Throughput Gain Research Articles

Virtual Local Area Network Performance Improvement Using Ad Hoc Routing Protocols in a Wireless Network

Wireless Communication has become one of the most popular types of communication networks because of the many services it provides; however, it has experienced several challenges in improving network performance. VLAN (Virtual Local Area Network) is a different approach which enables a network administrator to create a logical network from a physical network. By dividing a large network into smaller networks, VLAN technology improves network efficiency, management, and security. This study includes VLAN for wireless networks with mobile nodes integration. The network protection was improved by separating the connections and grouping them in a way that prevents any party from being able to contact unauthorized stations in another party using VLAN. VLAN demonstrated restricted access to private server data by managing traffic, improving security, and reducing levels of congestion. This paper investigates the virtual local area network in a wireless network with three ad hoc routing protocols in a number of different scenarios, using the Riverbed Modeler simulation, which was used as a simulation program in this study. It was found from the investigation process that adopting VLAN technology could reduce delay and data of the network and considerably lower throughput, which is a major drawback of VLAN. Ad hoc routing algorithms, including AODV (Ad Hoc On-Demand Distance Vector), DSR (Dynamic Source Routing), and OLSR (Optimized Link State Routing) routing protocols, were used to improve the delay and throughput of the network. Routing methods with VLAN were tested across the WLAN to obtain the best throughput gain performance. The findings also revealed that these ad hoc routing protocols improved the Wireless Sensor Network performance as an additional investigation for the improvement of any network’s delay and throughput.

Improving throughput in SWIPT-based wireless multirelay networks with relay selection and rateless codes

This paper studies a dual-hop Simultaneous Wireless Information and Power Transfer (SWIPT)-based multi-relay network with a direct link. To achieve high throughput in the network, a novel protocol is first developed, in which the network can switch between a direct transmission mode and a Single-Relay-Selection-based Cooperative Transmission (SRS-CT) mode that employs dynamic decode-and-forward relaying accomplished with Rateless Codes (RCs). Then, under this protocol, an optimization problem is formulated to jointly optimize the network operation mode and the resource allocation in the SRS-CT mode. The formulated problem is difficult to solve because not only does the noncausal Channel State Information (CSI) cause the problem to be stochastic, but also the energy state evolution at each relay is complicated by network operation mode decision and resource allocation. Assuming that noncausal CSI is available, the stochastic optimization issue is first to be addressed by solving an involved deterministic optimization problem via dynamic programming, where the complicated energy state evolution issue is addressed by a layered optimization method. Then, based on a finite-state Markov channel model and assuming that CSI statistical properties are known, the stochastic optimization problem is solved by extending the result derived for the noncausal CSI case to the causal CSI case. Finally, a myopic strategy is proposed to achieve a tradeoff between complexity and performance without the knowledge of CSI statistical properties. The simulation results verify that our proposed SRS-and-RC-based design can achieve a maximum of approximately 40% throughput gain over a simple SRS-and-RC-based baseline scheme in SWIPT-based multi-relay networks.

Design and Performance Analysis of an In-Band Full-Duplex MAC Protocol for Ad Hoc Networks

This paper proposes a MAC protocol for ad hoc networks using In-band Full-duplex (IBFD) wireless communications, which are named as AdHoc-FDMAC. To utilize IBFD communications in ad hoc networks, this protocol modifies a number of control frames in the IEEE 802.11 Distributed Coordination Function (DCF) MAC standard. Here, the detailed time sequences for all types of IBFD communications are shown for the data transmission and routing. In this paper, the probability and throughput equations for IBFD communications in different situations have been derived. The performance of the proposed AdHoc-FDMAC has been analysed in terms of probability, throughput, and routing time. The Maximum throughput of AdHoc-FDMAC has been found to be 48.34 Mbps, and it is compared with a recently published ad hoc MAC as well as with the conventional HD MAC. The AdHoc-FDMAC outperforms the recently published ad hoc MAC and conventional HD MAC by 16.80% and 66.50% throughput gain, respectively. AdHoc-FDMAC incorporates the existing Ad hoc On-demand Distance Vector (AODV) routing protocol, but this AODV routing is utilized here using IBFD communications. This paper also compares the routing time of the IBFD-based AODV with the conventional AODV. The result shows that the IBFD-based AODV requires 33.33% less routing time than that of the conventional AODV for 3-hop distance between the transmitter and receiver. This paper suggests that the AdHoc-FDMAC protocol provides much more throughput in ad hoc networks by utilizing IBFD communications.

Online Reinforcement Learning for Beam Tracking and Rate Adaptation in Millimeter-wave Systems

In this paper, we propose MAMBA, a restless multi-armed bandit framework for beam tracking in directional millimeter-wave (mmW) cellular systems. Instead of relying on explicit control messages, MAMBA utilizes the ACK/NACK packets transmitted by user equipments (UEs) to the base station (BS) as a part of the hybrid automatic repeat request (HARQ) procedure. These packets are used to measure the quality of the currently operating downlink beam, and select a new downlink beam along with an appropriate modulation and coding scheme (MCS) for future transmissions. At its core, MAMBA implements an online reinforcement learning technique called adaptive Thompson sampling (ATS), which determines a good beam and associated MCS to be used for the upcoming transmissions. To evaluate MAMBA's performance, we conduct extensive simulations and over-the-air (OTA) experiments over the 28 GHz band using phased-array antennas. We study fixed- as well as adaptive-rate variants of MAMBA, and contrast it with four other beam tracking strategies: a beam selection scheme similar to the one used in 5G NR (called ‘static oracle’), a theoretically optimal but practically infeasible beam tracking scheme (called ‘dynamic oracle’), an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -greedy algorithm [1], and the Unimodal Beam Alignment (UBA) algorithm [2]. Our results show that MAMBA achieves 182% throughput gain over the ‘static oracle’ and is reasonably close to the throughput of the ‘dynamic oracle’. Compared to UBA, MAMBA achieves 25-35% gain in throughput, depending on UE mobility. Finally, when operated at a fixed MCS, MAMBA/ATS achieves 21% gain over the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -greedy algorithm at the lowest applied MCS index, and 255% gain at the highest MCS index.

Improve the throughput of M-to-1 free-space optical systems by employing uniquely decodable codes

This paper utilizes uniquely decodable codes (UDCs) in an M-to-1 free-space optical (FSO) system. Benefiting from UDCs’ nonorthogonal nature, the sum throughput is improved. We first prove that the uniquely decodable property still holds, even in optical fading channels. It is further discovered that the receiver can extract each source’s data from superimposed symbols with only one processing unit. According to theoretical analysis and simulation results, the throughput gain is up to the normalized UDC’s sum rate in high signal-to-noise ratio cases. An equivalent desktop experiment is also implemented to show the feasibility of the UDC-FSO structure.

UAV-Net+: Effective and Energy-Efficient UAV Network Deployment for Extending Cell Tower Coverage With Dynamic Demands

Nowadays, mobile data traffic is growing explosively, but in many realistic scenarios, users still often encounter insufficient or unstable network bandwidth. A promising solution is provided by unmanned aerial vehicle mounted base stations (UAV-BSs) to serve regions with bandwidth shortfall. It is significant to investigate how to deploy UAVs effectively and efficiently for maximizing the sum throughput and service time of a set of mobile clients scattered in a large environment. A basic idea is to use RF ray tracing simulations as a hint to narrow down the search space of UAVs for conducting actual measurements. Furthermore, we formulate two key sub-problems, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">chunk selection</i> , which selects an optimal subset of chunks in the region as the search space of UAVs, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">chunk search</i> , which plans the paths of UAVs to cover all selected chunks for conducting measurements, provide network services and charge timely under energy constraints to maximize the total service time. As they are both proved to be NP-hard, a 3D convolutional deep reinforcement learning (DRL) based chunk selection algorithm and an energy-aware DRL-based chunk search algorithm are proposed to solve them efficiently. A prototype system, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">UAV-Net+</i> , is implemented to evaluate the feasibility by conducting measurements by an UAV mounted WiFi AP communicating with several clients scattered in a campus, reporting an obvious throughput gain with a small measurement overhead and time consumption. Extensive simulations demonstrate the effectiveness of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3D convolutional DRL-based chunk selection algorithm</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">energy-aware DRL-based chunk search algorithm</i> . It is able to achieve 95.35% effective throughput of the skyline algorithm, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Oracle</i> , with only 0.7% time cost. It is more beneficial for providing long-time network service and balancing the workload among UAVs.

PDAA3C: An A3C-Based Multi-Path Data Scheduling Algorithm

In this letter, a path dynamics assessment asynchronous advantage actor-critic scheduling algorithm (PDAA3C) is proposed to solve the MPTCP scheduling problem by using deep reinforcement learning Actor-Critic framework. The algorithm picks out the optimal transmitting path faster by multi-core asynchronous updating and also guarantee the network fairness. Compared with the existing algorithms, the proposed algorithm achieves 8.6% throughput gain over RLDS algorithm, and approaches the theoretic upper bound in the NS3 simulation.

Blockchain‐enabled handover skipping for high mobility train passengers

Due to the cell size decrements and limited sojourn time on a high speed train mobility, unnecessary handovers (HOs) occur, which can lead to higher network communication costs, and affect passengers quality of service (QoS). This paper proposes a novel blockchain-enabled privacy preserving HO skipping framework by using train mobility dataset from the city of London. Using a complex dataset parameters, passenger traffic flows are modelled by averaging various train lines and station's footfall numbers utilising blockchain to maintain privacy. The framework stores pseudonym addresses in order to track the path of users. The proposed framework allows for a better trade-off in terms of 2% (approx.) gain in average throughput, over 100% gain in the last-hop signal quality, and a 50% reduction in HO costs, while also addressing the needs for resources to operate the blockchain.

Enhanced Multilink Single-Radio Operation for the Next-Generation IEEE 802.11 BE Wi-Fi Systems

For the next-generation Wi-Fi systems, the Enhanced Multilink Single-Radio (EMLSR) operation has become a promising feature to improve the Wi-Fi system performance. The EMLSR enables dynamic switching among multiple bands with low-cost implementation and efficient power consumption. However, with realistic channelization of multiple links with 320 MHz bandwidth on 6 GHz and 160 MHz bandwidth on 5 GHz, the performance of EMLSR is jeopardized due to the crowded 5 GHz band with existing Wi-Fi systems. In addition, the unbalanced bandwidth configuration between an access point (AP) and stations (STAs) multilink devices (MLDs) may result in wasted secondary channels when STAs supporting smaller bandwidth stay on the primary channel only. We proposed the further enhanced EMLSR with a new MAC protocol and link selection mechanism, where a primary link (PL) is selected between AP and STA with the unbalanced Link/Band and one or multiple secondary links (SLs) with balanced Link/Band. The STA tunes the main radio on the PL and the scan radio to one of the SLs. The PL will be more prioritized than the SL based on the link selection algorithm to maximize the channel utilization. Compared with legacy EMLSR, the enhanced EMLSR can improve the utilization of the secondary channel. Even under heavy OBSS load on SL or both PL and SL, the further enhanced EMLSR can achieve 50% to 70% throughput gain.

Enhancing Earth Observation Throughput Using Inter-Satellite Communication

Earth observation systems play important roles in many critical applications. The rapid increase of the number of satellites and their sensing capability, however, makes it challenging to send the massive amount of observed data back to the Earth. One promising direction to enhance the earth observation throughput is to use inter-satellite communication. Towards this, we identify two key design factors: 1) the capability to support on-demand scheduling of inter-satellite communication; and 2) the capability to co-optimize the scheduling of observation and transmission missions. For both, rigorous study is needed to determine whether they provide sufficient throughput gain to justify their additional complexity. Our work formulates a generic earth observation and transmission problem to study the maximum network throughput under different settings. By succinctly modeling the different constraints using a generalized time-varying graph representation, we can efficiently find the optimal scheduling solutions. We conduct an extensive study, which shows that using 40 relay satellites from the “starlink” constellation can increase the throughput of 10 sensing satellites from the “Gaofen” constellation by more than 400%. In particular, on-demand scheduling under heavy load and co-optimization of observation/transmission under light but time-critical load can improve the throughput by more than 180% and 100%, respectively.

Energy-efficient routing in LEO satellite networks for extending satellites lifetime

Low Earth Orbit (LEO) satellites, when exposed to the sun, use solar energy for operation, processing, and communication, and with excess energy they recharge their batteries. However, when satellites are in an area with no sunlight, called eclipse areas, they operate using only their battery power. The batteries have limitations on the amount of recharges/discharges, also known as the depth of discharge (DOD) cycle. Therefore, this restricts the useful life of the batteries themselves and also of the satellites. In this paper, we propose two different efficient routing methods for LEO satellite networks, which optimize traffic in order to reduce the DOD of satellites. We improved the Energy and Capacity Aware Routing (ECARS) metric, existing in the literature, by adding the Energy Routing prUning (ERU)-DOD and Energy Routing penAlty (ERA)-DOD methods. These proposed methods prune and penalize, respectively, the links whose satellites have reached a certain minimum battery charge threshold. With this procedure, we avoid over-discharging the satellites’ battery, and thus, the lifetime is extended. Simulations results show that ERU-DOD and ERA-DOD can increase 133.19% and 11.88% the satellites’ batteries lifetime, respectively. Moreover, when comparing our ERU-DOD and ERA-DOD proposals with the ECARS in terms of the average residual energy of the batteries, they provide an increase of 109.77% and 32.73%, respectively. In addition, ERU-DOD and ERA-DOD proposals showed a gain in throughput of 7.28% and 3.06% higher than ECARS. Furthermore, compared to the ECARS metric, the ERA-DOD proposal has a 1.1% lower delay, a 1.5% lower number of hops, and 0.49% less in the total of blocked sources.

Queue-Aware Access Prioritization for Massive Machine-Type Communication

One of the pivotal services of the fifth generation (5G) of cellular technology is massive Machine-type Communications (mMTCs), which is intended to support connecting high density of machine-type devices (MTDs). Random access channel of long-term evolution (LTE)/LTE advanced needs to be modified in order to support the large simultaneous arrival of MTDs. 3GPP suggested access class barring (ACB) as a mechanism to inhibit network congestion in the mMTC or massive Internet of Things (IoT) scenario. Consequently, in devices that are repeatedly ignored by ACB, the queue of data packets keeps growing. In storage-constrained IoT nodes with limited buffer, this may lead to packet drop due to buffer overflow, causing a decline in the overall throughput of the system. To address this issue, a novel queue-aware prioritized access classification (QPAC)-based ACB technique is proposed in this article, where MTDs having data queue size close to its buffer limit are dynamically given higher priority in ACB. To study the queue build-up at each MTC device, a node-centric analysis of ACB in the buffer-constrained scenario is performed using a 2-D Markov chain. It is shown that the proposed QPAC scheme, with optimal model parameters obtained by maximizing overall system utility, offers up to 70% gain in throughput compared to the nearest competitive dynamic ACB scheme.

Integrated Access and Backhaul in Millimeter-Wave Cellular: Benefits and Challenges

The recently proposed NR-ready integrated access and backhaul (IAB) architecture promises to bring a cost-efficient deployment solution for both coverage extension and capacity boosting in the emerging 5G/5G+ systems. While its impact on the coverage extension was thoroughly addressed in the literature, the effect of advanced functionalities such as multihop, multi-connectivity, and multi-beam operations on the throughput remained unclear. We review and characterize the system-level impact of these capabilities on the performance of self-backhauled IAB systems operating in half-duplex mode and utilizing millimeter-wave (mmWave) technology across both access and backhaul. Our results indicate that the throughput gain of multihopping and multi-beaming is significant even without multi-connectivity operation. Another important lesson is that in all-mmWave systems with link blockage, multi-connectivity with link switching allows achieving self-load balancing. Finally, we outline future research directions.

Priority-Based Dynamic IoT-Downlink Communications with Blind Transmission-Mode Recognition

In downlink Internet of things (IoT) applications, certain nodes can be given a higher transmission priority than others, and hence might be allocated more transmission resources. Consequently, some nodes may face a resource-starvation problem. To overcome such a predicament, this article proposes an opportunistic non-orthogonal multiple access (NOMA) scheme to enable low priority (LP) nodes (LPNs) to share the transmission resources of high priority (HP) nodes (HPNs) while prioritizing the quality of service (QoS) requirements of the HPNs. In the proposed scheme, the control center (CC) may decide to multiplex the data of one or more LPNs with the HPN data using NOMA, which can improve the network throughput substantially. Such a decision is based on the channel conditions and QoS requirements for the HPNs and LPNs. Hence, the proposed system may operate in one of the following four modes, HPN orthogonal multiple access (OMA), LPN-OMA, (HPN, LPN)-NOMA, and the OFF mode where all nodes are muted. To improve the network efficiency and reduce overhead, the network is considered uncoordinated where the receiving nodes do not receive side information about the selected transmission-mode by the CC, leaving it to the receiving nodes to blindly recognize the transmission-mode. The network complexity and throughput trade-off is considered for fixed and adaptive power assignments. The results show that the proposed system can provide substantial throughput improvement over conventional NOMA transmission. For the example of a pair of HPN and LPN, the maximum throughput gain with opti-mal power allocation is about 0.85 bits/symbol, which implies that the throughput relative improvement is about 9 folds. The article also discuss the challenges and potential solutions of the proposed framework.

Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity.

The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs)-assisted wireless networks are one of the promising solutions to control the wireless channel by altering the electromagnetic properties of the signal. The dual connectivity (DC) increases the per-user throughput by utilizing radio resources from two different base stations. In this work, we propose the RIS-assisted DC system to improve the per-user throughput of the users by utilizing resources from two base stations (BSs) in proximity via different RISs. Given an -fair utility function, the joint resource allocation and the user scheduling of a RIS-assisted DC system is formulated as an optimization problem and the optimal user scheduling time fraction is derived. A heuristic is proposed to solve the formulated optimization problem with the derived optimal user scheduling time fractions. Exhaustive simulation results for coverage and throughput of the RIS-assisted DC system are presented with varying user, BS, blockage, and RIS densities for different fairness values. Further, we show that the proposed RIS-assisted DC system provides significant throughput gain of 52% and 48% in certain scenarios when compared to the existing benchmark and DC systems.

Sensor-Assisted Rate Adaptation for UAV MU-MIMO Networks

Propelled by multi-user MIMO (MU-MIMO) technology, unmanned aerial vehicles (UAVs) as mobile hotspots have recently emerged as an attractive wireless communication paradigm. Rate adaptation (RA) becomes indispensable to enhance UAV communication robustness against UAV mobility-induced channel variances. However, existing MU-MIMO RA algorithms are mainly designed for ground communications with relatively stable channel coherence time, which incurs channel measurement staleness and sub-optimal rate selections when coping with highly dynamic air-to-ground links. In this paper, we propose SensRate, a new uplink MU-MIMO RA algorithm dedicated for low-altitude UAVs, which exploits inherent onboard sensors used for flight control with no extra cost. We propose a novel channel prediction algorithm that utilizes sensor-estimated flight states to assist channel direction prediction for each client and estimate inter-user interference for optimal rates. We provide an implementation of our design using a commercial UAV and show that it achieves an average throughput gain of 1.24\times and 1.28\times compared with the bestknown RA algorithm for 2- and 3-antenna APs, respectively

Sliding-Window-Based RNC Scheme in UAV Multicasting: Performance Analysis and Network Optimization

Unmanned aerial vehicles (UAVs)-enabled multicasting network has attracted significant attention in recent years. However, there are still some disadvantages of existing multicasting schemes used in these systems, such as low transmission efficiency and high feedback overhead. Accordingly, we propose a sliding coding window (SCW)-based random network coding (SCWRNC) scheme for a UAV multicasting network where one UAV base station is dispatched to the multicast data stream to multiple user equipments (UEs). The proposed scheme includes an SCW scheduling original packets for encoding, a lower triangular coding structure enabling UEs to decode out information even without receiving a full set of coded packets, and a feedback-compete mechanism requiring only one UE to send feedback information. The packet scheduling process is described as a five-tuple Markov decision process. Then, we give a theoretical analysis of the proposed scheme, based on which the sliding steps of SCW and the UAV hovering location are jointly optimized to maximize the system throughput. The optimal sliding steps are obtained by applying the Greedy scheduling technique, while the UAV optimal position is obtained by minimizing the maximum outage probability of all UEs. Furthermore, we also propose a flexible feedback mechanism, which enables more than one UE to send feedback for systems with sufficient resources and a “F-SCWRNC” scheme for systems where no UE is allowed to send feedback. Numerical results show that both the proposed SCWRNC scheme and F-SCWRNC scheme could achieve significant throughput gain over the existing ones.

Efficient Water Softening in Heavy Oil Steamflood Operations

Summary Pigging of once through steam generators (OTSGs) has indicated various types of scales, the most predominant of these being silicates of hardness causing ions. It was noted that scaling propensity can potentially go up with higher steam quality (SQ) as the reject stream gets concentrated with ions. However, models suggested that there are benefits of higher SQ in enhancing fuel savings (8%) and electricity savings (2%) when SQ was increased by 20%. The challenges of higher SQ were noted in terms of increased scaling tendency and therefore the need for improved softening. In Field D, the service cycle, the backwash cycle, and the brining cycle were optimized leading to a gain in throughput and reduction in salt consumption. Service cycle improvement gained 30 to 130% in throughput between two regenerations, backwash cycle improvement by fluidizing the bed to nearly 35% helped gain 10% in throughput, and reduction of brining cycle from 75 to 48 minutes helped reduce salt consumption by 56% without impacting the throughput. In Field B, a 6-month pilot revealed that shallow shell resins where ion exchange is more efficient due to inert core (better intraparticle diffusion control) can enhance the throughput by 30 to 80% and simultaneously reduce the number of regenerations by 15 to 30%. Resin fouling is still a major challenge to contend with as oil can foul the resin and throughput can decline by 0.5 to 3 folds. In a plant operation, where there are multiple softener and brine vessels, there is a need to optimize them as a system. Reliability, availability, and maintainability (RAM) models are used in Field C to (a) address equipment configuration optimization with impact on capital capacity expansion project scope, (b) understand how net soft water delivery capacity was affected by increases in inlet hardness, and (c) assess through a comparison scenario if the large cost of addressing the valve issue in an upstream nutshell filter was worth the lost production opportunity related to unplanned downtime.

Enhancing PAPR and Throughput for DFT-s-OFDM System Using FTN and IOTA Filtering.

High frequency wireless communication aims to provide ultra high-speed transmissions for various application scenarios. The waveform design for high frequency communication is challenging due to the requirements for high spectrum efficiency, as well as good hardware compatibility. With high flexibility and low peak-to-average power ratio (PAPR), discrete Fourier transformation spreading-based orthogonal frequency division multiplexing (DFT-s-OFDM) can be a promising candidate waveform. To further enhance the spectral efficiency, we integrate faster-than-Nyquist (FTN) signaling in DFT-s-OFDM, and find that the PAPR performance can also be improved. While FTN can introduce increased inter-symbol interference (ISI), in this paper, we deploy an isotropic orthogonal transform algorithm (IOTA) filter for FTN-enhanced DFT-s-OFDM, where the compact time-frequency structure of the IOTA filter can significantly reduce the ISI. Simulation results show that the proposed waveform is capable of achieving good performance in PAPR, bit error rate (BER) and throughput, simultaneously, with dB gain in PAPR and 50% gain in throughput.

SlicedRAN: Service-Aware Network Slicing Framework for 5G Radio Access Networks

5G mobile networks are envisioned to substantiate new vertical services with diverse performance requirements. Slicing in the radio access network (RAN) promises an efficient solution for these diversified needs of 5G networks, which foresees the separation of the base station functionality between the central unit (CU) and the distributed remote radio heads. In this article, we formulate a mixed integer programming (MIP) framework that maximizes the throughput by jointly selecting the optimal functional split and the routing path from a connected user equipment to the CU, while satisfying the agreed service level agreements (SLAs) of each service. Furthermore, we propose an effective heuristic, SlicedRAN, which creates isolated RAN slices premised on the service requirements connected through a fronthaul/backhaul (FH/BH) network and obtains near-optimal solutions in a short computing time compared to the MIP framework. Our results show that there is a tradeoff between the architecture of the FH/BH network and the minimum SLA of each slice, which provides a solution to efficiently design a virtualized network infrastructure. According to the results, the SlicedRAN outperforms existing state-of-the-art up to 112% gain in throughput. Results are shown close to the optimal results, with a loss below 5%.