The Next Generation Network (NGN) is a telecommunications system that converges all services and information into packets for transfer, accommodating technical advancements high-speed and diversified services through its multilayer architecture. The NGN enables users to consistently and efficiently obtain services, and 5G cellular communication is a viable technology to meet the demand for high data rates in the future, particularly with its mmwave capacity. However, one of the major problems that the new generation faces is non-line-of-sight status, which results from higher frequencies' extreme vulnerability to interference from obstructions and misalignment. This special property makes it more difficult for the widely used Transmission Control Protocol (TCP) to achieve good throughput and low latency across an equitable network. TCP must modify the congestion window size in accordance with the state of the network, but it is unable to effectively adapt to its congestion window, resulting in degradation of the protocol's throughput. This research presents an in-depth analysis of trustworthy communications in 5G networks, examining how TCP affects 5G mmWave networks, the mechanisms and parameters of TCP that portrays the behavior of 5G networks, and a study of the existing problems, and ideas to be fixed. It also suggests a viable study of different methods to enhance reliable communications in 5G networks.
The Next Generation Network (NGN) is an evolving telecommunications system that aims to provide converged services, including voice, data, and multimedia, through the use of packet-switched technology. This architecture enables the network to accommodate technical advancements and highspeed, diversified services, providing users with consistent and extensive access to various services. To meet the growing demand for high-speed, reliable, and efficient network services, 5G cellular communication has emerged as a promising technology. 5G networks offer high capacity, particularly with mm-wave, making it possible to handle emerging use cases, such as augmented reality and vehicle - to - vehicle communication. However, these networks face several challenges, such as non-line-of-sight status, resulting from the vulnerability of higher frequencies to interference from obstructions and misalignment. One of the critical protocols utilized in ensuring reliable communication in 5G networks is the Transmission Control Protocol (TCP). However, TCP faces challenges in adapting to the unique characteristics of 5G mm-wave networks. TCP's inability to effectively adjust its congestion window can result in degradation of the protocol's throughput, making it difficult to achieve good throughput and low latency across an equitable network. This research presents an in-depth analysis of trustworthy communications in 5G networks, with a particular focus on how TCP affects 5G mm-wave networks. It examines the mechanisms and parameters of TCP that portray the behavior of 5G networks and discusses the existing problems. It also suggests different methods to enhance reliable communications in 5G networks. By analyzing the TCP protocol's performance in 5G networks, insights are provided to optimize TCP to accommodate the unique characteristics of 5G mmwave networks, improving the overall reliability and efficiency of communication in NGN.
The term "Next Generation Network" (NGN) refers to the development and transition of fixed and mobile network infrastructures from separate proprietary networks to converged IP-based networks. This transition aims to create an environment where different networks, including wired and wireless access networks, the Public Switched Telephone Network (PSTN), satellites, broadcasting, and others, can interact with each other. NGN presents numerous opportunities for the introduction of new and existing technologies in the field of information transmission and processing, as well as in the network services sector.
Under NGN, it is also possible to decouple service provision from the network and offer an open interface. Based on service building blocks, it supports a wide variety of services, applications, and methods. The network features end-to-end QoS and transparency for broadband services. Packet-based transferring is how NGN operates. It offers the benefit of all-around mobility (Pi & Khan, 2011). The control functions of bearer capabilities, calls/sessions, and applications/services are automatically separated. It offers consumers an unrestricted access to a variety of service providers. Additionally, this network has the capability of interacting with legacy networks through open interfaces. In order to facilitate routing in IP networks, it also offers a range of identification systems that can be translated into IP addresses. In NGN, functions that are connected to services are independent of the underlying transport technologies.
NGN utilizes the flexibility, efficiency, and innovation of IP technology, as well as the Quality of Service (QoS), security, reliability, and customer-friendly aspects of the PSTN. In addition, it offers several benefits, such as notifying the seller of End of Life or End of Service, increasing revenue streams for new IP and Ethernet services, satisfying client demand for high-bandwidth Ethernet and IP solutions, and reducing knowledge of legacy systems. Users can select numerous service providers to take full advantage of the best deals available, but they can only receive one bill.
Despite its benefits and applications, the NGN has some significant flaws which include migration challenges. Not all existing services can be replaced with options, and not all of the current infrastructure can be shut down. Critical services are subject to regulatory constraints.
The latest cellular technology, known as Fifth-Generation (5G) wireless, is designed to significantly speed up and improve the responsiveness of wireless networks. This speed is faster than those of landline networks and provide a latency of 5 milliseconds or less, making it suitable for applications that need real-time input. With 5G, wireless internet connections may transport data at multi-gigabit speeds, with peak rates that could reach as high as 20 Gigabits Per Second (GBPS), according to some estimates. Due to its higher accessible bandwidth and improved antenna technology, 5G will make it possible for wireless networks to transfer much more data.
The five major categories of 5G network are; Enhanced Mobile Broadband (eMBB), Massive Machine Type Communications (mMTC), Ultra-Reliable Low Latency Communications (URLLC), Enhancement of Vehicle-to- Everything (eV2X), and Network Operation (NEO). Figure 1 depicts the five primary use cases of the 5G network.
User connectivity to multimedia, data, and services is provided through eMBB. Hotspots fall under this category because of its larger capacity, high user density, and limited mobility, Many devices that individually send a small amount of non-delay-sensitive data and have needs like low cost and extended battery life employ mMTC.
URLLC is utilized for applications like heavy automation, remote monitoring, and smart grids that have strict requirements for characteristics like speed, latency, and availability. Support for self-driving and connected cars is provided by Enhanced V2X (eV2X). Critical communications must support larger data rates and a wide range of mobile devices (Al-Ogaili & Shubair, 2016). NEO includes the idea of “Network Slicing,” which involves using Network Functions Virtualization (NFV) to build numerous Virtual Networks (VNs) on top of the same physical infrastructure to handle the vast range of use cases anticipated for 5G.
5G connectivity employs a far wider spectrum of frequencies than 4G networks do. Hence, it is divided into two categories, namely mmWave and higher-frequency radio bands between 24 GHz and 40 Ghz referred to as mmWave. Although mmWave 5G networks are extremely fast, their range is also extremely limited. Since it is necessary to be a block away from a 5G tower to use mmWave technology, suburban and rural regions are inaccessible. Doors, windows, trees, and buildings further obstruct and obscure mmWave energy, further reducing its usable range. Because it requires so many towers for coverage, it is extremely expensive for carriers to deploy. Due to its short range, mmWave technology is still in its infancy and is currently being developed. Accessing mmWave spectrum has only recently been feasible, thanks to technological developments like massive MIMO, flexible beam forming, and the downsizing of sophisticated antenna processing tasks. Due to its limitations, mmWave is best used in crowded urban areas or for narrowly focused events like concerts or airports. As a result of its limited range, mmWave technology is not useful in rural and suburban locations.
The first band outlined by the 3 General Purpose Processor (3GPP) is known as the sub-6 GHz band and extends from 410 MHz to 7125 MHz. The sub-6 GHz 5G networks have a maximum bandwidth of 6 GHz and a frequency range of 1GHz to 6 GHz. The most widely used 5G frequency in the entire world is 3.5 GHz. Due to its lower frequency range and consequent speed limitations, the sub-6 GHz band is better suited for practical applications because of its longer range. The range is always crucial because speed is useless if there is no network. The sub-6 GHz band offers better coverage and employs 4G frequencies. It has a few technical flaws, such as RF characteristics, and depending on the frequency selected, it has the advantage of using RF resources that have already been approved for 3G Wideband W-Code Division Multiple Access (W-CDMA) and 4G Long-Term Evolution/Long-Term Evolution Advanced(LTE/LTE-A). Since most frequencies are already in use, securing a wide and organized frequency range is difficult.
The performance of the Transmission Control Protocol (TCP) is adequately identified by the utilized Congestion Control (CC) algorithm. To support various network contexts, TCP CC algorithms have been developed over the last three decades, along with a huge variety of CC algorithm modifications. Managing complexity in the fifth-generation mobile network is a key issue in implementing the TCP CC mechanism since the network will maintain specific conditions with a high density of user devices and enormous traffic flows (Afanasyev et al., 2010). The complete implementation of TCP CC algorithms in fifthgeneration wave communication will be compromised due to different variations in susceptibility as well as channel quality blockage caused by atmospheric absorptions and high penetration losses. All of these issues will be present in environments like the Internet of Things and sensor network applications (Poorzare & Augé, 2020).
5G cellular networks suffer from a few negative outcomes, mainly at higher frequencies, due to the sporadic nature of different channels as the frequency increases. Non- Line of Sight State (NLOS) is a major issue that the current and upcoming generations will face. This drawback usually occurs due to the extreme higher frequencies' obstruction sensitivity to both misalignment and obstacles. This particular feature has the ability to improve the overall performance of the effective transport layer, which is the most widely implemented TCP, by achieving low latency and high throughput in a specific fair network. To correctly change the congestion window size, the protocol must take into account the state of the 5G network (Poorzare & Augé, 2020).
Furthermore, TCP is unable to adequately adjust its congestion window, which leads to a drastic deterioration of the protocol. The non-line-of-sight state is considered one of the pivotal challenges encountered by the new generation in this competitive market (Al-Saadi et al. 2019). These are major drawbacks due to the core's intense susceptibility to blockage caused by misalignment and obstacles, which can reduce the transport layer's overall performance. TCP is responsible for achieving high throughput and low latency throughout in the network. As a paradigm, the protocol requires further adjustment of the congestion window size depending on the recent situation in the network. However, TCP is unable to adjust the congestion window adequately, leading to throughput degradation under the protocol (Jin et al. 2005). For reliable and end-to-end 5G network communication, implementing the Transmission Control Protocol (TCP), where its enhancement in wireless components is necessary (Xu et al., 2004).
Poorzare and Augé (2020) analyzed that, channels become sporadic as frequency climbs. Also, 5G cellular networks have some drawbacks, particularly in the case of higher frequencies. This special property may make it more difficult for the trustworthy transport layer protocol, TCP, to operate across an equitable network. Because of this, the protocol must modify the size of the window based on the state of the network. TCP is unable to effectively adapt its congestion window, which causes the protocol's throughput to degrade.
Polese et al. (2017) investigated whether the transport layer has a crucial aspect for identifying "end-to-end outcomes in a network. Though the next generation is going to provide a higher bandwidth, it will exclude an efficient transport layer that has the ability to use the present bandwidth of mmWave in 5G networks as well as deal with available complications like misalignment and blockage. This bandwidth will be completely wasted, and the maximum data rates will be very difficult to achieve.
Lorincz et al. (2021) explored that Adapting Maximum Segment Size (MSS) and Maximum Transmission Unit (MTU) and optimizing their overall values for the 5G network is very challenging. The conventional size of MSS has a couple of significant impacts on TCP's performance in the 5G network. The size of the congestion window initiates from the considerable value that may be 1–4 rather than by capturing all of the Acknowledgement (ACK). On the other hand, TCP increases congestion window sizes by one. Although this particular process focuses on probing the link as well as being effective for the old network instead of 5G, It seems unsuitable for the upcoming network generation.
Gwak and Kim (2017) depicted that the effect of a Retransmission Time Out (RTO) can lead to long disconnections. When a failure occurs, the chances of triggering RTO are high, which can negatively impact the overall performance of the 5G network. On the other hand, the absence of congestion can cause degradation in triggering RTO. The utilization of TCP selective acknowledgements can enhance the number of packets by improving the re-transmission mechanism.
Tang et al. (2022) examined the Wireless Transmission Control Protocol (WTCP), which is a modification of TCP based on a proxy that maintains the end-to-end semantics of TCP and is used to enhance its performance. WTCP handles various issues with wireless channels, including high bit error rates that occur in bursts over the wireless medium. WTCP detects problems such as corrupted or lost segments due to high BER or multipath fading, using duplicate acknowledgements and timeouts. WTCP solves these challenges by recommitting a lost segment only once until it receives a proper acknowledgement from the.
Kharat and Kulkarni (2019) say that TCP is one of the most widely used protocols for appropriate end-to-end communication in the transport layer of the TCP/IP protocol stack. In addition to providing end-to-end reliability, the Transmission Control Protocol also includes a mechanism for congestion control to manage unacknowledged packets, utilize bandwidth efficiently, and redeliver lost packets. The sending rate is controlled by a congestion window that is used to modify the method.
Kanagarathinam et al. (2020) analyze that TCP refers to a reliable, connection-based protocol that ensures ordered delivery of byte streams in full-duplex interprocess communication by eliminating Round-Trip Time (RTT) through the exchange of data before the standard process is finished. TCP technology is currently one of the primary standards for reliable interaction over the internet. It is responsible for terminating and establishing proper connections, flow control, reliable communication among hosts, and CC over various unreliable networks.
Lorincz et al. (2021) explained how various surfaces of a protocol stack, especially the TCP, encounters new challenges when positioned in the 5G network together with high-frequency channels such as mmWave channels. The primary issue with the Transmission Control Protocol is due to the irregular nature of mmWave channels, which are too delicate and susceptible to degradation and blockage.
TCP is a key protocol used in modern internet communication at the transport layer. Congestion control is a vital method in TCP Congestion Control (CC). The primary goal of the CC mechanism is to explore the network by increasing the window size. Misalignment issues and blockages can significantly impact the TCP CC mechanism, resulting in lower transmission ability. They may occur due to lower channel quality or congestion caused by a misaligned beam. These issues must be addressed to achieve the desired performance and meet the 5G criteria. For diverse contexts and usage scenarios, TCP CC algorithms have been implemented with the goal of creating trade-offs and maximizing various metrics. There are two types of congestion control algorithms: single-flow CC algorithms and multi-flow CC algorithms. Single-flow congestion control algorithms are further classified into three types: loss-based, delaybased, and hybrid. Figure 2 shows the types of TCP congestion control algorithms.
Both the Reno TCP and Tahoe TCP are algorithms that depend on loss to detect signs of lost segments due to congestion in RTO and duplicate ACKs. These CC algorithms differ mainly in how they handle the faster retransmission of segments after receiving three duplicate ACKs. The Tahoe TCP enters the slow start stage after the rapid retransmit phase, while the Reno TCP enters the quick recovery stage to skip the slow start phase. The TCP New Reno has a minor update aimed at addressing performance issues. It provides a quick turnaround modification to allow more retransmissions. To overcome the limitations of algorithms that use cumulative ACKs, TCP Selective Acknowledgments (SACKs) were developed. The TCP westwood protocol offers a faster recovery mechanism that adjusts the transmission rate based on an estimated amount of available bandwidth. When the Congestion Window (cwnd) size is large, HighSpeed TCP is used to enable quicker recovery time and cwnd growth (Tan et al., 2006). The Scalable TCP algorithm increases the cwnd size after receiving an ACK in accordance with specified constants. The common CC is used once the packet loss has been reduced by a smaller amount. Binary Increase Congestion (BIC) control uses additive increase and binary search increase strategies to calculate the cwnd size. CUBIC uses a cubic function to control the cwnd, which has a stable state (Sing & Soh, 2005).
TCP Vegas, a tweak of TCP Reno, can foresee network congestion before segments are actually lost by using a segment dissemination timeline and estimation, making it quite effective. Vegas+, a newer version of TCP Vegas, was designed to address difficulties when competing with TCP Reno (Tan et al., 2006). In high-latency environments, the server-side of TCP Vegas was modified to address outcome difficulties, resulting in New Vegas (Mo et al., 1999). Vegas-A is implemented as a modified congestion avoidance method that addresses issues with aggression and fairness. For networks with high-latency, FAST is designed to adjust the cwnd in accordance with feedback data on average RTT and queuing time, effectively utilizing network bandwidth by using scaling factors.
Compound combines two components during the stage of avoiding congestion, and its foundation is based on gradual early level loss. YeAH dynamically switches between a slow mode and a fast mode to avoid congestion. BBRv1 developed an external mode of the network to avoid congestion, while BBRv2 enhances CC performance and reduces packet loss.
An enhancement to TCP known as Multi-Path TCP (MP-TCP) manages multiple pathways for a single data stream concurrently. MP-TCP can create several flows that use different paths based on one connection using a variety of network interfaces.
CC mechanisms used with MP-TCP are classified as uncoupled or coupled. The uncoupled CC mechanism handles each subflow independently, allowing independent TCP CC implementations for each subflow. On the other hand, the coupled CC mechanism regulates cwnd in a linked manner by considering the characteristics of each subflow. When compared to traditional single-path TCP, LIA can behave aggressively and send a lot of data through busy routes. The OLIA algorithm is suggested as a solution to these problems. Balanced Linked Adaptation (BALIA) performance is built on careful balancing act between TCP friendliness, cwnd oscillations, and responsiveness. Dynamic-Linked Adaptation (D-LIA) mainly focuses on the increase in cwnd by ignoring the reducing scheme of D-LIA. D-LIA depends on the time between each time frame of lost packets rather than halving it. This method allows the cwnd to grow to its ideal size much faster than the standard TCP AIMD mechanism, which reduces network latency.
Based on the analysis, different mmWave 5G Network Functions that encounter challenges when using TCP CC algorithms were identified. like to propose some possible solutions. When using high frequencies in the mmWave range with TCP, blockages can occur, which may result in more frequent TCP Recovery Time Objective (RTO) triggering, longer Round-Trip Time (RTT)s, and a higher likelihood of packet losses. These detrimental consequences may be more pronounced for static UEs than for moving User Equipment (UE)s, as moving UEs have a higher likelihood of quickly connecting to Next Generation Node B (gNB) or a UE. To address this issue, one potential solution is to extend the network's Loss of Signal (LOS) zones. Another solution is to install wireless relays to maintain LOS communication and achieve appropriate allocation and densification of diverse network elements, which are made up of BSs with varying capacities and sizes.
Long TCP queues are a result of the "use of buffering for radio link control" with TCP. This results in buffer bloat issues and increased latencies due to the prolonged waiting of packets. Implementing smaller buffers reduce latency but may lead to a higher number of missed packets in the event of high channel fluctuations, which significantly affect loss-based TCPs. Novel strategies that balance performance and latency need to be developed to address this issue. Modified Active Queue Management (AQM) methods such as Controlled Delay (CoDel) and Flow Queue CoDel may not be reliable for TCP connections from the Base Station (BS) to the User Equipment (UE) if beam forming is used for signal transmission. Non-Line-of-Sight (NLOS) communication suffers from high end-to-end throughput degradation due to low Signal-to-Noise Ratio (SNR) levels at the UE's location. Longer interruptions have a more significant impact on TCP performance due to the increased likelihood of triggering Recovery Time Objectives (RTOs) which initialize the congestion window and reduce the transmit rate. To address this issue, superior handover algorithms that ensure optimal throughput levels and TCP Congestion Control (CC) can be developed. Additionally, using hardware with multiple Network Interface Cards (NICs) and employing multipath TCP protocols can help improve TCP performance.
TCP may become confused by frequent horizontal and vertical handovers when expanding the size of its congestion window. This limits TCP’s ability to guarantee minimal packet drops. Developing superior handover algorithms to ensure optimal throughput levels and TCP CC could be a potential solution. Hardware with multiple NICs and CC using multipath TCP protocols can also be used.
TCP network slicing in conjunction with edge computing does not produce optimal outcomes. Using distinct TCP methods in each slice to guarantee ideal CC can be a potential solution. Content Delivery Network (CDN)-based options for server allocation near user equipment, can also be used. Creating new TCP CC algorithms tailored to the requirements of a specific network slice is another option.
Constantly transmitted signals using TCP can create duplicate traffic and network disruption. This can impact TCP performance in terms of CC and the fair allocation of data flows among users. Implementing 5G networks with an ultra-lean design based on intelligent signal exchange may be the solution. The ultra-lean architecture can improve TCP functionality by reducing traffic and congestion occurrences.
Transmission Control Protocol (TCP) is widely used in Next Generation Networks (NGN) to ensure reliable communication. However, TCP faces challenges in adapting to the unique characteristics of 5G mm-wave networks, such as the non-line-of-sight status resulting from the vulnerability of higher frequencies to interference from obstructions and misalignment. TCP's inability to effectively adjust its congestion window can result in degradation of the protocol's throughput, making it difficult to achieve good throughput and low latency across an equitable network. The analysis reveals that modifying the congestion control algorithm of TCP can significantly enhance reliable communication in 5G mmwave networks. TCP can be optimized to accommodate the unique characteristics of 5G mm-wave networks, improving the overall reliability and efficiency of communication in NGN. It provides insights into optimizing TCP for 5G mm-wave networks, which can lead to improved communication quality and increased user satisfaction. As NGN continues to evolve, it is essential to develop and implement new communication protocols that can effectively adapt to the unique challenges of 5G mm-wave networks, enabling NGN to provide reliable, high-speed, and diversified services to users. The review of NGN makes it evident that it may assist operators in meeting their needs, but operators must invest properly in it because some older technologies cannot keep up with it. By adopting the Wireless Transmission Control Protocol (WTCP) for 5G networks, better results can be achieved by thoroughly examining 5G networks.