Energy Efficiency Spectral Efficiency Tradeoff Research Articles

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.

Trade-Off Energy and Spectral Efficiency in a Downlink Massive MIMO System

Massive multiple-input multiple-output (MIMO) technology has been proven to be a viable strategy for balancing the trade-off between energy efficiency (EE) and spectral efficiency (SE), which is key to the design of fifth-generation wireless cellular networks. In this work, we investigate the trade-off between EE and SE for downlink massive MIMO in wireless communication networks with respect to the power allocation problem. We maximize EE by deriving the signal-to-interference noise ratio for higher SE in the upper bound and propose that the EE–SE trade-off can be maximized when formulated as a Pareto-optimal solution based on the optimization problem. A Lagrange dual decomposition method is also developed for both transmit power allocation and the number of available antennas. From the simulation results, the maximum trade-off between EE and SE can be achieved based on the optimal transmit power allocation in every cell and when the number of base stations for the value of SE is high.

Energy and spectral efficiency tradeoff in massive MIMO systems with multi-objective adaptive genetic algorithm

Spectral efficiency (SE) and energy efficiency (EE) are both important metrics in massive multiple-input multiple-output (MIMO) systems. However, maximizing EE and SE is always conflicting with each other, and they can hardly be achieved simultaneously. In this paper, we focus on the tradeoff optimization between EE and SE in multiuser massive MIMO systems in terms of the number of transmit antennas and the transmit power. Different from the previous EE-oriented or SE-oriented method, the EE–SE tradeoff problem is formulated into a multi-objective optimization problem. To efficiently attain the Pareto optimal front (POF) of EE–SE tradeoff, a multi-objective adaptive genetic algorithm, inspired by the non-dominated sorting genetic algorithm (NSGA-II), is proposed to improve the convergence speed. Experimental comparisons against several well-known multi-objective algorithms show that the proposed algorithm can quickly adapt to the true POF of EE–SE tradeoff and maintain good performance on benchmark functions in terms of the adopted performance metrics.

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.

On the Spectral Efficiency of Energy Constrained Short-Range Communicating Systems

Recently the energy efficiency (EE) in wireless communication is becoming one of the key performance metric for wireless communicating systems. For battery driven system like wireless sensor networks and ad-hoc networks, the energy conservation is a critical factor for node life. In addition, the spectral efficiency (SE) has been traditionally used as a performance index for wireless transmission. This paper investigates the optimum spectral to energy efficiency tradeoff especially for short range communications. The analysis starts with the Shannon case in additive white gaussian noise channel where some theoretic results are developed when considering both transmit and circuit energy. Then, point to point communication system with uncoded M-ary quadrature amplitude modulation (MQAM) is considered. At the device layer, a system level power consumption model is proposed. At the physical layer, a novel and accurate approximation of the bit error rate (BER) function of the signal to noise ratio is made. The total energy per bit is formulated and the link between the Shannon limit capacity and MQAM based communication is established. The impact of distance, bandwidth, power consumption and BER as a quality-of-service parameter on EE–SE tradeoff is analyzed. It is shown that, varying distance, bandwidth and circuit power consumption induce more impact in the low SE regime whereas, the BER has more impact on the high SE regime. Moreover, the energy optimal spectral efficiency for MQAM is obtained in closed-form and confirmed by numerical results.

Energy-Spectral-Efficiency Tradeoff in Interference-Limited Wireless Networks

Spectral efficiency (SE) is an important metric in traditional wireless network design. However, as the development of high-data rate services and rapid increase of energy consumption, energy efficiency (EE) has received more and more attention. In this paper, we investigate the EE–SE tradeoff problem in interference-limited wireless networks. Different from previous researches, we try to optimize EE and SE simultaneously. Firstly, the problem is formulated as a multi-objective optimization problem (MOP), with the constraint of transmit power limit. Then, we convert the MOP to a single-objective optimization problem by the weighted linear sum method. We present an algorithm utilizing difference between two convex functions programming (DCP) to handle with SE optimization problem (SD). EE optimization problem can be solved by an algorithm (EFD) consists of fractional programming embedded with DCP. While for EE–SE tradeoff problem, a particle swarm optimization algorithm is proposed (ESTP) to deal with it. Simulation results validate that the proposed algorithm can efficiently balance EE and SE by adjusting the value of weighted coefficient, which could be used to design a flexible energy efficient network in the future.

User-Centric Precoding Designs for the Non-Regenerative MIMO Two-Way Relay Systems

In this letter, we jointly design the source and relay precoders for non-regenerative multi-input multi-output two-way relay systems from the user-centric perspective. The two sources are assumed to be both energy efficiency (EE) desirable and spectral efficiency (SE) desirable. We aim at studying the EE–SE tradeoff between the two sources. The resulting problem is a non-convex multi-objective problem. To address this issue, an iterative algorithm is proposed to design the relay precoding matrix and source beamforming vectors alternatively. We also show that the proposed iterative algorithm is guaranteed to converge.

Energy and Spectral Efficiency Tradeoff With User Association and Power Coordination in Massive MIMO Enabled HetNets

In this letter, we investigate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) while ensuring proportional rate fairness in massive multiple-input multiple-output enabled heterogenous networks, where user association and power coordination are jointly considered. It is first formulated as a multi-objective optimization problem, and then transformed into a single-objective optimization problem. To solve this mixed-integer non-convex problem, an effective algorithm is developed, where the original problem is separated into lower level power coordination problem and master user association problem. Simulation results verify that our proposed algorithm can significantly improve the performance of EE–SE tradeoff and obtain higher rate fairness compared with other algorithms.

Energy Efficiency and Spectral Efficiency Tradeoff for Asymmetric Two-Way AF Relaying With Statistical CSI

Both energy efficiency (EE) and spectral efficiency (SE) are two important design criteria that can hardly be achieved simultaneously. In this paper, we investigate the EE–SE tradeoff for a two-way relaying system with amplify-and-forward (AF) strategy. Applying a unified EE–SE tradeoff metric, a power-allocation problem is formulated as the joint EE and SE maximization problem with a tradeoff factor. In particular, only statistical channel-state information (CSI) is required, and the asymmetric traffic requirements are taken into consideration in our design. Through the exploitation of the theorem of nonlinear fractional programming, a unique closed-form optimum solution is obtained, and some useful insights are also achieved. It has been proved that the provided optimal solution is Pareto optimal for EE–SE optimization. Utilizing these results, one can flexibly make the tradeoff between EE and SE by simply setting the tradeoff factor. Simulation results highlight the effect of the proposed power-allocation scheme.

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.

Energy Efficiency–Spectral Efficiency Tradeoff: A Multiobjective Optimization Approach

In this paper, we consider the resource-allocation problem for energy efficiency (EE)–spectral efficiency (SE) tradeoff. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or on the achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a tradeoff parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then, we apply the generalized framework of the resource allocation for the EE–SE tradeoff to optimally allocate the subcarriers' power for orthogonal frequency-division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the tradeoff parameter and study the effect of the estimation error, transmission power budget, and channel-to-noise ratio on the multiobjective optimization.

Energy efficiency analysis of hybrid-ARQ relay-assisted schemes in LTE-based systems

This work deals with the analysis of energy efficiency (EE) issues of hybrid automatic repeat request (HARQ) protocols such as Chase combining (CC) and incremental redundancy (IR), in a LTE baseband-based half-division duplex relay-assisted network. The EE performance is highly dependent on delay and circuitry power consumption, i.e., baseband and radio-frequency (RF) parts, and the effects of these components are investigated for amplify and forward (AF) and decode and forward (DF) protocols. Moreover, a realistic estimation of the baseband power consumption is provided. Our contributions in this paper can be summarized as follows: (1) an accurate estimation of power consumption of the main blocks of the LTE baseband is provided based on a real field-programmable gate array (FPGA) target and is integrated to a global energy consumption model (2) based on the previous power consumption evaluation; energy-efficiencies of DF protocol with HARQ-CC and HARQ-IR are investigated with various modulation orders; in addition, a quite insightful study of the energy efficiency-spectral efficiency trade-off is conducted, and (3) DF and AF protocols with HARQ are compared in terms of EE, and recommendations are suggested in order to jointly enhance the QoS and the energy efficiency of wireless systems.

Energy Efficient Sparse Beamforming for Multi-user MIMO Systems with Non-ideal Power Amplifiers

In this paper, we consider energy-efficiency (EE) optimization problems with nonideal power amplifier (PA) models, per-antenna power constraints, and minimal spectral efficiency (SE) requirements in block-diagonalization-based multiuser multiple-input–multiple-output (MU-MIMO) systems. In the problem formulation, a joint optimization of the transmit covariance and the active transmit antenna set at the base station is considered. In general, the problem is a mixed-integer fractional programming problem, and it is difficult to solve it globally optimally. By reformulating the original problem as a sparse beamforming design problem and using a successive convex approximation method, we propose an iterative algorithm to solve it locally. In each iteration step, a concave fractional programming is solved, and the solution can be expressed in closed form with the help of the Lagrange dual method. Simulation results are used to verify the performance of our proposed algorithms. We also study the EE–SE tradeoff for the considered system. In fact, the relationship between EE and SE under an ideal PA model is not accurate for realistic systems. We characterize the EE–SE tradeoff under nonideal PA models by solving the EE maximization problems under different SE values. In this way, we can also shed light on the design of the system parameters to optimize the EE–SE curve. We find that with nonideal PA considered, the SE corresponding to the optimal EE will increase, compared with the ideal case. If we design the system parameters according to the optimal SE under an ideal PA model to maximize the EE, both the EE and the SE of the realistic system will decrease. We also find that when the proposed antenna selection algorithm is applied, the achieve region of the EE and the SE is expanded, particularly when the SE is low. In other words, the EE–SE win–win region is enlarged, and the EE–SE tradeoff is improved.

Energy and spectral efficiency tradeoff for massive MIMO systems with transmit antenna selection

This correspondence investigates the fundamental tradeoff between the spectral efficiency (SE) and energy efficiency (EE) for massive multiple-input multiple-output (MIMO) systems with linear precoding and transmit antenna selection, where both the circuit power consumption and the large-scale fading are considered. The EE and SE are optimized with respect to the number of transmit antennas and transmit power, and consequently, we formulate the EE–SE tradeoff as a mixed-integer-continuous-variable multiobjective optimization (MOO) problem. Using the derived EE–SE relations, the properties of the Pareto front for the EE–SE tradeoff are analyzed. To solve the complicated MOO problem, we develop two algorithms: the weighted-sum particle swarm optimization (WS-PSO) algorithm and the normal-boundary-intersection particle swarm optimization (NBI-PSO) algorithm. Simulation results show that the two algorithms can achieve the Pareto optimal EE-SE tradeoff, and NBI-PSO provides more evenly distributed solutions than WS-PSO.

Correction to “Energy Efficiency-Spectral Efficiency Trade-Off of Transmit Antenna Selection” [Dec 14 4293-4303

Presents corrections made to the paper, “Energy Efficiency-Spectral Efficiency Trade-Off of Transmit Antenna Selection” (Rayel, O.K., et al; IEEE Trans. Commun., vol. 62, no. 12, pp. 4293–4303, Dec. 2014).

Energy Efficiency-Spectral Efficiency Trade-Off of Transmit Antenna Selection

We investigate the energy efficiency-spectral efficiency (EE-SE) trade-off of transmit antenna selection/maximum ratio combining (TAS) scheme. A realistic power consumption model (PCM) is considered, and it is shown that using TAS can provide significant energy savings when compared to multiple-input multiple-output (MIMO) in the low to medium SE region, regardless the number of antennas, as well as outperform transmit beamforming scheme (MRT) for the entire SE range. For a fixed number of receive antennas, our results also show that the EE gain of TAS over MIMO becomes even greater as the number of transmit antennas increases. The optimal value of SE that maximizes the EE is obtained analytically, and confirmed by numerical results. Moreover, the influence of receiver correlation is also evaluated and it is shown that considering a non-realistic PCM can lead to mistakes when comparing TAS and MIMO.

On the Energy Efficiency-Spectral Efficiency Trade-Off of Distributed MIMO Systems

In this paper, the trade-off between energy efficiency (EE) and spectral efficiency (SE) is analyzed for both the uplink and downlink of the distributed multiple-input multiple-output (DMIMO) system over the Rayleigh fading channel while considering different types of power consumption models (PCMs). A novel tight closed-form approximation of the DMIMO EE-SE trade-off is presented and a detailed analysis is provided for the scenario with practical antenna configurations. Furthermore, generic and accurate low and high-SE approximations of this trade-off are derived for any number of radio access units (RAUs) in both the uplink and downlink channels. Our expressions have been utilized for assessing both the EE gain of DMIMO over co-located MIMO (CMIMO) and the incremental EE gain of DMIMO in the downlink channel. Our results reveal that DMIMO is more energy efficient than CMIMO for cell edge users in both the idealistic and realistic PCMs; whereas in terms of the incremental EE gain, connecting the user terminal to only one RAU is the most energy efficient approach when a realistic PCM is considered.

A Very Tight Approximation of the SISO Energy Efficiency-Spectral Efficiency Trade-Off

Beside the well-established spectral-efficiency (SE), energy-efficiency (EE) is currently becoming an important performance evaluation metric, which in turn makes the EE-SE trade-off as a prominent criterion for efficiently designing future communication systems. In this letter, we propose a very tight closed-form approximation (CFA) of this trade-off over the single-input single-output (SISO) Rayleigh flat fading channel. We first derive an improved approximation of the SISO ergodic capacity by means of a parametric function and then utilize it for obtaining our novel EE-SE trade-off CFA, which is also generalized for the symmetric multi-input multi-output channel. We compare our CFA with existing CFAs and show its improved accuracy in comparison with the latter.

On the Energy Efficiency-Spectral Efficiency Trade-off over the MIMO Rayleigh Fading Channel

Along with spectral efficiency (SE), energy efficiency (EE) is becoming one of the key performance evaluation criteria for communication system. These two criteria, which are conflicting, can be linked through their trade-off. The EE-SE trade-off for the multi-input multi-output (MIMO) Rayleigh fading channel has been accurately approximated in the past but only in the low-SE regime. In this paper, we propose a novel and more generic closed-form approximation of this trade-off which exhibits a greater accuracy for a wider range of SE values and antenna configurations. Our expression has been here utilized for assessing analytically the EE gain of MIMO over single-input single-output (SISO) system for two different types of power consumption models (PCMs): the theoretical PCM, where only the transmit power is considered as consumed power; and a more realistic PCM accounting for the fixed consumed power and amplifier inefficiency. Our analysis unfolds the large mismatch between theoretical and practical MIMO vs. SISO EE gains; the EE gain increases both with the SE and the number of antennas in theory, which indicates that MIMO is a promising EE enabler; whereas it remains small and decreases with the number of transmit antennas when a realistic PCM is considered.

On the Energy Efficiency-Spectral Efficiency Trade-Off in the Uplink of CoMP System

In this paper, we derive a generic closed-form approximation (CFA) of the energy efficiency-spectral efficiency (EE-SE) trade-off for the uplink of coordinated multi-point (CoMP) system and demonstrate its accuracy for both idealistic and realistic power consumption models (PCMs). We utilize our CFA to compare CoMP against conventional non-cooperative system with orthogonal multiple access. In the idealistic PCM, CoMP is more energy efficient than non-cooperative system due to a reduction in power consumption; whereas in the realistic PCM, CoMP can also be more energy efficient but due to an improvement in SE and mainly for cell-edge communication and small cell deployment.