Energy and spectral efficient microcell deployment in heterogeneous cellular networks

In this paper author demonstrates the relationship between spectral efficiency and energy efficiency for 10 Gbps, 40 Gbps and 100 Gbps transmission systems with NRZ-OOK, NRZ-DPSK and DP-QPSK modulation formats respectively. The focus of this research is the wavelength division multiplexed (WDM) transmission systems with Forward Error Correction (FEC) technology with required Bit Error Rate (BER) level that does not exceed 10−3. For this purpose the signal BER level versus cross-channel interval response is evaluated. Obtained data was used for the regeneration length calculations with purpose to define the number of regeneration steps for 200km and 2600km transmission systems. In order to observe relationship between spectral and energy efficiency, power consumption was calculated using different crosschannel intervals −37.5 GHz, 50 GHz and 100 GHz, by means of what different spectral efficiencies were reached. The total power consumption of transmission system was calculated by defining the quantity and power consumption values for all WDM system elements that require electrical energy. In this paper author demonstrates how the amount of transmitted information influence the total system power consumption in each considered transmission system and by using obtained data and spectral efficiency data, the systems energy efficiencies were calculated.

With the exponential increase in mobile internet traffic driven by a new generation of wireless devices, future cellular networks face a great challenge to meet this overwhelming demand of network capacity. At the same time, the demand for higher data rates and the ever-increasing number of wireless users led to rapid increases in power consumption and operating cost of cellular networks. One potential solution to address these issues is to overlay small cell networks with macrocell networks as a means to provide higher network capacity and better coverage. However, the dense and random deployment of small cells and their uncoordinated operation raise important questions about the energy efficiency implications of such multi-tier networks. Another technique to improve energy efficiency in cellular networks is to introduce active/sleep (on/off) modes in macrocell base stations. In this paper, we investigate the design and the associated tradeoffs of energy efficient cellular networks through the deployment of sleeping strategies and small cells. Using a stochastic geometry based model, we derive the success probability and energy efficiency in homogeneous macrocell (single-tier) and heterogeneous K-tier wireless networks under different sleeping policies. In addition, we formulate the power consumption minimization and energy efficiency maximization problems, and determine the optimal operating regimes for macrocell base stations. Numerical results confirm the effectiveness of switching off base stations in homogeneous macrocell networks. Nevertheless, the gains in terms of energy efficiency depend on the type of sleeping strategy used. In addition, the deployment of small cells generally leads to higher energy efficiency but this gain saturates as the density of small cells increases. In a nutshell, our proposed framework provides an essential understanding on the deployment of future green heterogeneous networks.

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 α, e.g., 56% for α = 4. All these analytic results are further validated by the numerical simulations.

Research into cutting-edge systems that can satisfy the rising needs for greater data rate and increased reliability is becoming more and more necessary as wireless communication technologies continue to evolve. To enhance the spectral and energy efficiencies, this study examine the performance of massive multiple input multiple output (mMIMO) communication systems using wavelet-order orthogonal frequency division multiplexing (W-OFDM). Also, a communication system was created based on W-OFDM Massive MIMO using MATLAB to model its operation. The simulated system's various stages of operation was examined through detailed analysis and its performance was compare with prior studies and practical networks on OFDM. Key performance metrics, specifically the data throughput, was evaluated to assess the effectiveness and viability of the system. The simulation results indicates that W-OFDM can achieve up to 35% reduction in peak-to-average-power-ratio (PAPR) compared to the traditional OFDM, with a 20% improvement in BER performance under Rayleigh fading conditions. Also, the spectral efficiency of W-OFDM mMIMO outperforms convectional OFDM by 15%, making it a viable technology for future communication networks requiring high data rates and reliability. This implies that, the analytical evaluation confirms that W-OFDM mMIMO provides substantial benefits for improving energy and spectral efficiencies in wireless communication systems, addressing the challenges of increased user demands for high spectrum. This study contributes to the understanding of MIMO systems' performance optimization, highlighting the importance of antenna configuration and cell distance. Comprehensive analysis of spectral efficiency and energy efficiency trade-offs in MIMO systems and identification of optimal antenna configuration for maximum energy efficiency, addressing some of the challenges of future wireless communication systems.

The growth of energy consumption driven by a rise in traffic rate demand and services, requires cellular operators to extend their infrastructure to meet these demands. To address this issue, deployment of low power base stations (BSs) in traditional macrocells have recently being considered to offer high data rates and simultaneously reduce the load of the macrocellular networks. However, the massive and unplanned deployment of small cells and their uncoordinated operations raise important questions about the energy efficiency in the heterogeneous cellular networks. In this paper, the impact of deploying a number of pico BSs on the system performance of macrocellular network is investigated. We analyze the energy efficiency of the downlink macro-picocells heterogeneous network, measured by the traffic capacity divided by the power consumption of the BSs. An adaptive power control based on the iterative-waterfilling scheme has been implemented to control the power among the macro and the pico BSs. The numerical results show that the total macrocellular capacity improves as the number of pico stations increases, but the energy efficiency is improved only for a reasonable number of pico base stations. Moreover, the iterative-waterfilling power allocation scheme improves the energy efficiency even with introducing more pico base stations as compared with other power allocation schemes. This work provides essential understanding for successful deployment of power efficient heterogeneous networks.

In future heterogeneous cellular networks (HCNs), the device-to-device (D2D) communication is considered as an efficient technique emerging mobile social network (MSN) services. Due to spectrum reuse among devices, the D2D however also brings in more interference, which will cause degradation in spectral efficiency (SE) when the density or centralization of devices is relatively high. With the help of control and data planes separation architecture (SARC) in the HCN, a smaller granularity of cooperation at device level is expected to be available for interference mitigation. Therefore, this letter introduces the coordinated multipoint transmission (CoMP) into D2D- enabled MSN to enhance SE performance. A CoMP scheme based on the average received signal power is designed for the D2D-enabled MSN (namely MSN-D2D- CoMP), on which basis the SE performance is analyzed using stochastic geometry for a hierarchical HCN with underlaying D2D devices. It is shown that MSN- D2D-CoMP effectively helps mitigating interference and outperforms the conventional paired D2D in SE (38.4% on average according to simulation results). And the gain of MSN-D2D-CoMP in SE increases with closer social relations for devices.

Recently, massive multiple input multiple output (MIMO) is considered as a promising technology to significantly improve the spectral and energy efficiency of fifth generation (5G) networks. Massive MIMO increases the energy efficiency (EE) by three orders of magnitude as compared to single antenna systems. In this paper, we review and analyze energy efficient resource allocation techniques for massive MIMO system. To this end, the energy efficiency of massive massive MIMO with linear processing is formulated. Analytical formulation is provided for the spectral efficiency (SE) and total system power consumption model. The tradeoff on the spectral and energy efficiency is analyzed. The impacts of propagation and system parameters on the SE-EE tradeoff are investigated. Then, large scale fading based analytical approximation for the energy efficiency is formulated. Finally, numerical simulation is done to validate the theoretical analysis.

In fifth-generation (5G) networks, the deployment of heterogeneous networks (HetNets) with macrocells layered over tiny cells is considered to be a practical solution to handle the growing demand for mobile traffic. The deployment of a significant count of small cell base stations (BSs) results in a notable rise in energy consumption. In this manuscript, Energy-Efficient (EE) 5G Heterogeneous Cloud Radio Access Networks (RRH to BBU), using Hybrid online green algorithm-based sleep scheduling and cost-efficient deadline-aware Scheduling Algorithm (OGASCDASA), are proposed. Here, the energy efficiency optimization issue is in the downlink of two-tier Heterogeneous Cloud Radio Access Networks (H-CRAN) by lowering micro and pico cells. Hybrid OGASCDASA is proposed for reducing remote radio side energy use when maintaining coverage and Quality of service (QoS) of H-CRAN. At the cloud side Baseband Units (BBU), hybrid Simulated Annealing with the Gaussian Mutation and Distortion Equalization algorithm with Battle Royale optimization is proposed to reduce the energy consumption of BBU by decreasing the count of BBU servers. The proposed EE-HCRAN-Hybrid OGASCDASA-SAGMDEBROA method attains 20.48%, 27.34%, and 32.24% higher throughput and 28.30%, 17.30%, and 32.94% lower delay compared to the existing models, such as heterogeneous computational resource allocation for NOMA (HCRA-NOMA-GMECS), energy-efficient hierarchical resource sharing in uplink-downlink decoupled NOMA heterogeneous networks (EE-HRA-NOMA-HetNet), energy-aware hierarchical resource management with backhaul traffic optimization in heterogeneous cellular networks (EA-HRM-BTO-HCN), respectively.

In this paper, we investigate the energy efficiency and spectral efficiency of heterogeneous networks, where macro-cell and microcell base stations are deployed according to two separate stochastic geometry based processes. Here, micro base stations are placed over the regions for which the received signal strength is below a certain limit. By employing the deployment model we propose, we investigate the effects of certain parameters like macro and micro base station densities, and user density on energy efficiency of heterogeneous networks. The results show that deploying micro base stations considerably improves both energy efficiency and spectral efficiency in a dense user scenario.

Energy efficiency is a basic need of the fifth-generation (5G) wireless networks, because the energy sources and capability of the battery are very narrow against the huge demand. Massive MIMO is a great invention of 5G cellular network with a large number of antennas. In this research, the prime aim is to maximize the energy efficiency and spectral efficiency simultaneously of massive MIMO system. Spectral and energy efficiency are formulated with fixed power, number of users, number of antennas with the impact of multiple users and without the impact of multiple users, the ratio of number of antennas and number of users. Trade-off also has been analyzed among the co-located, distributed and hybrid massive MIMO with the Nakagami-m fading channel, which can subtract the co-channel interference in a system and compared with each other. From the simulation results, it is seen that the energy efficiency of distributed massive MIMO is higher than the other two with the variation of fixed power, number of user and the ratio of number of antenna and number of user with respect to spectral efficiency. The energy efficiency of co-located massive MIMO is higher than the other two with the variation of number of antenna.

In this paper, we establish a general heterogeneous cellular network (HCN) model based on stochastic geometry and employ the accurate signal-to-interference-ratio (SIR) approximation of the ASAPPP (approximate SIR analysis based on the Poisson point process) technique to investigate spectrum allocation problems for general HCNs. Firstly, a spectrum partitioning problem where each tier uses a dedicated band is formulated to maximize the area spectral efficiency. The solution is obtained by approximating the problem with the ASAPPP method, deriving the optimal SIR thresholds, and solving a simple linear program to give the optimal spectrum allocation. Without a spectral efficiency constraint for each tier, the area spectral efficiency is maximized if the entire bandwidth is allocated to a single tier. Secondly it is shown that the proposed algorithm can also be used to solve the spectrum sharing optimization problem, where bands can be shared between tiers.

Heterogeneous cellular networks (HetNets) consist of different tiers of base stations (BSs) to meet the ever-increasing mobile traffic demand. Due to the random deployment of BSs, Poisson point process (PPP) is often used to model the BS distribution. However, low power small cells are usually clustered around the popular areas, and PPP can not reflect such a feature. To this end, we in this paper consider base station (BS) cooperation and analyze user rate and energy efficiency of HetNets based on a Poisson cluster process (PCP). A calculable formula for the average data rate (or spectral efficiency) and its approximated closed form are derived. Based on this closed form, a power minimization solution with certain spectral efficiency constraint is proposed, and the optimal cooperation radii are derived. Furthermore, we analyze spectral efficiency under a limited number of cooperative BSs in a two-tier network. Finally, we propose a range expansion (RE) scheme and examine the impact of this scheme. The theoretical analyses are verified by simulation results.

In fifth-generation cellular networks (5G), a large multiple-input multiple-output (MIMO) technique is critical for optimizing the trade-off between energy efficiency (EE) and spectral efficiency (SE). The challenges for the next generation depend on increasing the high data traffic in the wireless communication system for both EE and SE. The trade-off between EE and SE in downlink massive MIMO systems has been investigated in this paper using the first derivative of transmit antennas and transmit power. The EE-SE trade-off has been investigated using a multi-objective optimization problem to reduce transmit power. The EE and SE based on constraint maximum transmits power allocation and a number of antennas by computing the first derivative of transmit power to maximize the trade-off EE - SE has been improved. The optimal trade-off between EE and SE can be obtained based on the first derivative by selecting the optimal antennas with a low cost of transmit power showing good simulation results. Therefore, based on an optimal optimization problem is flexible to make trade-offs between EE-SE for distinct preferences.

Multi-hop heterogeneous cellular networks (MHCNs) consist of conventional macro cellular networks overlaid with an irregular deployment of low-power base stations (BSs), where the communication between BSs and mobile users can be established through a single hop or multiple hops. By modeling different kinds of randomly located BSs as K tiers of independent homogeneous Poisson Point Processes, we first explore the capacity of downlink MHCNs and derive the expression of capacity under Rayleigh fading channels. Particularly, the capacity gain achieved by cell splitting and multi-hop relaying is quantified for the first time. We then study the effects of BS density, transmit power, and signal-to-interference-plus-noise-ratio (SINR) threshold on the capacity of MHCNs. More importantly, we obtain the spectral efficiency enhancement condition under which the increase of BS density and transmit power improve the spectral efficiency, thereby enhancing the capacity. One interesting observation is that at a given SINR threshold, the capacity increases with BS density when all the tiers have the same SINR threshold. Moreover, the capacity of some special networks (i.e., heterogeneous cellular networks, multi-hop cellular networks, and conventional cellular networks) are derived directly by specializing some system parameters in our results. Finally, numerical studies and simulations are conducted to validate our analysis.

Underlay in-band device-to-device (D2D) multicast communication, where the same content is disseminated via direct links in a group, has the potential to improve the spectral and energy efficiencies of cellular networks. However, most of the existing approaches for this problem only address either spectral efficiency (SE) or energy efficiency (EE). We study the tradeoff between SE and EE in a single cell D2D integrated cellular network, where multiple D2D multicast groups (MGs) may share the uplink channel with multiple cellular users. We explore SE-EE tradeoff for this problem by formulating the EE maximization problem with constraint on SE and maximum available transmission power. A power allocation algorithm is proposed to solve this problem and its efficacy is demonstrated via extensive numerical simulations. The tradeoff between SE and EE as a function of density of D2D MGs, and maximum transmission power of an MG is characterized.