In the considered network, the central unit (CU) intends to concurrently not only transfer both energy and information toward downlink (DL) users using power splitting structures but also receive signals from uplink (UL) users. This communication is executed via FD radio units (RUs) which are distributed nearby users and connected to the CU through limited capacity fronthaul (FH) links. In order to unveil interesting trade-offs between the EE and SE metrics, we first introduce three conventional single-objective optimization problems (SOOPs) including (i) system sum rate maximization, (ii) total power minimization, and (iii) fractional energy efficiency maximization. Then, by making use of the multiobjective optimization (MOO) framework, the MOO problem (MOOP) with the objective vector of the achievable rate and power consumption is addressed. All considered problems are nonconvex with respect to designing variables comprising precoding matrices, compression matrices, and DL power splitting factors; thus, it is extremely intractable to solve these problems directly. To overcome these issues, we develop iterative algorithms by utilizing the sequential convex approximation (SCA) approach for the first two SOO problems and the SCA-based Dinkelbach method for the fractional EE problem. Regarding the MOOP, we first rewrite it as an SOOP by applying the modified weighted Tchebycheff method and, then, propose the iterative algorithm-based SCA to find its optimal Pareto set. Various numerical simulations are conducted to study the system performance and appealing EE-SE trade-offs in the considered system.

scholarly journals Energy Efficiency Maximization for Full Duplex MIMO Cloud Radio Access Networks

2021 ◽  
Vol 3 (3) ◽  
pp. first
Author(s):  
Tien Ngoc Ha ◽  
Xuan-Xinh Nguyen ◽  
Hoang Kha Ha
Keyword(s):  
Energy Efficiency ◽  
Optimization Problems ◽  
Control Unit ◽  
Access Networks ◽  
Full Duplex ◽  
Maximization Problem ◽  
Limited Capacity ◽  
Cloud Radio Access Networks ◽  
Radio Access Networks ◽  
Radio Access

This paper studies a joint precoder and fronthaul compression design for full-duplex (FD) miltiple-input-multiple-output (MIMO) cloud radio access networks (CRANs). A cloud control unit (CU) communicates with multiple downlink and uplink users through FD radio units (RUs) connected to the CU through fronthaul links which are limited capacity. We address the energy efficiency (EE) maximization problem subject to the transmit power constraints at each RU, each user and the limited capacity of fronthaul links. Since the formulated design problem is a highly non-convex problem in design variables, we exploit a successive convex approximation (SCA) method to obtain the concave lower bound of the achievable sum rate and a convex upper bound of limited capacity fronthaul link functions. Then, we apply the Dinkelbach method to develop an efficient iterative algorithm guaranteeing convergence in which the convex optimization problems are solved. Numerical results are provided to investigate the EE of the proposed algorithm.

scholarly journals Energy Efficiency and Spectral Efficiency Tradeoff in Massive MIMO Multicast Transmission with Statistical CSI

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 1045
Author(s):  
Bin Jiang ◽  
Bowen Ren ◽  
Yufei Huang ◽  
Tingting Chen ◽  
Li You ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Communication Systems ◽  
Multicast Transmission ◽  
Transmission Strategy ◽  
Trade Offs ◽  
Core Technology ◽  
System Resource

As the core technology of 5G mobile communication systems, massive multi-input multi-output (MIMO) can dramatically enhance the energy efficiency (EE), as well as the spectral efficiency (SE), which meets the requirements of new applications. Meanwhile, physical layer multicast technology has gradually become the focus of next-generation communication technology research due to its capacity to efficiently provide wireless transmission from point to multipoint. The availability of channel state information (CSI), to a large extent, determines the performance of massive MIMO. However, because obtaining the perfect instantaneous CSI in massive MIMO is quite challenging, it is reasonable and practical to design a massive MIMO multicast transmission strategy using statistical CSI. In this paper, in order to optimize the system resource efficiency (RE) to achieve EE-SE balance, the EE-SE trade-offs in the massive MIMO multicast transmission are investigated with statistical CSI. Firstly, we formulate the eigenvectors of the RE optimization multicast covariance matrices of different user terminals in closed form, which illustrates that in the massive MIMO downlink, optimal RE multicast precoding is supposed to be done in the beam domain. On the basis of this viewpoint, the optimal RE precoding design is simplified into a resource efficient power allocation problem. Via invoking the quadratic transform, we propose an iterative power allocation algorithm, which obtains an adjustable and reasonable EE-SE tradeoff. Numerical simulation results reveal the near-optimal performance and the effectiveness of our proposed statistical CSI-assisted RE maximization in massive MIMO.

An Alternating Optimization Algorithm for Energy Efficiency in Heterogeneous Networks

2018 ◽  
Vol 4 (1) ◽  
pp. 1 ◽  
Author(s):  
Kha Ha ◽  
Tien Ha
Keyword(s):  
Energy Efficiency ◽  
Heterogeneous Networks ◽  
Optimization Problems ◽  
Minimum Mean Square Error ◽  
Minimum Energy ◽  
Iterative Algorithms ◽  
Base Station ◽  
Small Cells ◽  
Total System ◽  
Design Problems

This paper studies the problems of precoding designs to achieve the energy efficiency (EE) in the uplink heterogeneous networks in which the multiple small cells are deployed in a macro-cell.  We consider two design problems which maximize either the total system energy efficiency (SEE) or the minimum energy efficiency (MinEE) among users subject to the transmit power constraints at each user and interference constraints caused to the macro base station. Since the optimization problems are non-convex fractional programming in matrix variables, it cannot be straightforward to obtain the optimal solutions. To tackle with the non-convexity challenges of the design problems, we adopt the relationships between the minimum mean square error (MMSE) and achievable data rate to recast the EE problems into ones more amenable. Then, we employ the block coordinate ascent (BCA) and the Dinkelbach methods to develop efficient iterative algorithms in which the closed form solutions are obtained or the semi-definite programming (SDP) problems are solved at each iteration. Simulation results are provided to investigate the EE performance of the EE optimization as compared to those of the spectral efficiency (SE) optimization.

Spectral Efficiency and Relay Energy Efficiency of Full-Duplex Relay Channel

2017 ◽  
Vol 16 (5) ◽  
pp. 3162-3175 ◽  
Author(s):  
Zhengchuan Chen ◽  
Tony Q. S. Quek ◽  
Ying-Chang Liang
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Full Duplex ◽  
Relay Channel ◽  
Full Duplex Relay

scholarly journals Energy Efficiency Optimization in Adaptive Massive MIMO Networks for 5G Applications Using Genetic Algorithm

2021 ◽  
Author(s):  
Ibrahim Salah ◽  
M. Mourad Mabrook ◽  
Kamel Hussein Rahouma ◽  
Aziza I. Hussein
Keyword(s):  
Genetic Algorithm ◽  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo System ◽  
Optimization Technique ◽  
Base Station ◽  
Maximum Efficiency ◽  
Adaptive Optimization ◽  
Trade Offs

Abstract Given that the exponential pace of growth in wireless traffic has continued for more than a century, wireless communication is one of the most influential innovations in recent years. Massive Multiple-Input Multiple-Output (M-MIMO) is a promising technology for meeting the world's exponential growth in mobile data traffic, particularly in 5G networks. The most critical metrics in the massive MIMO scheme are Spectral Efficiency (SE) and Energy Efficiency (EE). For single-cell MMIMO uplink transmission, energy and spectral-efficiency trade-offs have to be estimated by optimizing the number of base station antennas versus the number of active users. This paper proposes an adaptive optimization technique focusing on maximizing Energy Efficiency at full spectral efficiency using a Genetic Algorithm (GA) optimizer. The number of active antennas is estimated according to the change in the number of active users based on the proposed GA scheme that optimizes the EE in the M-MIMO system. Simulation results show that the GA optimization technique achieved the maximum energy efficiency of the 5G M-MIMO platform and the maximum efficiency in the trade-off process.

Energy-Efficient Full-Duplex Enabled Cloud Radio Access Networks

2020 ◽  
Vol E103.B (1) ◽  
pp. 71-78
Author(s):  
Tung Thanh VU ◽  
Duy Trong NGO ◽  
Minh N. DAO ◽  
Quang-Thang DUONG ◽  
Minoru OKADA ◽  
...  
Keyword(s):  
Energy Efficient ◽  
Access Networks ◽  
Full Duplex ◽  
Cloud Radio Access Networks ◽  
Radio Access Networks ◽  
Radio Access

Analysis of Optimum Precoding schemes in Millimeter Wave System

2020 ◽  
Vol 13 ◽  
Author(s):  
Divya Singh ◽  
Aasheesh Shukla
Keyword(s):  
Power Consumption ◽  
Millimeter Wave ◽  
Spectral Efficiency ◽  
Phase Shifter ◽  
Phase Shifters ◽  
Achievable Rate ◽  
Wave System ◽  
Digital To Analog Converter ◽  
Hybrid Precoding ◽  
Analog Converter

Background : Millimeter wave technology is the emerging technology in wireless communication due to increased demand for data traffic and its numerous advantages however it suffers from severe attenuation. To mitigate this attenuation, phased antenna arrays are used for unidirectional power distribution. An initial access is needed to make a connection between the base station and users in millimeter wave system. The high complexity and cost can be mitigated by the use of hybrid precoding schemes. Hybrid precoding techniques are developed to reduce the complexity, power consumption and cost by using phase shifters in place of converters. The use of phase shifters also increases the spectral efficiency. Objective: Analysis of Optimum Precoding schemes in Millimeter Wave System. Method: In this paper, the suitability of existing hybrid precoding solutions are explored on the basis of the different algorithms and the architecture to increase the average achievable rate. Previous work done in hybrid precoding is also compared on the basis of the resolution of the phase shifter and digital to analog converter. Results: A comparison of the previous work is done on the basis of different parameters like the resolution of phase shifters, digital to analog converter, amount of power consumption and spectral efficiency. Table 2 shows the average achievable rate of different algorithms at SNR= 0 dB and 5 dB. Table 3 also compares the performance achieved by the hybrid precoder in the fully connected structure with two existing approaches, dynamic subarray structure with and without switch and sub connected or partially connected structure. Table 4 gives the comparative analysis of hybrid precoding with the different resolutions of the phase shifter and DAC. Conclusion: In this paper, some available literature is reviewed and summarized about hybrid precoding in millimeter wave communication. Current solutions of hybrid precoding are also reviewed and compared in terms of their efficiency, power consumption, and effectiveness. The limitations of the existing hybrid precoding algorithms are the selection of group and resolution of phase shifters. The mm wave massive MIMO is only feasible due to hybrid precoding.

scholarly journals Characterizing Color Quality, Damage to Artwork, and Light Intensity of Multi-Primary LEDs for Museums

Heritage ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 188-197
Author(s):  
Dorukalp Durmus
Keyword(s):  
Energy Efficiency ◽  
Appearance Model ◽  
Light Sources ◽  
Great Flexibility ◽  
Oil Paintings ◽  
Damage Reduction ◽  
Output Variability ◽  
Color Quality ◽  
Trade Offs

Light causes damage when it is absorbed by sensitive artwork, such as oil paintings. However, light is needed to initiate vision and display artwork. The dilemma between visibility and damage, coupled with the inverse relationship between color quality and energy efficiency, poses a challenge for curators, conservators, and lighting designers in identifying optimal light sources. Multi-primary LEDs can provide great flexibility in terms of color quality, damage reduction, and energy efficiency for artwork illumination. However, there are no established metrics that quantify the output variability or highlight the trade-offs between different metrics. Here, various metrics related to museum lighting (damage, the color quality of paintings, illuminance, luminous efficacy of radiation) are analyzed using a voxelated 3-D volume. The continuous data in each dimension of the 3-D volume are converted to discrete data by identifying a significant minimum value (unit voxel). Resulting discretized 3-D volumes display the trade-offs between selected measures. It is possible to quantify the volume of the graph by summing unique voxels, which enables comparison of the performance of different light sources. The proposed representation model can be used for individual pigments or paintings with numerous pigments. The proposed method can be the foundation of a damage appearance model (DAM).

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