A Base Station DTX Scheme for OFDMA Cellular Networks Powered by the Smart Grid

To meet the demand for higher throughput, improved coverage and enhanced reliability, future wireless cellular networks face significant technical challenges. One promising solution is to place relay stations between transmitters and receivers in the cellular network. Meanwhile, as energy consumption reduction has been an important concern for the wireless industry, energy-efficient communications is of prime interest for future networks. In this paper, we study whether and how relays can improve the energy efficiency of cellular networks. Specifically, the energy efficiency of relay-assisted cellular networks is analyzed using tools of stochastic geometry. We first derive the coverage probability for the macro base station (MBS) to user (UE), the MBS to relay station (RS), and the RS to UE links, and then we model the power consumption at the MBS and RS. Based on the analytical model and expressions, the energy efficiency of relay-assisted cellular networks is then evaluated and is shown to be strictly quasi-concave on the transmit power for MBS to UE link or the RS to UE link. Numerical results show that the energy efficiency first improves while it hits a ceiling as the MBS density increases.

Cooperative relaying is a promising technology that can improve the spectral and energy efficiency of cellular networks. However, the deployed relays consume a lot of energy and system resources. To improve the energy efficiency of the relay-assisted cellular networks, this paper considers the use of energy harvesting (EH) on relay nodes. A random sleeping strategy is also introduced in macro base stations (MBS) as a possible method to reduce energy consumption. In this paper, an analytical model is proposed to investigate the energy efficiency of cellular networks with EH relays and sleep mode strategy. Numerical results confirm a significant energy efficiency gain of the proposed networks comparing to the cellular networks with non-EH relays and MBSs without sleep mode strategy. The effects of the density and transmit power of MBSs on energy efficiency are also given through simulations.

Though cooperative relaying is believed to be a promising technology to improve the energy efficiency of cellular networks, the relays' static power consumption might worsen the energy efficiency therefore can not be neglected. In this paper, we focus on whether and how the energy efficiency of cellular networks can be improved via relays. Based on the spatial Poisson point process, an analytical model is proposed to evaluate the energy efficiency of relay-assisted cellular networks. With the aid of the technical tools of stochastic geometry, we derive the distributions of signal-to-interference-plus-noise ratios (SINRs) and mean achievable rates of both non-cooperative users and cooperative users. The energy efficiency measured by “bps/Hz/W” is expressed subsequently. These established expressions are amenable to numerical evaluation and corroborated by simulation results.

Cell discontinuous transmission (DTX) has been proposed as a solution to reduce the energy consumption of cellular networks. This paper investigates the impact of network traffic load on the spectral and energy efficiency of cellular networks with DTX. The signal-to-interference-plus-noise ratio (SINR) distribution as a function of traffic load is derived first. Then, the sufficient condition for ignoring thermal noise and simplifying the SINR distribution is investigated. Based on the simplified SINR distribution, the network spectral and energy efficiency as functions of network traffic load are derived. It is shown that the network spectral efficiency increases monotonically in traffic load, while the optimal network energy efficiency depends on the ratio of the sleep-mode power consumption to the active-mode power consumption of base stations. If the ratio is larger than a certain threshold, the network energy efficiency increases monotonically with network traffic load and is maximized when the network is fully loaded. Otherwise, the network energy efficiency first increases and then decreases in network traffic load. The optimal load can be identified with a binary search algorithm. The power ratio threshold depends solely on the path loss exponent $\alpha$ , e.g., 56% for $\alpha = 4$ . All these analytic results are further validated by the numerical simulations.

Energy efficiency (EE) of cellular networks has attracted considerable attention recently. However, EE of relay-assisted cellular networks where the macro base stations (MBSs) are equipped with the multi-antenna has not been thoroughly addressed. This paper considered the downlink transmission of multi-antenna relay-assisted cellular networks, meanwhile, a strategic sleep scheme was used in relay stations (RSs), which dynamically adjusted the RS working mode according to whether the number of users serviced by the relay exceeds a given threshold. A geometric model was built to derive the coverage probability and mean achievable rate from the MBSs to user (UE), the MBS to RS, the RS to UE links and analyze the system EE. It is shown that the energy efficiency of cellular network with strategic sleep RS is slightly higher than that of cellular network with non-sleeping strategy. Furthermore, the MBS equipped with multi-antenna has better impact on energy efficiency and spectral efficiency than the MBS with single antenna.

Green communications has received much attention recently. For cellular networks, the base stations (BSs) account for more than 50 percent of the energy consumption of the networks. Therefore, reducing the power consumption of BSs is crucial to enhance the energy efficiency of cellular networks. Meanwhile, the mobile data traffic is expected to increase exponentially. To accommodate the increasing data traffic with the limited radio frequency, enhancing the spectrum efficiency is critical for next generation cellular networks. In this paper, we propose an auction-based energy-spectrum trading scheme which exploits the cooperation between primary base stations (PBSs) and the secondary base stations (SBSs) to enhance the energy as well as spectrum efficiency of cellular networks. In the cooperation, by leveraging cognitive radio, PBSs share the licensed spectrum with SBSs, and the SBSs provide data service to the primary users under its coverage utilizing the shared bandwidth. The cooperation between PSBs and SBSs can significantly improve the energy and spectral efficiency of cellular networks. However, optimizing the bandwidth sharing between PBSs and SBSs is an NP-hard problem. Solving such problem using centralized algorithms is not computationally efficient, especially when considering a large number of PBSs and SBSs. Thus, we design an auction-based decentralized mechanism to enable the cooperation between PBSs and SBSs. Simulation results that demonstrated the performance and viability of the proposed decentralized mechanism.

Chapter 11 - Cell-Coverage-Area Optimization Based on Particle Swarm Optimization (PSO) for Green Macro Long-Term Evolution (LTE) Cellular Networks

Recently, green communications has received much attention. Cellular networks are among the major energy hoggers of communication networks, and their contributions to the global energy consumption increase fast. Therefore, greening cellular networks is crucial to reducing the carbon footprint of information and communications technology. In this article, we overview the multicell cooperation solutions for improving the energy efficiency of cellular networks. First, we introduce traffic-intensity-aware multicell cooperation, which adapts the network layout of cellular networks according to user traffic demands in order to reduce the number of active base stations. Then we discuss energy-aware multicell cooperation, which offloads traffic from on-grid base stations to off-grid base stations powered by renewable energy, thereby reducing the on-grid power consumption. In addition, we investigate improving the energy efficiency of cellular networks by exploiting coordinated multipoint transmissions. Finally, we discuss the characteristics of future cellular networks, and the challenges in achieving energy-efficient multicell cooperation in future cellular networks.

Reducing the power consumption of base stations is crucial to enhancing the energy efficiency of cellular networks. As the number of mobile users increases exponentially, enhancing the spectrum efficiency is also critical in order to accommodate more users. In this paper, by exploiting the cooperation between secondary base stations (SBSs) and primary base stations (PBSs), we propose a new energy spectrum trading model to enhance the energy as well as spectrum efficiency of cellular networks. In our scheme, by leveraging cognitive radio, PBSs share some portion of their licensed spectrum with SBSs, and SBSs, in exchange, provide data service to the primary users under their coverage. We first prove that the power consumption minimization problem is NP-hard. Then, to decrease the computational complexity, we design an efficient distributed auction model including green energy aware bidding (GEAB) and adaptive bid selection (ABS) algorithms, to achieve a good approximation of the optimal solution in less time. Our simulation results show that the cooperation between PBS and SBSs via ABS and GEAB algorithms can significantly improve the energy and spectral efficiency of cellular networks by nearly doubling the number of offloaded users and reducing the PBS power consumption by up to 40% as compared to existing approaches. Furthermore, green energy utilization among SBSs is increased by nearly 25%.

Due to the cooperation diversity, Coordinated MultiPoint (CoMP) transmission may potentially improve energy efficiency of cellular networks. The main purpose of this paper is to analyze this potential. By employing CoMP, there are two schemes to improve energy efficiency; one is to decrease the transmission power of base stations (CDTP) without changing cells' size and re-deploying base stations (BSs); another one is to reduce the number of BSs by increasing coverage area (CICA). In this paper, the coverage gain brought by CoMP technology given the guaranteed coverage ratio performance is firstly performed. Based on that, the energy efficiency gain of CDTP and CICA is investigated. It showed that comparing to the scheme of CDTP which is nearly no potential to improve energy efficiency, CICA can improve energy efficiency by more than 15%. This result could provide references for operators when carrying out new cellular deployments.

In this paper, the relationship between the energy efficiency and spectrum efficiency in a two-cell cellular network is obtained, and the impact of multi-antenna on the energy efficiency of cellular network is analyzed and modeled based on two-state Markovian wireless channels. Then, the energy efficiency of multi-cell cellular networks with co-channel interference is investigated. Simulation results verify the proposed model and the energy-spectrum efficiency tradeoffs in cellular networks with multi-antenna and co-channel interference.

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogenous network deployment based on micro, pico and femtocells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technology.

Energy efficiency in cellular networks is a growing concern for cellular operators with regard to maintaining profitability and reducing their overall environmental impact. Because evolved node Bs (eNBs) for long-term evolution wireless cellular networks are deployed to accommodate peak traffic, they are underutilized most of the time, especially under low-traffic conditions. Hence, switching eNBs on and off in accordance with traffic pattern variations is considered to be an effective method of improving energy efficiency in cellular networks. However, two main concerns of network operators when applying this technique are coverage issues and securing radio service for an entire area in response to the increased size of some cells to provide coverage for cell areas that are switched off. This study focuses on the parameters that affect coverage in order to find a balance between cellular network energy consumption and the area of cell coverage. To achieve this goal, particle swarm optimization, a bio-inspired computational method, has been adopted in this study to maximize the cell coverage area under the constraints of the transmission power of the eNB $$(P_{tx})$$(Ptx), the total antenna gain (G), the bandwidth (BW), the signal-to-interference-plus-noise ratio (SINR), and shadow fading $$(\sigma )$$(�). In addition, the study investigated potential for gains in operational expenditures by operating eNB on solar energy. The optimum criteria, including economic, technical and environmental feasibility parameters, were analyzed using the HOMER.

In cellular networks, the base station (BSs) is obligated to more than 50% energy consumption of the networks. Therefore, reducing the power consumption of BSs is crucial to enhance the energy efficiency of cellular networks. Cognitive radio, an enabling technology, is a new system design paradigm for next cellular networks. In this paper, we proposed an optimal bandwidth sharing based on the selection scheme which exploited the cooperation between multiple primary base stations (PBSs) and several secondary base stations (SBSs) to enhance the spectrum as well as energy efficiency of cellular networks.

This paper investigates the collaboration between multiple mobile operators to optimize the energy efficiency of cellular networks, maximize their profits or achieve or tradeoff between both objectives. Mobile operators cooperate together by eliminating redundant base stations (BSs) using a low complexity algorithm that aims to maximize their objective functions subject to a quality of service constraint. The problem is modeled as a two-level Stackelberg game: a mobile operator level and a smart grid level. Indeed, in our framework, we assume that cellular networks are powered by multiple energy providers existing in the smart grid characterized by different pollutant levels in addition to renewable energy source deployed in BS sites. The objective is to find the best active BS combination and the optimal procurement decision needed to the network operation during collaboration by considering electricity real-time pricing. Our study includes the daily traffic variation in addition to the daily green energy availability. Our simulation results show a significant saving in terms of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions compared to the non-collaboration case and that cooperative mobile operators exploiting renewables are more awarded than traditional operators.