Predicting Performance of Channel Assignments in Wireless Mesh Networks through Statistical Interference Estimation

Wireless Mesh Network (WMN) deployments are poised to reduce the reliance on wired infrastructure especially with the advent of the multi-radio multi-channel (MRMC) WMN architecture. But the benefits that MRMC WMNs offer viz., augmented network capacity, uninterrupted connectivity and reduced latency, are depreciated by the detrimental effect of prevalent interference. Interference mitigation is thus a prime objective in WMN deployments. It is often accomplished through prudent channel allocation (CA) schemes which minimize the adverse impact of interference and enhance the network performance. However, a multitude of CA schemes have been proposed in research literature and absence of a CA performance prediction metric, which could aid in the selection of an efficient CA scheme for a given WMN, is often felt. In this work, we offer a fresh characterization of the interference endemic in wireless networks. We then propose a reliable CA performance prediction metric, which employs a statistical interference estimation approach. We carry out a rigorous quantitative assessment of the proposed metric by validating its CA performance predictions with experimental results, recorded from extensive simulations run on an ns-3 802.11g environment

Radio Co-location Aware Channel Assignments for Interference Mitigation in Wireless Mesh Networks

Designing high performance channel assignment schemes to harness the potential of multi-radio multi-channel deployments in wireless mesh networks (WMNs) is an active research domain. A pragmatic channel assignment approach strives to maximize network capacity by restraining the endemic interference and mitigating its adverse impact on network performance. Interference prevalent in WMNs is multi-faceted, radio co-location interference (RCI) being a crucial aspect that is seldom addressed in research endeavors. In this effort, we propose a set of intelligent channel assignment algorithms, which focus primarily on alleviating the RCI. These graph theoretic schemes are structurally inspired by the spatio-statistical characteristics of interference. We present the theoretical design foundations for each of the proposed algorithms, and demonstrate their potential to significantly enhance network capacity in comparison to some well-known existing schemes. We also demonstrate the adverse impact of radio co- location interference on the network, and the efficacy of the proposed schemes in successfully mitigating it. The experimental results to validate the proposed theoretical notions were obtained by running an exhaustive set of ns-3 simulations in IEEE 802.11g/n environments.Comment: Accepted @ ICACCI-201

On placement and dynamic power control of femtocells in LTE HetNets

Femto cells a.k.a. Low Power Nodes (LPNs) are used to improve indoor data rates as well as to reduce traffic load on macro Base Stations (BSs) in LTE cellular networks. These LPNs are deployed inside office buildings and residential apartment complexes to provide high data rates to indoor Users. With high SINR (Signal-to-Interference plus Noise Ratio) the users experience good throughput, but the SINR decreases significantly because of interference and obstacles such as building walls, present in the communication path. So, efficient placement of Femtos in buildings while considering Macro-Femto interference is very crucial for attaining desirable SINR. At the same time, minimizing the power leakage in order to improve the signal strength of outdoor users in a high interference (HIZone) around the building area is important. In our work, we have considered obstacles (walls, floors) and interference between Macro and Femto BSs. To be fair to both indoor and outdoor users, we designed an efficient placement and power control SON (Self organizing Network) algorithm which optimally places Femtos and dynamically adjusts the transmission power of Femtos based on the occupancy of Macro users in the HIZone. To do this, we solve two Mixed Integer Programming (MIP) methods namely: Minimize number of Femtos (MinNF) method which guarantees threshold SINR (SINRTh) -2dB for all indoor users and optimal Femto power (OptFP) allocation method which guarantees SINRTh (- 4 dB) for indoor users with the Macro users SINR degradation as lesser than 2dB

Optical networking special issue based on selected papers of IEEE ANTS 2015

In Priority-based content processing with Q-routing in Information Centric Networking (ICN), Sibendu Paul, Bitan Banerjee, Amitava Mukherjee and Mrinal K. Naskar address content management issue in a cache with finite storage capability in ICN by proposing an efficient content management policy that changes a router to a self-sustained cache. A novel algorithm based on Q-routing is proposed to determine the order of service for content packets in the buffer of a cache and find next node toward the destination with minimum propagation delay

Reliable Prediction of Channel Assignment Performance in Wireless Mesh Networks

The advancements in wireless mesh networks (WMN), and the surge in multi-radio multi-channel (MRMC) WMN deployments have spawned a multitude of network performance issues. These issues are intricately linked to the adverse impact of endemic interference. Thus, interference mitigation is a primary design objective in WMNs. Interference alleviation is often effected through efficient channel allocation (CA) schemes which fully utilize the potential of MRMC environment and also restrain the detrimental impact of interference. However, numerous CA schemes have been proposed in research literature and there is a lack of CA performance prediction techniques which could assist in choosing a suitable CA for a given WMN. In this work, we propose a reliable interference estimation and CA performance prediction approach. We demonstrate its efficacy by substantiating the CA performance predictions for a given WMN with experimental data obtained through rigorous simulations on an ns-3 802.11g environment.Comment: Accepted in ICACCI-201

Near Optimal Channel Assignment for Interference Mitigation in Wireless Mesh Networks

In multi-radio multi-channel (MRMC) WMNs, interference alleviation is affected through several network design techniques e.g., channel assignment (CA), link scheduling, routing etc., intelligent CA schemes being the most effective tool for interference mitigation. CA in WMNs is an NP-Hard problem, and makes optimality a desired yet elusive goal in real-time deployments which are characterized by fast transmission and switching times and minimal end-to-end latency. The trade-off between optimal performance and minimal response times is often achieved through CA schemes that employ heuristics to propose efficient solutions. WMN configuration and physical layout are also crucial factors which decide network performance, and it has been demonstrated in numerous research works that rectangular/square grid WMNs outperform random or unplanned WMN deployments in terms of network capacity, latency, and network resilience. In this work, we propose a smart heuristic approach to devise a near-optimal CA algorithm for grid WMNs (NOCAG). We demonstrate the efficacy of NOCAG by evaluating its performance against the minimal-interference CA generated through a rudimentary brute-force technique (BFCA), for the same WMN configuration. We assess its ability to mitigate interference both, theoretically (through interference estimation metrics) and experimentally (by running rigorous simulations in NS-3). We demonstrate that the performance of NOCAG is almost as good as the BFCA, at a minimal computational overhead of O(n) compared to the exponential of BFCA

On Supporting Small M2M Data Transmissions in LTE/LTE-A Networks

In Machine-to-Machine (M2M) applications, devices monitor events (e.g., temperature, inventory level), which is relayed through a communication network infrastructure (e.g. Internet, LTE) to an application (software program running on a server connected to the Internet), that translates the monitored event into some meaningful information to be able to take collaborative decisions with limited or no human intervention. With the availability of IPv6 address, it is possible to interconnect everything in this universe. By using the concept of interconnecting things, several applications can be envisioned to make the world smarter. Internet of Things (IoT) is a paradigm whose aim is to implement the concept of interconnection of everything by using all possible technologies and others means. M2M communica- tion is one of the components of Internet of Things (IoT) whose goal is to make the communication smooth and seamless between any two networking enabled devices. According to the researchers by the end of 2014, 1.5 billion devices and by the end of 2020, 20 billion devices will be part of M2M communication

On Improving Data Rates of Users in LTE HetNets

The proliferation of smartphones and tablets has led to huge demand for data services over cellular networks. Cisco VNI mobile forecast (2014-2019) tells that although only 3.9% of mobile connections were Long Term Evolution (LTE) based they accounted for 40% of the mobile traffic and this will rise to 51% by 2019, by which the mobile data usage will grow 11 fold to over 15 Exabytes per month. Reports by Cisco and Huawei tell that 70% of the traffic is generated in indoor environments such as homes, enterprise buildings and hotspots. Hence, it is very important for mobile operators to improve coverage and capacity of indoor environments. Indoor data demand is partly met by intensifying the deployment of Macro Base Stations (MBSs/eNodeBs) in LTE cellular networks. Owing to many obstacles in the communication path between MBS and users inside the building, radio signals attenuate at a faster rate as the distance increases. Thus, Indoor User Equipments (IUEs) receive still low signal strength ( i.e., Signal-to-Noise Ratio, SNR) compared to Outdoor User Equipments (OUEs). To address this problem, one can deploy a large number of Low Power Nodes (LPNs) a.k.a. small cells (e.g., Picos and Femtos) under an umbrella MBS coverage and thereby form an LTE Heterogeneous Network (HetNet). Small cells are mainly being deployed in homes, enterprise buildings and hotspots like shopping malls and airports to improve indoor coverage and data rates. This is a win-win situation as telecom operators also benefit by reduction in their CAPEX and OPEX. Though the deployment of Femtocells improves indoor data rates, the resulting LTE HetNet may face a host of problems like co-tier and cross-tier interference (due to frequency reuse one in LTE) and frequent handovers (due to short coverage areas of Femtocells). Deployment of Femtos inside a building can lead to signal leakage at the edges/corners of the buildings. This causes cross-tier interference and degrades the performance of OUEs in High Interference Zone (HIZone) around the building area, which are connected to one of the MBSs in the LTE HetNet. Arbitrary placement of Femtos can lead to high co-channel cross-tier interference among Femtos and Macro BSs and coverage holes inside buildings. If Femtos are placed without power control, this leads to high power consumption and high inter-cell interference in large scale deployments. Our goal is to address these problems by developing efficient architecture, Femto placement and power control schemes in LTE HetNets. Random or unplanned placement of the Femtos leads to poor SNR and hence affects achievable data rates of IUEs. Hence, placement of Femtos is important for the cellular operators to perform planned deployment of minimum number of Femtos with no coverage holes and guarantee a good signal quality with no co-tier interference. Once the placement of Femtos is done optimally in enterprise environments, operators need to ensure that traffic load is evenly distributed among neighboring Femtos for improving Quality of Service (QoS) of IUEs by efficiently utilizing the network resources. In traditional cellular networks, the uplink access and downlink access of UEs are coupled to the same (Femto) cell. Suppose a Femto is fully loaded when compared to its neighboring Femtos, the traditional offloading or load balancing algorithms will try offloading some of the UEs for both their uplink and downlink access from the loaded cell to one of less loaded neighboring cells (i.e., target cell) provided that these UEs could get connected to the chosen target cell. This type of offloading is a forced handover to reduce traffic imbalance and trigger for handover is not based on better signal strength from the target cell. But, the offloaded UEs are connected for both their uplink and downlink access to the same target cell. Since UEs are most likely separated by walls and floors from their connected cells in enterprise environments, these offloaded UEs now have to transmit with higher transmit power in the uplink and thereby affects their battery lives. In order to reduce the battery drain for the offloaded UEs while maintaining their QoS, we employ the Decoupled Uplink and Downlink (DUD) access method in such a way that, the uplink of UE is connected to the closest Femto while the downlink is connected to a less loaded neighboring Femto. To maximize the utilization of the limited operating spectrum and provide higher data rate for IUEs, operators can configure Femtos in open access mode with frequency reuse one (i.e., all Femtos and MBSs operates on a same frequency) in LTE HetNets. However, this leads to high co-tier interference and cross-tier interference. Another problem in enterprise buildings having Femtos is frequent handovers, that happens when IUEs move from one room/floor to another room/floor inside the building. This leads to degradation of network performance in terms of increased signaling overhead and low throughputs. In order to reduce this kind of unnecessary handovers in enterprise buildings, Femtos should be placed optimally with handover constraints. Hence, we obtain the optimal coordinates from the OptHO model by adding handover constraints to the Minimize Number of Femtos (MinNF) model which guarantees threshold Signal-to-Interference plus Noise Ratio (SINR) of -2 dB for all IUEs inside the building. Such optimized deployment of Femtos reduces the number of handovers while guaranteeing good SINR to all IUEs. In LTE HetNets, even though planned deployment of Femtos in open access mode boosts the IUEs performance, the power leakage from indoor Femtos create interferix ence to the OUEs in the HIZone in the buildings surrounding areas. We propose an efficient placement and power control SON (Self organizing Network) algorithm which optimally places Femtos and dynamically adjusts the transmit power of Femtos based on the occupancy of Macro connected OUEs in the HIZone. To do this, we use the same MinNF model to place the Femtos optimally and solve Optimal Femto Power (OptFP) allocation problem (Mixed Integer Linear Programming (MILP)) which guarantees threshold SINR of -4 dB for IUEs with the Macro users SINR degradation as lesser than 2 dB. In the OptFP model, Femto’s transmit power is tuned dynamically according to the occupancy of OUEs in the HIZone. But the presence of even a single OUE in the HIZone decreases SINR of numerous IUEs, which is not fair to IUEs. In order to address this issue, we propose two solutions a) On improving SINR in LTE HetNets with D2D relays and b) A novel resource allocation and power control mechanism for Hybrid Access Femtos in LTE HetNets, which we describe in the following two paragraphs. To guarantee certain minimum SINR and fairness to both IUEs and OUEs in HIZone, we consider a system model by applying the concept of Device-to-Device (D2D) communication wherein free/idle IUEs connected to Femto act like UE-relays (i.e., UE-like BS, forwarding downlink data plane traffic for some of the HIZone users connected to MBS). We formulate a Mixed-Integer Linear Programming (MILP) optimization model which efficiently establishes D2D pairs between free/idle celledge IUEs and HIZone users by guaranteeing certain SINRT h for both IUEs and HIZone users. As D2D MILP model takes more computation time, it is not usable in real-world scenarios for establishing D2D pairs on the fly. Hence, we propose a two-step D2D heuristic algorithm for establishing D2D pairs. In above works, we assume that Femtos are configured in open access mode. But Hybrid Access Femtocells (HAFs) are favored by the operators because they ensure the paid Subscribed Group (SG) users certain QoS and then try to maximize the system capacity by serving near-by Non Subscribed Group (NSG) users in a best-effort manner. To reap in the benefits of HAFs, the operators need to employ effective resource sharing and scheduling mechanisms to contain co-tier and cross-tier interference arising out of reuse one in the HetNet system. Towards this, we address various challenges in terms of deployment and operation of HAFs in indoor environments. We propose an Optimal Placement of hybrid access Femtos (OPF) model which ensures a certain SINRT h inside the building and a certain SINRT h in the HIZone of the building. Unlike in previous optimization models, in this model, users in HIZone are connected to HAF s deployed inside the building. Also we propose a decentralized Dynamic Bandwidth Allocation (BWA) mechanism which divides the available HAF bandwidth between the two sets of user groups: SG and NSG. In order to mitigate co-tier and cross-tier interference, we then propose a dynamic Optimal Power Control (OPC) mechanism which adjusts the transmit powers of HAFs whenever the users in the HIZone cannot be served by the HAFs. In such a case, HIZone users connect to an MBS instead. Since the OPC problem is hard to solve in polynomial time, we also present a Sub-Optimal Power Control (SOPC) mechanism. To maintain fair resource allocation between SG and NSG users, we propose an Enhanced Priority (EP) scheduling mechanism which employs two schedulers which are based on the Proportional Fair (PF) and the Priority Set (PS) scheduling mechanisms. In above works, placement of Femtos is optimized to reduce co-channel co-tier interference among neighboring Femtos and transmit power of Femtos is optimized to reduce cross-tier interference between MBSs and Femtos. But, for arbitrary deployed Femtos, Inter Cell Interference Coordination (ICIC) techniques could be employed to address co-tier interference problem among Femtos which are connected with each other over X2 interface. Hence, in this work, we propose an ICIC technique, Variable Radius (VR) algorithm which dynamically increases or decreases the cell edge/non-cell edge regions of Femtos and efficiently allocates radio resources among cell edge/non-cell edge regions of Femtos so that the interference between neighboring Femtos can be avoided. We implement the proposed VR algorithm on top of PF scheduler in NS-3 simulator and find that it significantly improves average network throughput when compared to existing techniques in the literature

IP Flow Mobility based Offload in LTE Wi-Fi Interworking Scenario

Mobile data traffic has seen an exponential growth in the past few years with the trend expected to continue. LTE as a standalone cellular network is unable to keep pace with the increasing traffic demands. In the meanwhile, wireless LAN has proven itself as an economical wireless access technology. 3GPP has thus been encouraged to standardize the integration of Wi-Fi networks with LTE. This opens up numerous opportunities to study data offloading and mobility management protocols. One of the newer offloading technique is known as IP Flow Mobility, where individual IP flows are migrated from one network to the other without affecting other flows belonging to the same IP session. In this thesis work, a framework has been developed on ns-3 which supports flow mobility between LTE and Wi-Fi. This framework is based on PMIPv6. This flow mobility framework provides an opportunity to implement various algorithms to decide which network is used to serve which flows while trying maintain a balance between bandwidth utilization and user satisfaction. One such algorithm has been proposed here for a network consisting of LTE and Wi-Fi. This algorithm calculates a quality value for each flow on the network using parameters like flow type, SNR, velocity of the user, etc and tries to offload these flows onto either network based on the flow’s quality value. A simple simulation is carried out which validates the implementation of the framework, where a TCP flow is migrated to a Wi-Fi network from the LTE network based on the SNR of the Wi-Fi network. It also shows how the velocity of a UE affects the percentage of offload which can be achieved and how the flow’s performance is affected by the offload