Auon Muhammad Akhtar

Synergistic spectrum sharing in 5G HetNets: A harmonized SDN-enabled approach

Given the anticipated 1000 times growth of tele-traffic, the conception of efficient spectrum management and sharing mechanisms becomes essential for 5G networks due to the scarcity of spectral resources. To meet this ambitious goal, we propose an SDN-based synergistic spectrum sharing technique, the harmonized SDN-enabled approach (HSA), which relies on distributed input reporting on spectrum availabilities in 5G heterogeneous networks. Conventional spectrum sharing mechanisms, particularly those using cognitive radio techniques, rely heavily on spectrum sensing and adaptive transmission-aided communications devices. However, this device-level spectrum sharing might lead to inaccurate sharing decisions due to the widely fluctuating signal quality observed by each device. Moreover, the network becomes vulnerable to malicious devices that report false sensing data to gain unfair access to the spectrum. These problems are further compounded by the fact that operational cellular networks have a somewhat rigid architecture relying on vendor-specific configuration interfaces, hence restricting the operators to have, at best, only indirect control of the networks operation and resources. In addressing these challenges, we adopt a synergistic approach that integrates the distributed sensing devices, cellular base stations, and SDN controller into an intrinsically amalgamated network. To alleviate any potential controller scalability and latency concerns, HSA harmonizes the networks operation by distributing the local decision making and network-wide policy making tasks among the base stations and the SDN controller, respectively. The article outlines the detailed network architecture and also presents an efficient resource management algorithm.

Temporal and spatial correlation based distributed fault detection in wireless sensor networks

Since wireless sensor networks are usually used for long-term monitoring in harsh environments, sensor nodes are vulnerable to faults. Function fault can lead to immediate node breakdown, while data fault makes the node generate erroneous sensor data. Faulty data results in incorrect estimation of the environment and causes unnecessary consumption of the network resources. Therefore, it is necessary to detect faulty data in real time. In this paper, a new distributed fault detection algorithm is proposed, which is based on the temporal and spatial correlation of the sensor data. With the proposed algorithm, faulty data is detected and discarded locally, so that the network resource consumption is minimized and the processing burden of the terminal is reduced. Simulation results show that the proposed algorithm improves detection accuracy, as compared to the baseline distributed fault detection algorithms.

Cooperative ARQ-Based Energy-Efficient Routing in Multihop Wireless Networks

In this paper, we design an integrated protocol that jointly optimizes the performance of the physical, medium access control (MAC), and network layers. Our goal is to minimize total network energy consumption while delivering a minimum required signal-to-noise ratio (SNR) at each intended receiver within the network. At the MAC layer, we develop a cooperative automatic repeat request (ARQ) system, in which the relay nodes assist the source with its retransmission attempts. A complete analytic framework for the cooperative system is developed. Using this framework, we find the optimum transmission energy at the physical layer. To demonstrate the effectiveness of the proposed scheme in minimizing energy consumption, we propose two cooperative routing algorithms at the network layer. The proposed algorithms utilize the derived cooperative link cost as a basic building block. Through analysis and simulations, it is shown that over a single hop, cooperative transmission can achieve energy savings of up to 73%, as compared with noncooperative transmis.sion. The simulation results also demonstrate that the proposed routing algorithms can achieve significant energy savings while using fewer hops, as compared with the baseline cooperative and noncooperative routing algorithms.

Monostatic Airborne SAR Using License Exempt WiMAX Transceivers

The well-established low-cost broadband OFDM based wireless systems in license-exempt bands, including worldwide interoperability for microwave access (WiMAX) systems, have drawn considerable attention for radar related applications over the past decade. This paper explores an idea of utilizing Commercial Off-The-Shelf (COTS) WiMAX base stations (BSs) in unlicensed band for monostatic airborne synthetic aperture radar (SAR) application. The OFDM PHY of the WiMAX base station has been redesigned to meet the requirements of airborne stripmap SAR applications. The pulse repetition frequency (PRF) offered by standard WiMAX BSs can neither satisfy Doppler bandwidth nor expand SAR slant range. To increase PRF, we propose an RF front modification by employing WiMAX BSs together with a microwave double-pole-double-throw (DPDT) switch and two absorbing loads. Further, a standard WiMAX BS receiver can be directly used to acquire raw data of targets. Simulation results show the proposed scheme can significantly increase the range with limited transmission power.

Partial mobile data offloading with load balancing in heterogeneous cellular networks using Software-Defined Networking

The proliferation of mobile services and the explosive growth of data traffic has created new challenges in cellular networks. Mobile data offloading has attracted significant attention, since it has the ability to alleviate cellular burden by using complementary resources and thus, offers better services to end users. In this paper, we introduce intelligence into heterogeneous network management and propose a Software-Defined Networking based module framework, which includes Wi-Fi based partial data offloading and load balancing. Our objective is to make real time decisions for selectively offloading traffic and balancing loads, while taking network conditions and quality of service (QoS) into consideration. The proposed mechanisms are subject to system-level simulations which shows an improvement in load balancing, in terms of equilibrium extent and network stability. We also prove that with the proposed Wi-Fi partial data offloading algorithm, quality of service can be satisfied, while saving a significant amount of cellular resources through smart resource allocation.

Communication Neighbors Comparison in a Poisson Field of Nodes

The statistics of the ratio between the propagation losses of a given node and its i-th and j-th least-propagation-loss neighbors are obtained assuming that the spatial distribution of the neighboring nodes follows a two-dimensional homogeneous Poisson point process. It is shown that these statistics, unlike those for each individual propagation loss, are independent of the environmental fading type as well as the density of the neighbor nodes. The analytical results are validated and illustrated through numerical results and computer simulations. Some applications of the derived statistics are also presented.

Energy-Efficient Scheduling Mechanism for Indoor Wireless Sensor Networks

Energy efficiency is one of the most critical issues in wireless sensor networks, since the sensor nodes are usually battery powered. These energy-constrained sensor nodes are usually densely distributed in indoor environments, which leads to spatially correlated sensor data and low network efficiency. Thus, one way to improve energy efficiency is to reduce the redundancy caused by the correlated data. In this paper, a new sensor scheduling algorithm, based on data correlation, is proposed. The sensor nodes are clustered into groups by a new adaptive dual-metric K-means (DK-means) algorithm. Within each group, the sensor nodes take turns to work as a group representative and transmit data to the sink. Thus, the energy consumed by the redundant transmissions of the correlated sensor data is saved. Performance evaluation of the proposed mechanism is conducted through OPNET simulations. The simulation results show that the adaptive DK-means algorithm significantly improves data reliability, as compared to the adaptive K-means algorithm. Furthermore, this improvement in reliability is achieved with minimal cost in terms of complexity. Finally, it is shown that the proposed sensor scheduling algorithm achieves energy savings of up to 58%, as compared to the baseline ZigBee protocol.

Enhanced WiMAX SAR system equipped with multiple modes

Widespread use of WiMAX systems has lowered the cost of radio units significantly. We previously proposed a low cost single-mode Synthetic Aperture Radar (SAR) system which took advantage of these low-cost WiMAX transceiver units. However, the imaging swath of this system was limited due to the short length of the cyclic prefix (CP) of WiMAX. In this paper, we propose a multi-mode WiMAX SAR to overcome this limitation. Specifically, we first put forward a design of scan-mode WiMAX SAR, which significantly expands the slant range swath for surveillance and imaging applications. Subsequently, spotlight and squint-mode WiMAX SAR are also proposed to enhance imaging quality. Finally, a windowing scheme on reference data at the receiver is proposed to reduce ghost images in the direction of range. The validity of proposed design is confirmed through detailed simulation results.

Secrecy Enhancement via Cooperative Relays in Multi-Hop Communication Systems

This paper proposes using cooperative relays to improve the ergodic secrecy capacity (ESC) of a multi-hop decode-and-forward (DF) relaying system where communication takes place in the presence of multiple non-colluding eavesdroppers. The proposed scheme is based on a recent approach to generate artificial noise in which transmitter of each hop allocates a portion of its power for generating an intentional interference at the eavesdroppers. Under the assumption that the transmitters can only use limited transmit power, a power allocation strategy has been developed which maximizes the secrecy capacity by optimally distributing the power between the original signal and the artificial noise. Since the optimal solution depends on the channel state information (CSI) of the eavesdroppers, which is difficult to obtain in practice, a sub-optimal solution is also presented in which the CSI of the eavesdroppers is not needed.

Adaptive distributed compression technique utilizing intermediate network nodes

Data networks are experiencing an unprecedented growth in traffic resulting in a multitude of challenges including high network congestion, latency, and packet loss rates. These challenges greatly affect the performance of the network and have a drastic impact on the Quality of Service (QoS) for various applications. In order to reduce network congestion and in turn, maintain the desired QoS, an adaptive and distributed compression/decompression scheme is proposed. The proposed scheme performs the compression and decompression processes within the queues of the intermediate routing nodes of a network. The payload of a packet is compressed based on the packet queuing time. The average expected queuing time of packets is determined instantaneously within the intermediate nodes of a network by employing the Pollaczek Khinchin (PK) equation. Using Network Simulator 3 (NS3), the proposed scheme was simulated under different network conditions and compared with non-compressed transmission sessions of different flow rates. The simulation results show a dramatic improvement in network performance. More specifically, the number of lost packets and one way latency are reduced by at least 22.50% and 18%, respectively.