Green Communication in Modern Wireless Networks : A Comprehensive Review

Green Communication in Modern Wireless Networks : A Comprehensive Review

Author 1 Nidhi Author 2 Dr. Shamsher Singh

Institute- UIET, Maharshi Dayanand University, Rohtak City-Rohtak

Country – India

Abstract

The rapid evolution of wireless communication technologies, particularly the deployment of fifth-generation (5G) networks and the conceptualization of next-generation networks (6G and beyond), has significantly transformed global connectivity. However, this progress comes with a substantial increase in energy consumption and carbon emissions, posing environmental and economic challenges. Green communication, which focuses on energy-efficient and sustainable network design, has emerged as a critical research area to mitigate these impacts. This review paper provides a comprehensive analysis of green communication strategies in 5G and next-generation networks, covering energy-efficient technologies, network architectures, resource management techniques, and emerging trends. It discusses key enabling technologies such as small cell networks, massive MIMO, device-to-device (D2D) communication, renewable energy integration, and artificial intelligence (AI)-driven optimization. Additionally, the paper addresses security challenges, standardization efforts, and future research directions, emphasizing the balance between energy efficiency, performance, and quality of service (QoS). By synthesizing recent advancements and identifying open issues, this paper aims to guide researchers and industry professionals toward sustainable wireless communication systems.

1. INTRODUCTION

   The advent of 5G networks marks a pivotal shift in wireless communication, offering unprecedented data rates, ultra- low latency, and massive device connectivity to support applications like the Internet of Things (IoT), autonomous vehicles, and smart cities. As of 2025, 5G deployments are expanding globally, with over 2.8 billion 5G connections projected by the end of the year [1]. However, the energy demands of 5G networks, driven by dense base station deployments and advanced technologies like massive multiple-input multiple-output (MIMO), have raised concerns about their environmental impact. The information and communication technology (ICT) sector accounts for approximately 10% of global energy consumption, with wireless networks contributing significantly to this figure [2]. The carbon footprint of mobile networks is expected to triple from 2007 to 2020 levels by 2030 if current trends persist [3].

   Green communication aims to address these challenges by developing energy-efficient technologies and sustainable network architectures. The concept encompasses strategies to reduce power consumption, optimize resource allocation, and integrate renewable energy sources while maintaining or enhancing network performance. In 5G, green communication is critical not only for environmental sustainability but also for economic viability, as energy costs constitute a significant portion of operational expenses for network operators [4]. Looking ahead, next-generation networks (6G) are expected to further prioritize sustainability, leveraging AI-native architectures and advanced spectrum management to achieve carbon-neutral operations [5].

   This review paper provides an in-depth analysis of green communication in 5G and next-generation networks, synthesizing recent advancements and identifying future research directions. The paper is structured as follows: Section 2 discusses the energy challenges in 5G networks, Section 3 reviews key green communication technologies, Section 4 explores resource management and optimization techniques, Section 5 addresses renewable energy integration, Section 6 examines security challenges in green networks, Section 7 discusses standardization and ongoing projects, and Section 8 outlines future trends and open issues. Section 9 concludes the paper.

2. ENERGY CHALLENGES IN 5G NETWORKS

   The transition from 4G to 5G has introduced several energy-intensive features, including ultra-dense networks (UDNs), millimeter-wave (mmWave) communications, and massive MIMO. These technologies enable high data rates and low latency but significantly increase power consumption. The following subsections outline the primary energy challenges in 5G networks.

   1. Ultra-Dense Networks (UDNs)

      UDNs involve the deployment of numerous small cells to enhance coverage and capacity in high-traffic areas. While small cells consume less power per unit than macro base stations, their high density leads to substantial aggregate energy consumption. Studies estimate that small cell networks can account for up to 50% of a 5G networks total power usage [6]. Additionally, the backhaul infrastructure required to connect small cells to the core network further exacerbates energy demands [7].

   2. Massive MIMO

      Massive MIMO, which uses hundreds of antennas to serve multiple users simultaneously, is a cornerstone of 5Gs spectral efficiency. However, the increased number of antennas and associated radio frequency (RF) chains significantly raises power consumption. The power amplifiers (PAs) in massive MIMO systems are particularly energy-intensive, contributing to a high peak-to-average power ratio (PAPR) [8]. Optimizing PA efficiency is a critical challenge for green 5G networks.

   3. Millimeter-Wave (mmWave) Communications

      mmWave frequencies (above 24 GHz) offer wide bandwidths for high-speed data transmission but suffer from high path loss and signal attenuation. To compensate, mmWave systems require dense deployments of base stations and high-power transmission, leading to increased energy consumption [9]. The short-range nature of mmWave signals also necessitates frequent handovers, further straining network resources.

   4. Internet of Things (IoT) and Massive Connectivity

      5G supports massive machine-type communications (mMTC), enabling connectivity for billions of IoT devices. While individual IoT devices consume minimal power, their sheer volume and continuous operation contribute to significant network-wide energy demands. Battery life optimization for IoT devices is a key concern, as frequent recharging or replacement is impractical in large-scale deployments [10].

   5. Backhaul and Core Network

      The backhaul infrastructure, which connects base stations to the core network, is another major energy consumer. Traditional copper-based backhaul systems are being replaced by fiber-optic and microwave solutions, but these still require substantial power, especially in dense 5G deployments [11]. Additionally, the core networks reliance on cloud-based architectures and network function virtualization (NFV) increases computational energy demands [12].

3. KEY GREEN COMMUNICATION TECHNOLOGIES

   To address the energy challenges outlined above, several technologies have been developed to enhance the energy efficiency of 5G networks. This section reviews the most prominent green communication technologies, including small cell networks, massive MIMO optimization, D2D communication, spectrum sharing, and visible light communication (VLC).

   1. Small Cell Networks (SCNs)

      Small cell networks are a cornerstone of 5Gs energy-efficient design, as they reduce the transmission distance between base stations and user equipment (UE), lowering power requirements. Research indicates that SCNs can save p to 48% more power compared to traditional macrocell networks by dynamically activating or deactivating small cells based on traffic demand [13]. Techniques such as cell zooming, which adjusts the coverage area of small cells, and sleep mode activation further enhance energy efficiency [14]. However, the dense deployment of small cells necessitates sophisticated interference management and backhaul optimization to maximize energy savings.

   2. Massive MIMO Optimization

      Optimizing massive MIMO systems for energy efficiency involves reducing the power consumption of PAs and RF chains. Techniques such as hybrid beamforming, which combines analog and digital signal processing, can significantly lower energy demands while maintaining spectral efficiency [15]. Additionally, PAPR-aware resource allocation schemes, which minimize the peak power requirements of PAs, have been shown to improve energy efficiency by up to an order of magnitude in 5G deployments [16]. Machine learning-based precoding algorithms also offer promising solutions for energy-efficient massive MIMO systems [17].

   3. Device-to-Device (D2D) Communication

      D2D communication enables direct data exchange between UEs without routing through base stations, reducing network energy consumption. By offloading traffic from the core network, D2D can decrease the power requirements of base stations and extend the battery life of UEs [18]. Energy-efficient mode selection and power allocation schemes for D2D communication have been proposed, achieving significant improvements in system capacity and power efficiency [19]. However, efficient interference management is critical to ensure the coexistence of D2D and cellular links.

   4. Spectrum Sharing

      Spectrum sharing, including cognitive radio and licensed-assisted access (LAA), optimizes the use of available frequency bands, reducing the need for high-power transmissions. By dynamically allocating spectrum based on demand, spectrum sharing can enhance energy efficiency and alleviate the spectrum crisis in 5G networks [20]. A proposed spectrum-sharing model has demonstrated potential to extend UE battery life by optimizing resource allocation [21]. However, spectrum sharing introduces complexity in interference management and requires robust security mechanisms to prevent unauthorized access.

   5. Visible Light Communication (VLC)

      VLC uses light-emitting diodes (LEDs) to transmit data, offering an energy-efficient alternative to RF-based communication. VLC systems leverage existing lighting infrastructure, reducing the need for dedicated power sources. They are particularly suitable for indoor environments and smart city applications [22]. A VLC prototype using pulse position modulation (PPM) has shown promising results for short-range, low-power communications [23]. However, VLCs limited coverage and susceptibility to ambient light interference pose challenges for widespread adoption.

4. RESOURCE MANAGEMENT AND OPTIMIZATION TECHNIQUES

   Effective resource management is essential for achieving green communication in 5G networks. This section discusses advanced techniques for energy-efficient resource allocation, including AI-driven optimization, sleep mode strategies, and network slicing.

   1. AI-Driven Optimization

      Artificial intelligence, particularly machine learning (ML) and deep learning (DL), has emerged as a powerful tool for optimizing resource allocation in 5G networks. AI algorithms can predict traffic patterns, optimize power allocation, and manage interference in real time, leading to significant energy savings. For example, a recurrent neural network (RNN)-based precoding scheme for massive MIMO systems has achieved energy efficiency improvements of up to 90% compared to traditional methods [24]. Reinforcement learning (RL) has also been applied to dynamically adjust small cell activation, reducing power consumption while maintaining QoS [25]. The integration of AI into 6G networks is expected to further enhance energy efficiency through native AI architectures [26].

   2. Sleep Mode Strategies

      Sleep mode strategies involve deactivating underutilized base stations or small cells during low-traffic periods to reduce energy consumption. Advanced sleep mode protocols, such as those based on medium access control (MAC) layer optimization, can achieve energy savings of up to 50% in 5G networks [27]. However, these strategies must balance energy efficiency with network performance, as frequent state transitions can introduce latency and degrade QoS. Traffic-intensity-aware multicell cooperation, which adapts the network layout based on user demand, has been proposed to mitigate these issues [28].

   3. Network Slicing

      Network slicing enables the creation of virtual network instances tailored to specific applications, optimizing resource utilization and energy efficiency. By allocating resources dynamically based on service requirements, network slicing can reduce unnecessary power consumption. For example, a coverage-aware resource provisioning method for network slicing has been shown to improve energy efficiency in 5G networks [29]. Machine learning techniques, such as those based on deep reinforcement learning, further enhance the efficiency of resource orchestration in sliced networks [30]. However, the computational overhead of network slicing must be carefully managed to avoid offsetting energy savings.

5. RENEWABLE ENERGY INTEGRATION

   Integrating renewable energy sources, such as solar and wind, into 5G networks is a key strategy for achieving sustainability. This section explores the opportunities and challenges of renewable energy-powered 5G infrastructure.

   1. Opportunities

      Renewable energy can significantly reduce the carbon footprint of 5G networks by powering base stations and backhaul infrastructure. Solar-powered base stations, for instance, have been deployed in off-grid areas, reducing reliance on diesel generators and lowering operational costs [31]. Microgrid-based energy trading, enabled by software-defined networking (SDN) and AI, optimizes the use of renewable energy across multiple base stations, improving economic efficiency and utilization rates [32]. In 6G networks, renewable energy integration is expected to be a core component of sustainable network design, supported by advanced energy harvesting techniques [33].

   2. Challenges

      The intermittent nature of renewable energy sources poses challenges for maintaining service quality in 5G networks. Energy outages due to weather variability can disrupt network operations, necessitating hybrid power systems that combine renewable and grid energy [34]. Additionally, the high initial cost of renewable energy infrastructure and the need for efficient energy storage solutions remain barriers to widespread adoption [35]. Research into energy-efficient battery management and predictive energy allocation algorithms is ongoing to address these issues [36].

6. SECURITY CHALLENGES IN GREEN COMMUNICATION

   Green communication strategies, such as D2D communication and spectrum sharing, introduce security vulnerabilities that must be addressed to ensure reliable network operation. This section discusses key security challenges and proposed solutions.

   1. Small Cell Access Point (SCA) Vulnerabilities

      Small cell access points (SCAs) are susceptible to spoofing attacks, particularly during handovers between SCAs. An intruder can exploit the brief disconnection period to impersonate a legitimate user, compromising network security [37]. Secure power optimization techniques, such as relay-based authentication, have been proposed to mitigate these riss, but they can drain the relays battery, limiting their effectiveness [38].

   2. D2D Communication Security

      D2D communication, while energy-efficient, is vulnerable to eavesdropping and interference from malicious users. Multi-antenna beamforming with power control, which maximizes transmission power toward the intended receiver while minimizing it in other directions, has been shown to reduce interference and enhance security [39]. However, implementing these techniques in resource-constrained devices remains challenging.

   3. Network Slicing Security

      Network slicing introduces security risks related to resource isolation and cross-slice interference. Unauthorized access to a slice can compromise the entire networks integrity. AI-based security frameworks, which detect anomalies and enforce access control, are being developed to secure sliced 5G networks [40]. Standardization efforts, such as those by the 3rd Generation Partnership Project (3GPP), are also addressing security requirements for network slicing [41].

7. STANDARDIZATION AND ONGOING PROJECTS

   Standardization plays a crucial role in promoting green communication in 5G and next-generation networks. This section reviews key standardization efforts and ongoing research projects.

   1. Standardization Efforts

      The 3GPP has introduced several energy-efficient features in 5G New Radio (NR), including the Radio Resource Control (RRC) INACTIVE state, which reduces signaling overhead and energy consumption by storing UE context during idle periods [42]. The 5G PPP (5G Public-Private Partnership) has also published white papers on energy- efficient network architectures, emphasizing the role of network slicing and AI [43]. For 6G, the International Telecommunication Union (ITU) is developing sustainability-focused standards, targeting carbon-neutral networks by 2030 [44].

   2. Ongoing Projects

      Several research projects are advancing green communication technologies. The METIS-II project, funded by the European Union, has developed energy-efficient operational use cases for 5G, focusing on D2D and massive MIMO [45]. The 5G-GREEN project explores renewable energy integration and small cell optimization, achieving significant reductions in carbon emissions [46]. Additionally, Samsungs 6G Forum is investigating AI-native and sustainable communication technologies, including cross-division duplex (XDD) for improved energy efficiency [47].

8. FUTURE TRENDS AND OPEN ISSUES

   As 5G deployments mature and 6G research accelerates, several trends and challenges are shaping the future of green communication. This section discusses emerging trends and open research issues.

   1. Emerging Trends

      • AI-Native 6G Networks: 6G networks are expected to leverage AI for end-to-end optimization, enabling real-time energy management and predictive resource allocation. AI-native architectures will integrate energy efficiency as a core design principle [48].

      • Terahertz and cmWave Communications: Beyond mmWave, terahertz and centimeter-wave (cmWave) frequencies are being explored for 6G, offering ultra-high bandwidths but requiring innovative energy-efficient transmission techniques [49].

      • Energy Harvesting: RF energy harvesting and ambient energy harvesting techniques are gaining traction for powering IoT devices and small cells, reducing reliance on traditional power sources [50].

      • Sustainable Network Design: 6G networks aim to achieve carbon-neutral operation through holistic sustainability frameworks, including green manufacturing and lifecycle management [51].

   2. Open Issues

      • Trade-offs Between Energy Efficiency and Performance: Balancing energy efficiency with QoS, latency, and throughput remains a challenge, particularly in high-demand scenarios like autonomous driving [52].

      • Scalability of AI Solutions: While AI offers significant energy savings, the computational complexity of large- scale AI models can offset these benefits, necessitating lightweight algorithms [53].

      • Security in Energy-Efficient Networks: The integration of energy-saving techniques like D2D and network slicing introduces new security vulnerabilities that require robust solutions [54].

      • Cost of Renewable Energy Infrastructure: The high upfront costs of renewable energy systems and energy storage solutions hinder their adoption in 5G and 6G networks [55].

      • Standardization for 6G: Developing global standards for energy-efficient 6G networks is critical but challenging due to diverse regional requirements and technological complexities [56].

9. CONCLUSION

Green communication is a cornerstone of sustainable 5G and next-generation networks, addressing the pressing need to reduce energy consumption and carbon emissions in the ICT sector. This review has explored the energy challenges of 5G networks, key green communication technologies, resource management techniques, renewable energy integration, security challenges, standardization efforts, and future trends. Technologies such as small cell networks, massive MIMO optimization, D2D communication, and AI-driven resource allocation have demonstrated significant potential to enhance energy efficiency while maintaining network performance. However, challenges such as trade- offs between energy efficiency and QoS, security vulnerabilities, and the scalability of renewable energy solutions require further research. As 6G networks emerge, the focus on AI-native architectures, energy harvesting, and carbon- neutral design will drive the next wave of innovation in green communication. By addressing these challenges and leveraging emerging technologies, the wireless communication industry can achieve sustainable growth, benefiting both the environment and society.

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