Energy Spectral Efficiency Tradeoff Research Articles

Analysis of Optimal Spectral-energy Efficiency Tradeoff Linear Precoding Massive MIMO 5G and Beyond

In this article, we consider cellular wireless communication with a large number base station antennas deployement, called Massive-MIMO systems, are inspected. Massive MU (multi-user), (MIMO) multiple-input-multiple-output technique gives a significant SE (spectral efficiency) using easy techniques precoding while high EE (energy efficiency) is expected to be offered. Our paper works on two famous schemes, linear precoding Zero-Forcing and Maximum-RatioTransmission taking into account of system circuit power consumption, where that important aspect was ignored in the literature. Both EE (energy efficiency) and SE (spectral efficiency) are considered to be the important key indicators in 5G and beyond communications, which need to be taken into account at the same moment with respect to nowadays environmental consideration. To realize an optimal tradeoff between SE-EE, that precoding schemes are been formulated under CSI-imperfection (channel state information) in a realistic way. Simulation results illustrate that our proposed method achieves better optimal balance between Energy Efficiency and Spectral Efficiency. Under Matlab experimentation, simulation result shows an optimal performance, while tradeoff aspect is observed clairly between SE and EE using such two precoders algorithms. Although such tradeoff SE-EE coincide at first but later on their interests become conflicting and divergent then leading EE to so gradually decrease while SE continues increasing logarithmically. ZF pre-coding method is the appropriate scenario to achieve higher pre-coder performance.

Spectral-Energy Efficiency Trade-Off Based Design for Hybrid TDMA-NOMA System

The combination of time division multiple access (TDMA) and non-orthogonal multiple access (NOMA), referred to as hybrid TDMA-NOMA system, is considered as a potential solution to meet the unprecedented requirements for future wireless networks. While recent resource allocation techniques aiming to individually maximize either spectral efficiency (SE) or energy efficiency (EE), this paper considers an SE-EE trade-off based technique for a hybrid TDMA-NOMA system. This design offers an additional degree of freedom in resource allocation. The proposed design is formulated as a non-convex multi-objective optimization (MOO) problem. The MOO framework is reformulated as a single-objective optimization (SOO) problem by combining the multi-objectives through a weighted-sum objective function. With this, each of the original objectives is assigned with a weight factor to reflect its importance in the design. Then, the sequential convex approximation (SCA) and a second-order cone (SOC) approach are jointly utilized to deal with the non-convexity issues of the SOO problem. Simulation results reveal that the proposed trade-off based design strikes a good balance between the objective functions, while meeting the instantaneous requirements of the system.

Spectral–energy efficiency tradeoff in decode‐and‐forward full‐duplex relay system

In this study, the spectral efficiency (SE) and energy efficiency (EE) tradeoff in full-duplex (FD) two-hop decode-and-forward (DF) relaying system is studied by considering the influence of residual self-interference. In order to increase the SE of the traditional DF relaying system, firstly, an optimal power allocation (OPA) method is proposed, and the SE and EE analyses of the system are obtained. Secondly, by applying an unified SE–EE tradeoff metric, the multi-object joint SE and EE maximisation problem is formulated as a single-objective joint maximisation problem for SE and EE. Furthermore, the optimal total transmission power of the single-objective joint SE and EE maximisation problem is obtained according to the tradeoff factors. Theoretical analysis and numerical results show that the proposed OPA method significantly improve the system's SE and EE. At the same time, it reveals that the tradeoff between the SE and EE can be flexible by setting the tradeoff factors.

Energy-Spectral Efficiency Tradeoff in DCO-OFDM Visible Light Communication System

Due to its simple implementation and higher spectral efficiency (SE), the direct current (DC) biased optical orthogonal frequency division multiplexing (DCO-OFDM) scheme has been extensively employed in visible light communication (VLC) system. In this paper, the tradeoff between energy efficiency (EE) and SE in DCO-OFDM system is investigated. Specifically, the achievable SE of DCO-OFDM system with power and bit loading is derived, and the closed-form expression of the EE-SE tradeoff is obtained, on the basis of which, the optimal SE to maximize EE is derived, and the optimal parameters of the DCO-OFDM system, e.g., the horizontal and vertical distances of optical transmission network, the number of subcarriers, to maximize the EE-SE tradeoff are theoretically derived. Moreover, to derive the optimal transmitted power, a Pareto optimal set based multi-objective optimization (MOO) is formulated, which is successfully transformed into a single-objective optimization (SOO), with the help of a proposed EE-SE tradeoff metric. Finally, simulation results are provided to verify the presented EE-SE tradeoff, the derived optimal SE, the optimal vertical distance of optical transmission network and the optimal transmitted power.

Power Allocation in Cognitive Satellite-Vehicular Networks From Energy-Spectral Efficiency Tradeoff Perspective

With great potential to support multitudinous services and applications in intelligent transportation systems, cognitive satellite-vehicular networks, an emerging paradigm of cognitive satellite-terrestrial networks, are attracting increasing attentions. To realize friendly coexistence of satellite and vehicular networks as well as efficient resource utilization, we investigate power allocation for the cognitive satellite-vehicular network under a realistic 3-D vehicle-to-vehicle channel model. Specifically, by analyzing the characteristics of energy efficiency (EE) and spectral efficiency (SE) performance in different vehicular environments, we first develop an EE–SE tradeoff metric with a preference factor. Based on the developed metric, we formulate and analyze a power allocation strategy from the EE–SE tradeoff perspective while guaranteeing the interference power constraint imposed by satellite communications. Further, utilizing the obtained optimal transmit power, we derive a closed-form expression of the outage probability, through which the impacts of the preference parameter and interference constraints on the performance of vehicular communications can be theoretically analyzed. Finally, numerical results are provided to demonstrate the viability of the EE–SE tradeoff metric and the validity of theoretical analyses.

Spectral-Energy Efficiency Pareto Front in Cellular Networks: A Stochastic Geometry Framework

We compute the spectral-energy efficiency Pareto front in Poisson cellular networks, by formulating a spectral-energy efficiency bi-objective optimization problem as a function of either the transmit power or the density of the base stations. Capitalizing on fundamental theoretical results on weighted Tchebycheff optimization problems applied to strictly quasi-concave functions, we derive analytical expressions of the unique Pareto-optimal solution of the bi-objective problem. We prove that the Pareto front is constituted by a subset of the spectral-energy efficiency tradeoff and that it can be formulated in analytical terms. We identify new functional relations between the Pareto-optimal transmit power and the density of base stations.

Energy-Spectral Efficiency Trade-Off in Underlaying Mobile D2D Communications: An Economic Efficiency Perspective

With a great potential to support multitudinous services and applications, mobile device-to-device (D2D) communications are conceived as a candidate paradigm for the future intelligent transportation systems and mobile Internet. To optimize the performance of underlaying mobile D2D communication systems with mutual interference caused by resource reuse, we propose two scenario-related power allocation schemes and investigate the energy efficiency (EE) and spectral efficiency (SE) trade-off. A 3-D vehicle-to-vehicle channel model is adopted to characterize propagation characteristics in realistic vehicular environments. We observe that a small degradation in EE around its peak value can significantly increase the SE for high vehicular traffic density (VTD) scenarios, while a marginal degradation in SE results in a considerable gain in EE for low VTD scenarios. Therefore, we maximize the SE subject to EE requirement in high VTD scenarios and maximize EE subject to SE requirement in low VTD scenarios. Moreover, to provide comprehensive understanding and further facilitate the practicality of EE-SE trade-off, economic efficiency (ECE) is employed as a general evaluation criterion to assess the efficacy of tradeoff. Finally, extensive simulations are provided to reveal the tradeoff quantitatively and demonstrate the viability that ECE can serve as a general metric for EE–SE trade–off in vehicular environments under different communication conditions.

Energy Efficiency of mmWave Massive MIMO Precoding With Low-Resolution DACs

With the congestion of the sub-6 GHz spectrum, the interest in massive multiple-input multiple-output (MIMO) systems operating on millimeter wave spectrum grows. In order to reduce the power consumption of such massive MIMO systems, hybrid analog/digital transceivers and application of low-resolution digital-to-analog/analog-to-digital converters have been recently proposed. In this work, we investigate the energy efficiency of quantized hybrid transmitters equipped with a fully/partially-connected phase-shifting network composed of active/passive phase-shifters and compare it to that of quantized digital precoders. We introduce a quantized single-user MIMO system model based on an additive quantization noise approximation considering realistic power consumption and loss models to evaluate the spectral and energy efficiencies of the transmit precoding methods. Simulation results show that partially-connected hybrid precoders can be more energy-efficient compared to digital precoders, while fully-connected hybrid precoders exhibit poor energy efficiency in general. Also, the topology of phase-shifting components offers an energy-spectral efficiency trade-off: active phase-shifters provide higher data rates, while passive phase-shifters maintain better energy efficiency.

Secure spectral-energy efficiency tradeoff in random cognitive relay networks

Spectral efficiency (SE) and energy efficiency (EE) in secure communications is of primary importance due to the fact that 5G wireless networks aim to achieve high throughput, low power consumption and high level of security. Nevertheless, maximizing SE and EE are not achievable simultaneously. In this paper, we investigate the SE and EE tradeoff for secure transmission in cognitive relay networks where all nodes are randomly distributed. We first introduce the opportunistic relay selection policy, where each primary transmitter communicates with the primary receiver with the help of a secondary user as a relay. Then, we evaluate the secure SE and secure EE of the primary network based on the outage probabilities analysis. Thirdly, by applying a unified SE-EE tradeoff metric, the secure SE and EE tradeoff problem is formulated as the joint secure SE and EE maximization problem. Considering the non-concave feature of the objective function, an iterative algorithm is proposed to improve secure SE and EE tradeoff. Numerical results show that the opportunistic relay selection policy is always superior to random relay selection policy. Furthermore, the opportunistic relay selection policy outperforms conventional direct transmission policy when faced with small security threat (i.e., for smaller eavesdropper density).

Massive MIMO full-duplex relaying with hardware impairments

Massive multiple-input-multiple-output full-duplex relaying (MM-FDR), which exploits both the benefits of large-scale antenna arrays and full-duplex transmission, is considered as a promising technology to achieve very high spectral efficiency in the future wireless network. Despite the inevitable presence of transceiver impairments due to the use of low-cost hardware components, most of the prior works on MM-FDR assume perfect transceiver hardware which is unrealistic in practice. This paper investigates the impact of hardware impairments on the MM-FDR. Based on the recent experimental results, the effect of hardware impairments is modeled using transmit and receive distortion noises. The end-to-end achievable rate is derived and the scaling behaviors of echo interference due to the full-duplex operation, multi-user interference and effective distortions caused by hardware impairments are obtained. The scaling results show that the achievable rate of MM-FDR is limited by the hardware impairments at the sources and destinations, instead of that at the relay or other interferences, as the number of relay antenna tends to infinity. A low-complexity power control scheme is proposed to further improve the energy efficiency of MM-FDR with hardware impairments. Simulation results show that the proposed scheme can improve the spectral-energy efficiency tradeoff significantly.

On the Secure Spectral-Energy Efficiency Tradeoff in Random Cognitive Radio Networks

Spectrum efficiency (SE) and energy efficiency (EE) in secure communications have attracted much attention recently due to the fact that future wireless networks need to address the issues of high throughput, low power consumption, and high level of security. However, maximizing EE and SE are conflicting objectives, which can hardly be achieved simultaneously. In this paper, we develop a framework to study the SE and EE for secure transmission in underlay random cognitive radio (CR) networks where the primary, secondary, and eavesdropper nodes are randomly distributed according to Poisson point processes. We first analyze the connection outage probability and the secrecy outage probability of the typical links in the random CR network. Then, we evaluate the secure SE and EE in the secondary network based on the outage probability analysis. It is demonstrated that the scheduling scheme of the secondary network (i.e., the transmission power and the intensity of secondary transmitters arouses a tradeoff between the secure SE and EE. Furthermore, applying a unified secure SE-EE tradeoff metric, which condenses the secure SE and EE into a single utility function with a tradeoff factor, we formulate the joint secure SE and EE optimization problem with respect to the scheduling scheme of the secondary network. An iterative algorithm is proposed based on the separation optimization of the transmission power and the intensity. The analytical and simulation results show the effects of system parameters on the optimal solutions and secure SE-EE tradeoff. We also verify that the optimal scheduling scheme can improve the secure SE-EE tradeoff. Using these results, one can easily understand and make the secure SE-EE tradeoff in random CR networks.

Full-Duplex Massive MIMO AF Relaying With Semiblind Gain Control

This paper proposes an amplify-and-forward-based massive multiple-input–multiple-output full-duplex relaying (AF-MM-FDR) protocol, where multiple source–destination pairs communicate simultaneously with a common full-duplex relay. A zero-forcing (ZF)-based relay transceiver design with semiblind gain control is presented, considering the problem of relay oscillation. The asymptotic expression of end-to-end signal-to-interference-plus-noise power (SINR) is derived under the general power scaling scheme. The scaling behaviors of echo interference (EI) and effective channel estimation error are determined. Scaling results show that the deployment of very large antenna arrays at the relay has the potential to eliminate the effect of EI due to the full-duplex operation, if the power scaling scheme is selected properly. Moreover, based on the asymptotic analysis, a low-complexity power control scheme is proposed to optimize the spectral efficiency of AF-MM-FDR. Simulation results show that the proposed power control scheme improves the spectral–energy efficiency tradeoff of AF-MM-FDR significantly.

Energy–Spectral Efficiency Tradeoff in Cognitive Radio Networks

In this paper, we propose a general framework to evaluate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in cognitive radio networks (CRNs). The proposed framework is discussed in three typical CRN paradigms: underlay CRNs (UCRNs), overlay CRNs (OCRNs), and interweave CRNs (ICRNs). The EE–SE relation for three CRNs is expressed in the closed-form formulation, in which the optimal (suboptimal) EE solution as the function of SE is deduced with the corresponding limits. The theoretical analysis and numerical results indicate that the EE–SE relation in CRNs is not contrary, i.e., an optimal EE–SE tradeoff can be achieved. The proposed framework provides a useful guidance in the design of practical green CRNs.

Spectral-Energy Efficiency Tradeoff in Relay-Aided Massive MIMO Cellular Networks With Pilot Contamination

This paper concerns with a relay-aided massive multiple input multiple output (MIMO) cellular network. The exact closed-form expressions of both spectral efficiency (SE) and energy efficiency (EE) are obtained for downlink single-cell multi-user multi-relay massive MIMO transmission in the pilot-contaminated regime, where the number of users is larger than the pilot sequence length. Based on the theoretical results of SE and EE, we investigate the effects of some system parameters [such as number of antennas at the base station (BS), transmit power at the BS, and transmit power of each relay station (RS)] on system performance, and achieve the tradeoff between SE and EE by power control. Specifically, the tradeoff problem is solved by joint optimization over transmit power $P$ of the BS and transmit power $p_{r}$ of each RS, so as to maximize EE while satisfying the SE requirement. With the proposition that EE function is strictly quasi-concave with either $P$ or $p_{r}$ , we propose two optimization methods: 1-D searching and alternate optimization. Comparatively, the former achieves a better performance, while the latter has a lower complexity. Simulation results validate the effectiveness of the two methods.

Spectral and Energy Efficiency Analysis for Cognitive Radio Networks

Cognitive radio (CR) is considered one of the prominent techniques for improving the utilization of the radio spectrum. A CR network (i.e., secondary network) opportunistically shares the radio resources with a licensed network (i.e., primary network). In this work, the spectral-energy efficiency trade-off for CR networks is analyzed at both link and system levels against varying signal-to-noise ratio (SNR) values. At the link level, we analyze the required energy to achieve a specific spectral efficiency for a CR channel under two different types of power constraint in different fading environments. In this aspect, besides the transmit power constraint, interference constraint at the primary receiver (PR) is also considered to protect the PR from a harmful interference. Whereas at the system level, we study the spectral and energy efficiency for a CR network that shares the spectrum with an indoor network. Adopting the extreme-value theory, we are able to derive the average spectral and energy efficiency of the CR network. It is shown that the spectral efficiency depends upon the number of the PRs, the interference threshold, and how far the secondary receivers (SRs) are located. We characterize the impact of the multi-user diversity gain of both kinds of users on the spectral and energy efficiency of the CR network. Our analysis also proves that the interference channels (i.e., channels between the secondary transmitter and PRs) have no impact on the minimum energy efficiency.

Spectral–Energy Efficiency Tradeoff in Full-Duplex Two-Way Relay Networks

Owing to its high spectral efficiency (SE), two-way relaying (TWR) has aroused tremendous research interests. Recently, substantial progress in self-interference (SI) cancelation makes full-duplex (FD) TWR practical. For this new paradigm, analyzing spectral–energy efficiency (SE–EE) tradeoff is crucial, which has not been addressed in the existing works in the literature. In this paper, the SE–EE tradeoff in a FDTW relay network with amplify-and-forward (AF) relaying is studied by considering the residual SI at the relay. An optimization problem is formulated to maximize the EE under the SE requirement and the maximum transmission power constraints by adjusting the transmission power of the terminals and the amplification gain of the relay. A lower complexity iterative optimization algorithm is developed to solve the optimization problem. Simulation results show that: 1) the proposed algorithm can achieve optimal EE that is consistent to the one obtained by the exclusive searching method; 2) the FDTW relay network can achieve higher SE but lower optimal EE compared with the half-duplex (HD) one; and 3) the optimal EE is insensitive to the residual power of SI, when the relay is located near either terminal.

Cognitive radio in 5G: a perspective on energy-spectral efficiency trade-off

A cognitive cellular network, which integrates conventional licensed cellular radio and cognitive radio into a holistic system, is a promising paradigm for the fifth generation mobile communication systems. Understanding the trade-off between energy efficiency, EE, and spectral efficiency, SE, in cognitive cellular networks is of fundamental importance for system design and optimization. This article presents recent research progress on the EE-SE trade-off of cognitive cellular networks. We show how EE-SE trade-off studies can be performed systematically with respect to different architectures, levels of analysis, and capacity metrics. Three representative examples are given to illustrate how EE-SE trade-off analysis can lead to important insights and useful design guidelines for future cognitive cellular networks.

Energy spectral efficiency tradeoff in downlink OFDMA network

SummarySpectral efficiency (SE) is an important metric in traditional wireless network design. However, as the development of high‐data rate services and rapidly increase of energy consumption, energy efficiency (EE) has received more and more attention. In this paper, we investigate the EE–SE tradeoff in downlink OFDMA network. Different from previous researches, we try to optimize EE and SE simultaneously. First, the problem is formulated as a multiobjective optimization problem (MOP), and its Pareto optimal set is characterized. Then, we convert the MOP to a single‐objective optimization problem (SOP) by the weighted linear sum method and show that it is neither quasi‐convex nor quasi‐concave. After that, a novel algorithm using particle swarm optimization is proposed to solve the SOP. Simulation results validate that the proposed algorithm can efficiently reduce total transmit power and improve EE, although the cost is sacrificing some SE, which could be used to design an flexible energy efficient network in the future.Copyright © 2014 John Wiley & Sons, Ltd.

Spectral-Energy Efficiency Tradeoff in Relay-Aided Cellular Networks

A relay cooperation scheme is proposed for the downlink of multicell multiple-input-multiple-output cellular networks. The relay stations (RSs) will cooperatively transmit the signal replicas of all the user equipments obtained during the broadcast phase. We consider different RS decoding strategies during the broadcast phase and joint relay transmission with different degrees of channel state information (CSI) sharing during the relay phase. We also propose the partial semi-orthogonal user selection (PSUS) method designed specifically for relay cooperation. The spectral and energy efficiencies are then evaluated for the relay cooperation scheme. Its cooperative costs for different cooperation levels are also investigated. Simulation results indicate that joint RS decoding outperforms independent RS decoding but a cooperative link with a bit rate of an order of magnitude greater than that achievable by the relay network is required. Compared to the competing user selection methods that require global CSI, the proposed PSUS method utilized for relay phase joint transmission operates at less than half of the cooperative cost while introduces only a slight degradation in system performance.

Energy-Spectral Efficiency Trade-Off in Virtual MIMO Cellular Systems

Virtual multiple-input multiple-output (V-MIMO) technology promises significant performance enhancements to cellular systems in terms of spectral efficiency (SE) and energy efficiency (EE). How these two conflicting metrics scale up in large cellular V-MIMO networks is unclear. This paper studies the EE-SE trade-off of the uplink of a multi-user cellular V-MIMO system with decode-and-forward type protocols. We first express the trade-off in an implicit function and further derive closed-form formulas of the trade-off in low and high SE regimes. Unlike conventional MIMO systems, the EE-SE trade-off of the V-MIMO system is shown to be susceptible to many factors including protocol design (e.g., resource allocation) and scenario characteristics (e.g., user density). Focusing on the medium and high SE regimes, we propose a heuristic resource allocation algorithm to optimize the EE-SE trade-off. The fundamental performance limits of the optimized V-MIMO system are subsequently investigated and compared with conventional MIMO systems in different scenarios. Numerical results reveal a surprisingly chaotic behavior of V-MIMO systems when the user density scales up. Our analysis indicates that low frequency reuse factor, adaptive resource allocation, and user density control are critical to harness the full benefits of cellular V-MIMO systems.