Sixth Generation (6G) networks are envisioned to unify 5G services, offering new service classes with stringent data rate, connectivity, and latency requirements. End-to-End (E2E) network slicing orchestration is essential to ensure optimum resource provisioning for services while upholding service quality standards. E2E slicing for a large number of slices hosting diverse services across multiple domains is a complex problem, for which highly centralized resource management approaches have been proposed in literature. With increasing types of services in 6G, the demand for slices will expand, making centralized solutions less practical due to scalability and responsiveness issues. To address this challenge, this paper proposes a novel hierarchical Multi-Domain Resource Management (MDRM) framework that translates global slice-hosted service requirements into requirements per network domain. MDRM operates in two phases; in the first phase, a centralized cross-domain resource optimization model is proposed to estimate user transmission parameters. Leveraging this information, the framework deploys a distributed and probabilistic open radio access network resource management strategy in the second phase that combinatorially groups and manages service requests. The two-phase approach allows the system to be highly responsive to address a large volume of 6G requests while significantly improving user service quality and experience. Extensive simulations show that MDRM enhances resource provisioning efficiency by up to 66.48%, thereby boosting slice throughput by up to 52.63% while minimizing decision delay by 57.87% compared to state-of-the-art algorithms. Additionally, MDRM enhances user service experience by up to 4.44 times compared to existing algorithms.

Upcoming 6G networks are expected to serve several mission-critical cyber-physical systems (CPS) applications that demand timely and fresh control updates. Different from traditional quality of service (QoS) metrics, Age of Information (AoI) measures the freshness of information for CPS applications. To efficiently serve such applications, cell-free massive multipleinput multiple-output (CF-mMIMO) has emerged as a better alternative to traditional cellular architectures. To the best of our knowledge, the time-average power minimization problem has not been addressed so far in AoI-constrained CF-mMIMO networks. In this context, we aim to minimize the time-average power consumed in CF-mMIMO networks with maximum tolerable average AoI constraints, along with communication QoS and per-transmitter power budget constraints. We propose a novel iterative scheduling and precoding algorithm to achieve our objective. Detailed analytical modeling and resulting simulation illustrate the performance of our algorithm as a function of a penalty parameter, which show the average AoI of all users are within constraint limits. We also show that the penalty parameter allows to dynamically prioritize between the time-averages of power consumed and AoI as per performance requirements.

Designing efficient routing protocols for Uncrewed Aerial Vehicle (UAV)-assisted communication presents significant challenges due to rapidly changing topology, limited battery capacity, and dynamic network conditions.such as energy consumption, link quality, or latency but often overlook the necessity of an integrated approach considering a broader range of factors. This paper introduces the Improved Q-learning-based Multi-hop Routing (IQMR) algorithm that facilitates energy-efficient, and reliable data transmission in UAV-assisted communication. IQMR achieves this by selecting the optimal next-hop node to ensure efficient energy utilization, reliable packet delivery through collision avoidance, and adaptive network reorganization to maintain connectivity without relying on predefined UAV paths. To the best of our knowledge, IQMR is the first to employ a multi-objective framework that captures the inter-dependencies between network parameters and UAV operational states while leveraging$Q(\lambda)$learning to make routing decisions, ensuring reliable communication in dynamic environments. Results show that IQMR demonstrates a 36.35% improvement in energy efficiency and a 32.05% increase in data throughput over existing methods.

The progression of Sixth-Generation (6G) services requires networks to meet stringent Quality of Service (QoS) and Quality of Experience (QoE) standards, demanding superior performance from all network segments. Selecting the most suitable path that meets application demands across multiple network segments is a key strategy for achieving these objectives. Traditional and modern path selection methods focus on QoS metrics such as bandwidth and latency to ensure efficient and reliable data delivery. However, as 6G introduces more interactive applications like Virtual Reality (VR) and Augmented Reality (AR), prioritizing user experience alongside QoS metrics becomes more crucial. This paper presents a Service-Aware Optimal Path Selection (SOPS) algorithm designed to select an optimal End-to-End (E2E) path for each application by minimizing a global cost function that incorporates both QoS and QoE parameters. The global optimality of the selected E2E path is proven by demonstrating the closed and convex nature of the underlying cost functions. Moreover, our proposed distributed cost function ensures optimal E2E paths formed from selected network segment-specific paths. Extensive simulations show that SOPS improves QoS and QoE when compared with other state-of-the-art routing algorithms. SOPS enhances QoS by improving reliability by 0.84% and reducing packet delay by 5.55%. An improvement of up to 99.65% is seen in the connection acceptance ratio, particularly for diverse application requirements. Significant improvements in QoE are observed across Hypertext Transfer Protocol (HTTP) and video applications, with throughput increases of 10.04% and 7.99%, jitter reductions of 86.25% and 2.49%, and delay improvements of 77.08% and 0.69%, respectively.

Puncturing ongoing enhanced Mobile Broadband (eMBB) traffic to accommodate the stringent delay and reliability requirements of ultrareliable low-latency communication (URLLC) Internet of Things (IoT) traffic has attracted a lot of attention recently. These puncturing decisions are based on the channel quality indicator (CQI) as seen by the eMBB/URLLC users, and any error/delay in the estimation/observation of the CQI is likely to adversely impact the reliability of URLLC-IoT traffic. Moreover, each puncturing decision incurs a signaling overhead in terms of the downlink control information for the URLLC-IoT devices, as well as puncturing indication for eMBB devices. In this work, we propose a static puncturing scheme which does not rely on CQI information. The reliability of URLLC-IoT transmissions is maintained by designing the system for lowest supported CQI. The deterministic nature of the proposed technique will allow a base station to schedule the eMBB traffic in such a way that system design goals like overall fairness and other Quality of Experience parameters for eMBB users can be optimized. The amount of URLLC-IoT traffic that can be served reliably at any given time is always limited, and we quantify this limit for the proposed scheme by numerically evaluating the maximum URLLC-IoT arrival rate that can be supported for any chosen level of reliability. Furthermore, we show that our puncturing scheme provides a deterministic and contained impact on eMBB throughput when compared to other schemes that puncture eMBB traffic greedily with respect to URLLC-IoT CQI or eMBB sum-throughput.

Optimum network slice resource allocation for multiple User Equipment (UE) requesting several services concurrently in a scalable manner is a complex open research problem. Each network slice is designed to support distinct applications with corresponding Service Level Agreements (SLAs) across multiple UEs. The distribution of network resources across slices has been a challenge to achieve the SLAs under limited bandwidth and power budget constraints. This is referred to as inter-slice resource allocation, where a UE may simultaneously request multiple services hosted across slices. When a UE is assigned a slice, the slice shares the available resources across new and existing UEs without violating the SLA. This is referred to as intra-slice scalability. While inter-slice resource allocation has been addressed in the literature, further throughput gains can be achieved by improving intra-slice scalability. This paper presents a novel Probabilistic Intra-slice Resource Service Scheduling (PRSS) method. PRSS algorithm works in two stages. In the first stage, the service throughput is estimated using a multinomial probabilistic model, followed by dynamic conditional resource estimation in the second stage. For newly requested services, the resources are re-estimated and reconfigured across prior inter and intra-slice services. The proposed two-stage method allows the system to be highly adaptive with respect to the number of UEs and their requested services hosted across slices. Analytical and simulation results show that by using PRSS, the number of services served with a better experience in terms of service quality, i.e., throughput is enhanced by 20% to 75% compared to state-of-the-art schedulers.

Federated Learning (FL) is an important Machine Learning (ML) technique in a decentralized computing environment. For FL in the 5thgeneration (5G) and beyond networks, there is a need to improve the link capacity, latency, and reliability for every iteration. This would help the user equipment (UE) to efficiently download the global ML model from the FL server, upload the partially trained model from the UE, and update the global ML model hosted on the FL server. However, due to limited coverage areas of terrestrial mobile networks and limited bandwidth at the periphery of a terrestrial cell, the UEs may be out of coverage or have low bandwidth to support the iterations for FL, lowering the performance of FL. To enhance the performance, we propose using aerial cells to augment the existing terrestrial infrastructure and offer enhanced coverage and capacity to the operators. There has been limited work on the management of aerial links in an augmented deployment to improve the performance of FL. To the best of our knowledge, for the first time, we present and analyze a novel Federated Learning by Aerial-Assisted Protocol (FLAP) that selects and manages the aerial link for the federated UEs in each training iteration. FLAP will improve the reliability and latency of the FL process. Through call flow analysis and extensive simulation, we have shown an increase of 50% in the number of federated UEs taking part in FL. Our results reveal that FLAP enables a much faster convergence for an image classification model with much higher accuracy.

Fifth-generation millimeter wave (mmWave) systems deploy spatial beam search using synchronization signal (SS) blocks for initial access (IA). Technique based on narrow beam sweeping procedure completed in a single SS burst is optimum for idle users that have arrived before IA. With a maximum IA duration of 5ms specified by 3GPP Release 15, the probability of user arrival during IA is non-trivial. For these users, existing search procedures will result in significant discovery delays and low detection probability. This work considers an alternative scenario wherein the user arrives after the commencement of IA. In such cases, a single SS burst may not suffice and one must consider repeating the SS burst to enhance user detection probability and reduce IA delay. Repetition of SS burst brings the trade-off between half-power beamwidth (HPBW) and the number of SS blocks per burst i.e., large HPBW supports a smaller number of SS blocks per burst and vice-versa. To achieve high accuracy of angular position with SS burst repetition, a grating-based search has been proposed which utilizes antenna element spacing greater than half-wavelength. This paper presents an IA delay, location error and detection analysis for both scenarios; with and without SS burst repetition. Simulation results demonstrate the enhanced performance of the proposed grating search technique with SS burst repetition in terms of user detection, reduced IA delay, and low angular position error.

Massive multiple-input multiple-output (MIMO) systems operating in the millimeter-wave (mmWave) frequency band support extremely high data rates. One of the major shortcoming of severe path losses in these systems is addressed by the employment of large phased array antennas with highly directional beams. Owing to the precise nature of the beams, identification of the most suitable beam for link establishment between the base station (BS) and the user equipment (UE) becomes an extremely challenging and time-consuming task. The existing two-level phased array approach is based on an exhaustive search that requires a high number of beam sweeps. In this work, a novel hierarchical fast beam search approach based on a two-level phased array is proposed for improved UE discovery in mmWave massive MIMO systems. The proposed approach leverages suitable antenna spacing and radiation pattern multiplication at two-levels to yield refined beams. The hierarchical implementation via grouped antenna units results in a refinement of the beamspace at the digital level based on the best beam direction evaluated at the analog subarray level. Extensive simulation results validate the superior performance of the proposed algorithm in terms of mean position error and the total number of beam sweeps. The investigation of misdetection probability will be considered in our future work.

In Band Full Duplex (IBFD) is a promising technology to double Spectral Efficiency (SE). Due to practical limitations in realizing IBFD User Equipments (UEs), Hybrid IBFD Cellular Network (HICN), composed of an IBFD Base Station (BS) and legacy Half Duplex (HD) UEs, is preferred. Optimum resource allocation algorithm for HICNs has been of great interest, and it primarily relies on UE-to-UE Channel State Information (CSI). Though computational and signaling intensive approaches are used in literature to obtain this CSI, we introduce a location-aware technique without these overheads at UEs. Using proposed idea of frequency sharing within UE groups, we formulate a constrained optimization problem for HICNs to maximize sum-SE. Based on multiple constraints imposed, frequency sharing possibilities amongst UEs are captured in the adjacency matrix, which lays the foundation for UE grouping. An exhaustive search from adjacency matrix identifies the theoreticallybestUE groups to achieve maximum frequency sharing. For practical realizations, a computationally efficient algorithm to identifyoptimalgroups of two and/or three UEs is derived. We propose anovelcorrelation approach to avoid expensive resource allocations in every scheduling interval. Simulation results reveal median sum-SE of 89% over HD systems, thus making the proposed solution far more attractive.

Demonstrated Spectral Efficiency (SE) gain by In Band Full Duplex (IBFD) makes it an attractive radio technology. Owing to inherent complexities in IBFD, Hybrid IBFD Cellular Network (HICN) is opted in practice because it limits IBFD capability only to Base Station and continues with legacy Half Duplex (HD) User Equipments (UEs). Since sharing frequencies within UE groups maximizes sum-SE in a HICN, we formulate a grouped UEs maximization problem for achieving maximum frequency sharing. Unlike heuristic search methods developed in literature, in this paper, we build a mathematical framework for UE grouping. Three grouping algorithms are analytically derived in closed-forms with varying performance and time complexity trade-offs. The optimal algorithm provides benchmarking on these performance measures. Using structural advantages of a HICN, we derive reduced search-optimal algorithm that reduces time complexity while guaranteeing optimal grouping, whereas near-optimal algorithm achieves close-to-optimal grouping with substantially reduced time complexity for real-time cellular systems. We further introduce the concept of ineligible UEs, which uniformly reduces time complexity of all three algorithms without impacting their grouping performance. Extensive simulations reveal that the proposed near-optimal algorithm achieved a median sum-SE of 93.5% of theoretically doubling maximum over legacy HD systems, thus emerging as a prospective solution.

Multi SIM (Multi Subscriber Identity Module) Multi Standby (MSMS) feature-enabled devices have gained huge popularity among smartphone users as it offers the flexibility to use multiple SIM cards of the same or different operators on the same handheld device. To reduce cost, these MSMS devices are predominantly built with a single Radio Frequency Integrated Circuit (RFIC), restricting Protocol Stack Unit (PSU) of only one SIM to communicate with the cellular network at a time. Random Access (RA) procedure in MSMS devices experiences two delays: (i) typical RACH contention time, (ii) the PSU wait time to get RFIC to transmit RA messages. IoT (Internet of Things) devices, Single SIM, and Multi SIM Multi Active (MSMA, with an equal number of SIMs and RFICs) smartphones do not have the above second delay. As a result, MSMS device with a single RFIC has to face both delays to get network access even in 5G and future networks. To improve RA performance of MSMS devices, we propose a novel algorithm called, Network Assisted Random Access for MSMS (NARAM), which enables the 5G network to estimate the prevailing congestion levels using Hidden Markov Model (HMM) and reduce the first delay by tuning the network configuration appropriately. The simulation results reveal that the MSMS RA delay reduced by 8% from legacy. Furthermore, the RA failure rate of MSMS devices dropped by 23% when compared to the legacy.

User Equipment (UE) with more than one Subscriber Identity Module (SIM) is designed usually with a single Radio Frequency Integrated Circuit (RFIC), with one Rx and one Tx path component, for reduction of cost. The RFIC components are shared for serving requests from as many SIMs (Subscriber Identify Module) in the UE, leading to Physical Channel Resource (PCR) wastage for the operator during the tune away periods. We present a novel technique to arrive at the number of Rx and Tx paths components, that should be deployed when designing a Multi-SIM UE with limited PCR wastage. Through mathematical modelling, supported with simulations, our proposal gives the right number (e.g. 2 each) of Rx and Tx paths to be used while designing up to Quad-SIM (4 SIMs) UE. This results in saving up to 33.3 % both in the cost of the RFIC component selection and peak power consumption of the Quad-SIM UE as compared to literature.

In current Wi-Fi technology trend, Mobile Hotspot (MHS) or Soft Access Point (S-AP) is an integral part of our day-to-day life. At any time, MHS could be enabled as Wi-Fi Hotspot in mobility devices (smart phone, tablet) with cellular backhaul network (3G/4G/5G) and provides Internet access to client devices such as laptop, TV etc. Unlike Wi-Fi Access Point, which is typically a powered device, MHS is enabled as battery-operated device. In addition, MHS consumes higher power and reported as one of the primary Voice of Customer (VoC) issue. Due to high power consumption, many customers are skeptical about MHS feature and its continuous usage. Apart from few literatures, there is no specific IEEE 802.11 standard for MHS and its power management. In this paper, we have proposed a Machine Learning (ML) based Intelligent MHS Power Save (I-MHSPS) algorithm using Wi-Fi parameters such as RSSI, SNR, TX power and channel condition. In addition, we have used other contextual parameters such as client behavior, battery level, application usage and internet backhaul to improve the accuracy of our algorithm. In I-MHSPS, we have proposed Intelligent Transmit Power Control (I-TPC): MHS TX power regulation based on client vicinity, Intelligent Ultra Power Save (I-UPS): Applying different system power level for MHS operation and Intelligent Low Power Encryption (I-LPE): Enabling low power encryption for short range MHS. In our first experiment with I-TPC idea has reduced power consumption by 10-16% approximately when compared to existing methodologies. In second experiment for I-UPS, we have applied different system power levels for MHS operation and achieved power saving around 22% without any performance degradation. Further, in third experiment, using I-LPE method, we have observed the power required for encryption of data packets reduced by 20%.

To improve the performance of the Transmission Control Protocol (TCP), the Quick UDP Internet Connections (QUIC) was introduced. However, from the recent literature, in the wireless networks, QUIC does not fully utilize the link capacity, because of varying network wireless medium characteristics for an application. To the best of our knowledge, for the first time, this paper has proposed two novel protocols to overcome the wireless network's challenges, by MultiPipe (multi sessions) QUIC protocol (MP-QUIC). The two MP-QUIC's novel protocols are (i) Round Robin MP-QUIC (RR-MP-QUIC) and (ii) Cross-Layer Burst Aware MP-QUIC (CBA-MP-QUIC). In RR-MP-QUIC, multiple pipes are created between source as well as destination and assign a pipe to each object in a round-robin manner. We set up the testbed over live air commercial network. The experimental results reveal that the RR-MP-QUIC Page Load Time (PLT) of a web page decreases by 76% with respect to QUIC. Furthermore, to improve the performance of RR-MPQUIC, we proposed CBA-MP-QUIC, which optimally creates pipes, efficiently schedules the objects and understands with respect to cross-layer (wireless channel characteristics and load in data link layer) parameters. Hence this adapts dynamically to the network conditions and maintains fairness between the applications in User Equipment (UE) and within the same application. Experimental result of CBA-MP-QUIC on live air improves the web page PLT by 143% with respect to QUIC.

MultiSIM feature offers convenience to a user by providing connection to multiple operators for accessing different services through different SIMs with a User Equipment (UE). Generally, MultiSIM is deployed as a Dual Subscriber-Identity-Module (SIM) Dual Standby (DSDS) feature; sharing transceiver with secondary SIM (SIM-2), while primary SIM (SIM-I) is on an active data session with Operator-1. The sharing of transceiver (called tune away), causes inactivity on the Radio Link (RL) between UE and eNodeB (eNB) leading the Physical Channel Resource (PCR) wastage for Operator -1. Multi SIM Multi Standby (MSMS) feature is an enhancement over DSDS to scale up the usage with three or more SIMs with single transceiver. With MSMS deployment, PCR wastage will scale up as compared to DSDS, as it additionally introduces more challenges, like (a) increased number of tune away events due to more than two SIMs, (b) increase in tune away duration due to a cascading effect of simultaneous and back-to-back high priority procedures on secondary SIMs. MSMS will thus affect by increasing the backhaul retransmissions and buffering at Operator -1. To overcome the above challenges and to ensure MSMS is a reality soon, to the best of our knowledge for the first time, this paper proposes a new signaling via Non Access Stratum (NAS) layer, from UE to Evolved Packet Core (EPC) to indicate tune away when the duration of tune away spans several seconds. We propose to apply NAS signaling in a scenario specific manner to address tune away events. Through extensive simulation derived from mathematical modeling and measurements obtained from test bed with commercial UEs, the results reveal that for three SIMs in cascaded scenarios, with the proposed solution, the PCR wastage is reduced to only 7.9 % against 48.5% and eNB buffering reduced by 95% in comparison to the available literature for a practical deployment.

WiFi Mesh network is made up of Mesh Access Points (MAPs). MAPs perform two roles: Mesh Station (STA) to communicate with other MAPs, and Basic Service Set (BSS) AP to interact with WiFi client devices. Hence, MAPs typically broadcast two kinds of independent beacons periodically, which will be received by other MAPs and WiFi client devices. This could lead to multiple beacon collision scenarios. And these beacon collisions occur in Mesh STA or WiFi client devices when other MAPs are hidden (two hops away). We have proposed Unified Signaling Beacon Framework (USBF) concept to reduce the probability of these beacon collision substantially. The proposed USBF performs unification and synchronization between BSS AP and Mesh STA beacons in MAPs. Our simulation result with the proposed concept shows improvement of beacon processing time (reduced around 35%), and total energy consumption (reduced around 22%).

Mobile Hotspots are very popular as they use 4G-LTE (via eNodeB to the network) to provide connectivity to multiple User Equipments (UEs). Additionally, In order to improve the performance of a session from a UE which is directly connected to the eNodeB, literature has proposed Multi-Pathing (MP) concepts (Multi Path TCP, Multi Path QUIC). However, these MP concepts do not work for a UE connected to eNodeB through the hotspot. Moreover, to improve the performance of hotspot, there can be MP connections from mobile hotspot itself. First one from hotspot to LTE eNodeB (Licensed spectrum) and second to WiFi (unlicensed) Access Point (AP). To the best of our knowledge, in available literature, a hotspot device does not provide MP aggregation of licensed and unlicensed spectrums to the connected UEs. Secondly, traffic from the hotspot device majorly goes over LTE hence congesting the licensed spectrum. With respect to the above two challenges, we proposed a novel hotspot architecture called Next-Gen Mobile HotSpot (NextGen-MHS), which is a unique approach to aggregate any combination of available licensed (4G/5G) with unlicensed (WiFi/5G) spectrum and provide the aggregated connection as a Mobile-Hotspot AP. We have successfully implemented this new architecture of NextGen-MHS and conducted evaluation experiments with 4G (licensed) and WiFi (unlicensed). NextGen-MHS significantly provides better results with 80% aggregated throughput and 45% reduction in data traffic over licensed spectrum.

A user equipment (UE) with Dual Subscriber-identity-module (SIM) Dual Standby (DSDS) feature can connect to two network operators, such as, each SIM is associated with one operator and with one Protocol Software Stack (PSS) while both the SIMs share same Radio Frequency Integrated Circuit (RFIC). UE schedules SIM-1 to communicate with Operator-1 and at the same time SIM-2 remains standby and vice versa. The ongoing data session with Operator-1, through SIM-1 is interrupted while the UE's RFIC tunes away to attend a higher priority signaling through SIM-2 to Operator-2. This tune away procedure of RFIC results in allocated Physical Channel Resource (PCR) wastage at Operator-1 for SIM-1 during the tune away period. After the end of tune away at SIM-1, it further more suffers from low PCR allocation from Operator-1, because of no response from SIM-1 during tune away period. To overcome the above challenges, to the best of our knowledge, for first time this paper proposed Signaling indication from UE to network for RFIC tune away event to reduce network PCR wastage. This signaling is done by: (a) Radio Resource Control (RRC) layer (b) Medium Access Control (MAC) layer (c) Layer 1 (L1). Each of the above-mentioned signaling has particular level of latency and reliability. We propose to apply above-mentioned signaling in scenario specific manner to address all possible tune away events. Through extensive simulation derived from mathematical modelling and measurements obtained from test bed with commercial DSDS UEs, the results reveal an improvement in overall PCR utilization for an operator and increase in UE admission by up to 30% in comparison with current DSDS solutions.

This is an era of Internet and IOT devices where every device needs Internet connection. The Mobile Hotspot (MHS, SoftAP) provided by smartphone is one solution where user cannot find an Access Point (AP) and uses his/her MHS to continue the connectivity to Internet. Smartphone consumes around 10 times more power while MHS is active, however few proposals have been made for power save in MHS which are difficult to commercialize and also would require client side changes. The IEEE 802.11 standard defined power saving techniques which is applicable only for client devices and it is not efficient when acting as MHS. This paper proposes a novel idea which has a hybrid approach called as High Throughput Mode Power Save (HTMPS) and Low Throughput Mode Power Save (LTMPS). Our experimental results show that we can save up to 20% power using the first method and put MHS interface to sleep for 50% of the time during no data activity using LTMPS.

Augmented reality (AR), virtual reality (VR), health and payments are fueling the next wave of cellular connected smart devices leading to increased number of user equipment (UE) per person. This trend of multiple devices per user and his frequent needs to transfer on going session(s) from one smart device to another opens up several challenges for cellular technology, like: (a) managing separate operator subscription for each UE, (b) supporting low latency for session transfer, and (c) supporting seamless change of smart device after session transfer. In literature, session transfers one at a time from a source UE (S_UE) to a target UE (T_UE) using Session Initiation Protocol (SIP), with high latency of the order of several seconds per session and significant power consumption on every T_UE. We present a Session Cloning Protocol (SCP), which to the best of our knowledge is novel and first of its kind to provide low latency and low power consumption for session transfer between smart devices. SCP proposes using a peer-to-peer (P2P) link to share the required connectivity parameters from S_UE to a proximate T_UE. SCP contributes the following: (a) Session transfer from S_UE to T_UE when T_UE was offline at beginning of session transfer initiation, and S_UE was in connected state with one or more sessions. (b) State and parameter transfer from S_UE to T_UE, when T_UE was offline and S_UE was either in idle or out of coverage states, and (c) Upgrading/Downgrading of Quality of Service (QoS) of the transferred session(s) at T_UE when its capability is higher/lower than S_UE respectively. The simulation reveals that SCP reduces the latency of session transfer by over 90%, and energy consumption by over 99% as compared to SIP based session transfer.

Smart meter applications have been gaining huge importance due to its use in many appliances of citizen requirements. Wireless standards have been proposing requirements and protocols to support such applications of smart meters connectivity to networks through MTC (Machine Type Communication). One of the main requirements of smart meter applications is to have periodic reporting of meter readings to server without any human intervention. LTE (Long Term Evolution) network being the latest cellular technology with extended coverage becomes a preferred choice for supporting connectivity between smart meter device and network. After each data transfer to server, connection between transmission-device in smart meter and LTE network is terminated to allow device to move to power saving mode and hence initial access through RACH (Random Access Channel) is required every time for establishing connection to network before transmitting data to server. When such large number of initial access is attempted at the same time, it would increase the probability of collision among smart meter devices. This would further delay access to network and in turns increases the battery consumption due to retransmissions till initial access is successful. To overcome the above challenge of initial access congestion, we proposed a novel algorithm called Time Distributed Initial Access (TDIA), which group the smart meters and available preambles to distribute the start time of RACH transmissions in each group based on their IMSI (International Mobile Subscriber Identity). The major advantage of our TDIA algorithm is that each smart meter device could calculate its start time on its own without much overhead in network. The analytical model supported simulation results shows that our TDIA algorithm of uniformly distributing the initial access attempts increases the probability of successful preamble transmission to around 98% compared to 70% in Poisson distributed arrival process and 25% in Beta distributed arrival process in legacy 3GPP initial access schemes while considering 3000 initial access attempts at an average load of 20.

Mobile Network Operators (MNOs) are considering 3rd Generation Partnership Project (3GPP) Systems (including 5G system) to interwork with Wireless Local Area Network (WLAN; also referred as WiFi) as a cost-effective way to expand the wireless user data traffic capacity further. Achieving adequate level of security from WLAN is one of the main challenges to be addressed, from the 3GPP system perspective, to have effective interworking with the WLAN. Preventing User Equipment (UE) tracking and protecting subscriber's privacy is considered to be crucial requirement in the 3GPP systems, where as in WLAN it is never been considered as an important issue. Hence, combination of WLAN permanent identity and exposure of the 3GPP system permanent identity in the same context in the interworking scenario is identified to be a serious threat for user's privacy and for launching subscriber specific targeted attacks in the 3GPP network. A network harmonized security mechanism is needed to perform authorized tracking by the MNO and at the same time, it should prevent exposure of permanent identities to mitigate unauthorized tracking by the eavesdroppers. This paper details the user traceability threat identified in Long-Term Evolution (LTE)-WLAN Interworking (LWI) and proposes novel ideas to mitigate the identified threat by use of 3GPP network Locally administered Randomized Address (LRA) for the UE's WLAN MAC address instead of universally administrated MAC address. The LRA is generated using the 3GPP network assigned pseudonyms, so that the user's privacy (confidentiality of user and device identity) in the interworking scenario is as secure and efficient as the 3GPP systems. Among the detailed novel ideas, the LRA generated using the core network assigned pseudonyms addresses the user's privacy effectively and has less than 1% collision probability.

Flows in software defined networking (SDN) can pass through multiple domains having separate controllers. A domain is interpreted as part of the network topology under a SDN controller. This necessitates negotiation between various domains, to meet the QoS requirements of flows. These QoS negotiations may be static or dynamic. The SDN domains may be wired or wireless. Though, there have been efforts in the past to define inter-domain QoS negotiations for wired networks using SDN, to the best our knowledge, not much headway has been made when both wireless and wired domains are involved. In this paper, we consider a case where flows connect devices passing through a wired and a wireless domain having separate SDN controllers, and propose a novel QoS negotiation mechanism between them. First, we define a generic mechanism to map QoS parameters from one domain to the other. We then, define utilities for both the domains based on the QoS parameters of flows, and model our proposed mechanism as a mixed integer program. We observe that the problem is NP-complete, and propose a branch and bound-based algorithm to maximize the utility of the wireless domain, and evaluate the same for the wired part. Results indicate, as the resources provided to the flows in the wired domain varies dynamically, the wireless domain accordingly modifies the flows, satisfying their minimum/maximum QoS requirements under different scenarios. Conversely, this also means that resources in wired domain get adjusted, when wireless counterpart changes flow parameters based on wireless channel conditions. Further, the results reveal that smaller granularity of increment/decrement steps of QoS parameters satisfy flow requirements efficiently.

Power saving-semipersistent scheduler (PS-SPS) for voice over LTE (VoLTE) traffic was proposed in the downlink of LTE-A cell to reduce the energy consumption of the eNodeB. PS-SPS introduces the energy saving ability through a modification of traditional SPS (T-SPS) in allocating downlink Physical Resource Block (PRBs) to VoLTE users. In this paper, we first identify the drawbacks of PS-SPS that might curtail its energy saving capability and also degrade its capacity (maximum number of calls that can be supported simultaneously) compared with T-SPS. We then propose a novel SPS scheduler called enhanced-PS-SPS (E-PS-SPS) to allocate downlink PRBs to VoLTE users more efficiently compared with PS-SPS. Next, we build analytical models to derive expressions for capacity and eNodeB energy consumption for both PS-SPS and E-PS-SPS. Our analytical results show that E-PS-SPS not only outperforms PS-SPS in capacity by a substantial margin, but also considerably improves the energy saving. The analysis results are validated using simulations. Furthermore, owing to the modeling complexity of T-SPS, we bound its performance in terms of PS-SPS and E-PS-SPS through heuristic arguments. Simulation results validate our analytical bounds and also show that the proposed E-PS-SPS outperforms T-SPS also both in capacity and energy consumption, unlike PS-SPS whose capacity is lower than T-SPS.

LTE uses the SC-FDMA radio access technology for its uplink data traffic transmission from the User Equipment (UE) to eNodeB. To the best of our knowledge the uplink MAC scheduling decisions at the eNodeB that have been proposed so far for Small Cell network are mostly based on single parameters like channel awareness, buffer status, or minimal power transmission. In this paper, we propose a novel algorithm to support Quality of Service (QoS) aware uplink scheduling and resource allocation scheme at the small cell eNodeB. The proposed scheme dynamically calculates user weights through utility functions considering the parameters like queuing delay and throughput and does resource allocation based on uplink channel condition as well as Hybrid Automatic Repeat Request (HARQ) retransmission status.. The proposed scheduler is referred to as UQUS (Utility based QoS Uplink Scheduler).The performance of the proposed algorithm is compared with traditional scheduling algorithms such as round robin (RR) and proportionate fairness (PF). The simulation results show that the proposed UQUS mechanism achieves minimum gain of 4 times the video cell throughput and minimum gain of 2 times voip cell throughput compared with RR and PF schedulers.

Machine Type Communication (MTC) is becoming an integral part of the Long Term Evolution - Advanced (LTE-A) cellular network. Challenges arise when some of the MTC devices, due to the nature of their applications, are deployed in low signal locations. As per 3GPP requirements, there is a need for additional coverage enhancement up to 20 dB in comparison with LTE category 1 UE for MTC devices. In the previous works reported till now, Repetition Coding is proposed as an effective technique to achieve the required coverage enhancements at cost of longer decoding time. In low signal conditions where many repetitions are required to build the SNR needed, the decoding delay may be unacceptable. For a LTE-A MTC UE, Physical Broadcast CHannel (PBCH) decoding has a very important role and fast, efficient decoding of PBCH will help to improve the device performance. In this paper, we propose to use well established technique called Reduced Search (RS) Viterbi to improve PBCH decoding performance without compromising the time-to-decode. RS Viterbi technique utilizes a priori knowledge of transmitted bits to reduce the size and complexity of trellis, which in turn also reduces probability of choosing incorrect path, i.e., error. Up to 2.2 dB SNR gain is seen in simulation using the RS Viterbi decoding against the conventional Viterbi decoding, which will contribute in improving the sensitivity of MTC devices for better reachability.

Power efficiency in broadband wireless access networks has emerged as a very important area of research worldwide. 4G wireless standards such as the 3GPP LTE have attempted to address this issue through mechanisms such as Discontinuous Reception (DRX) which can enhance the battery performance in user equipments (UEs) and improve resource utilization at the base station (eNodeB) especially for applications characterized by long periods of inactivity such as the WWW. However, DRX in connected mode has not been optimized for real time applications such as Mobile TV and Video on Demand (VoD) which require strict latency and QoS uarantees. This paper presents a novel mechanism, La VoLTE, based on time series prediction and enhanced eNodeB architecture to determine DRX opportunities during video streaming over Real Time Protocol (RTP) in a TDD-LTE network without compromising the QoS. Through extensive simulations, it is found that the proposed mechanism can result in 30-80 percent power saving over the video transmission duration depending on video data for different video quality and bandwidth requirements.

Power saving in Mobile Wireless Broadband networks is one of the vibrant, important and current areas of research. Mobile WiMAX based on IEEE 802.16e standard provides different Power Saving Modes (PSM) like sleep mode and idle mode to save power in Subscriber Station/Mobile Station(s). The forthcoming IEEE 802.16m standard has extended idle mode with introduction of concept of primary and secondary paging groups with PGLU (Paging Group Location Update) timer for optimization of power saving during paging and location update. In this paper, authors have provided comparative study of power saving due to enhancements in IEEE 802.16m standard with respect to IEEE 802.16e especially in idle mode. In addition to this, authors have proposed a novel idea of Enhanced PGLU (EPGLU) timer to further optimize the paging and location update in 802.16m standard. The simulation results show up to 60 percent decrease in paging signalling overhead and a marginal increase in location update in Mobile Station (MS).

Since mobile devices are equipped with limited battery power, it is essential to have efficient power management mechanisms in mobile broadband networks such as mobile WiMAX that enable always on connectivity and provide high throughputs. In recent times Voice over IP (VoIP) has emerged as an important and dominant application in broadband mobile networks such as WiMAX. VoIP traffic is uniquely characterized by small packets sent regularly at periodic intervals and are bound by strict latency requirements for satisfactory user experience. This paper presents novel mechanisms to achieve enhanced power saving during a VoIP session by exploiting unique characteristics of VoIP traffic in next generation mobile WiMAX networks based on IEEE 802.16m standard. The analytical model and simulation results indicate that proposed methods reduce the average power consumption during a VoIP call by up to 70% compared to the existing IEEE 802.16m draft specifications. Moreover, the simulation results closely match our proposed analytical model.

It has been a challenge to support high speed (above 200 kms/hr - freeways and high speed train) mobile user with broadband data communication. Research community efforts are underway to develop wide area networks (wireless access and optical backbone) to support broadband to high speed vehicular users. ITU-R has proposed the International Mobile Telecommunication-Advanced (IMT-Advanced) technical requirements for supporting such usage scenarios. IEEE 802.16 m based (WiMAX) standard is working to meet the requirements of IMT-Advanced proposal. In this paper we have proposed a novel technology referred as Seamless Wireless internet for Fast Trains (SWiFT). In particular SWiFT architecture relies on a fast handoff mechanism by layer 2 (L2) triggering using a confidence factor (a probabilistic value evaluated by high speed movement and signal strength, to decide handoff). An interface gateway (IGW) that enables interoperability between WLAN (802.11e) and WiMAX 802.16 m is being designed to support the above handoff. Extensive simulation results by NS-2 shows that, SWiFT handoff latency is 52% less than mobile IPv6 (MIPv6) proposed by IETF.

The IEEE 802.11e standard defines the enhanced distributed coordination function (EDCF) to improve the quality of service (QoS) in a wireless local area network (WLAN). The EDCF is a CSMA/CA based protocol, where stations compete for the medium with prioritized contention parameters. Also defined in the 802.11e standard is the polling mode of the hybrid coordination function (HCF - Polling), which is a centralized QoS mechanism. The primary purpose of the 802.11e HCF is to decrease the average queuing delay. The EDCF fails to scale well at high loads due to increase in collisions, while the HCF Polling compromises on throughput to achieve lower delay and has the disadvantage of being centrally controlled. In this paper, we propose an adaptive sniffing based protocol (Sniff and Embark protocol) that works around the deficiencies of the IEEE 802.11e standard. The simulations show that Sniff and Embark protocol outperforms the EDCF in terms of providing higher throughput and lower average delay.