Tamaghna Acharya

Energy Efficient Cognitive Radio System for Joint Spectrum Sensing and Data Transmission

An energy-efficient cognitive radio system design is suggested that simultaneously meets spectrum sensing reliability and secondary data transmission rate constraints. System model involves co-located multiple amplify-and-forward relays in single cognitive radio source-destination (S-D) environment with a primary focus on optimal relay power allocation strategy. The problem is mathematically formulated as minimization of total energy consumption under the constraints of sensing reliability (in terms of detection and false alarm probabilities), secondary user throughput and interference threshold to primary user. Then a cluster based nonequal relay power allocation is also suggested. Extensive simulation results illustrate the variation of the minimum energy consumption with the key system parameters.

On optimal fuzzy c-means clustering for energy efficient cooperative spectrum sensing in cognitive radio networks

This work explores the scope of Fuzzy C-Means (FCM) clustering on energy detection based cooperative spectrum sensing (CSS) in single primary user (PU) cognitive radio network (CRN). PU signal energy sensed at secondary users (SUs) is forwarded to the fusion center (FC). Two different combining schemes, namely selection combining (SC) and optimal gain combining are performed at FC to address the sensing reliability problem on two different optimization frameworks. In the first work, optimal cluster center points are searched for using differential evolution (DE) algorithm to maximize the probability of detection under the constraint of meeting the probability of false alarm below a predefined threshold. Simulation results highlight the improved sensing reliability compared to the existing works. In the second one, the problem is extended to the energy efficient design of CRN. The SUs act here as amplify-and-forward (AF) relays and PU energy content is measured at the FC over the combined signal from all the SUs. The objective is to minimize the average energy consumption of all SUs while maintaining the predefined sensing constraints. Optimal FCM clustering using DE determines the optimal SU amplifying gain and the optimal number of PU samples. Simulation results shed a light on the performance gain of the proposed approach compared to the existing energy efficient CSS schemes.

Maximum lifetime broadcast communications in cooperative multihop wireless ad hoc networks: Centralized and distributed approaches

Abstract We investigate the problem of broadcast routing in energy constrained stationary wireless ad hoc networks with an aim to maximizing the network lifetime measured as the number of successive broadcast sessions that can be supported. We propose an energy-aware spanning tree construction scheme supporting a broadcast request, considering three different signal transmission schemes in the physical layer: (a) point-to-point, (b) point-to-multipoint, and (c) multipoint-to-point. First we present a centralized algorithm that requires global topology information. Next, we extend this to design an approximate distributed algorithm, assuming the availability of k -hop neighborhood information at each node, with k as a parameter. We prove that the centralized scheme has time complexity polynomial in the number of nodes and the distributed scheme has a message complexity that is linear in the number of nodes. Results of numerical experiments demonstrate significant improvement in network lifetime following our centralized scheme compared to existing prominent non-cooperative broadcasting schemes proposed to solve the same lifetime maximization problem in wireless ad hoc networks. Due to lack of global topology information, the distributed solution does not produce as much advantage as the centralized solution. However, we demonstrate that with increasing value of k , the performance of the distributed scheme also improves significantly.

Energy-Aware Virtual Backbone Tree for Efficient Routing in Wireless Sensor Networks

Virtual backbone has been proposed recently for provisioning an efficient communication infrastructure in energy constrained wireless sensor network. In this paper, a distributed algorithm is proposed for constructing a energy-aware virtual backbone tree (EVBT) for general-purpose communication in wireless sensor network. What distinguishes our algorithm from others is that it chooses only nodes with adequate energy levels (energy level above threshold) as the member of the virtual backbone. Simulation results show that size of the EVBT is always much smaller compared to other prominent schemes. This will greatly reduce the protocol overhead. It also shows that algorithm performs competitively with others in terms total energy consumption for data delivery along the tree. The use of multiple nodes disjoint EVBTs further improves the robustness of the communication infrastructure.

Multiple Disjoint Power Aware Minimum Connected Dominating Sets for Efficient Routing in Wireless Ad Hoc Network

Dominating set based routing is emerging as a promising approach for routing in ad hoc wireless networks. A set is dominating if all the nodes in the network are either in the set or neighbors of nodes in the set. Power aware minimum connected dominating set refers to a minimum connected dominating set where energy levels of all dominator nodes are above a predefined threshold level. Usually, nodes in the connected dominating set consume more energy in order to handle various bypass traffics than nodes outside the set. If we want to prolong the life span of each node in the network by balancing their energy consumption, nodes should be alternated in being chosen to form a connected dominating set. With this objective, a distributed algorithm is presented to construct multiple node-disjoint power aware minimum connected dominating sets, based on our initial proposal for single power aware MCDS. Applying existing prominent multipath routing strategies on this multiple dominating set, we show that the new algorithm yields better results in terms of maximizing routing tasks, minimizing average energy consumption per packet, and enhancing lifetime of each node in the network.

Joint Power Allocation and Routing in Outage Constrained Cognitive Radio Ad Hoc Networks

We investigate the problems of route lifetime maximization and interference to primary user minimization jointly in outage constrained stationary cognitive radio ad hoc networks. It may be noted that although, both lifetime maximization schemes in wireless ad hoc networks (WANETs) and interference minimization schemes in cognitive radio networks mostly aim to minimize transmission power of nodes in a given routing session, using any one of them to achieve both of the said objectives simultaneously does not yield satisfactory performance. In this paper, first, we study both minimum total interference (MTI) and maximum lifetime (ML) routing problems separately as joint power allocation and routing problems. Next closed form expressions for power allocation for both MTI and ML strategies are derived and, from these solutions, we obtain corresponding routing metrics to solve the routing problems. Moreover, closed form expression for a hybrid-ML-MTI power allocation approach is also proposed followed by a new hybrid routing metric. We also present implementation issues related to the proposed hybrid routing and power allocation scheme. Extensive simulation results are used to evaluate performance of our proposed schemes both in regular grid and random networks. Results show that while in grid networks, a straightforward combination of MTI routing with ML power allocation scheme strikes a good balance between interference and lifetime performances, in random networks, our proposed hybrid approach is found to extend lifetime and control interference performances simultaneously in a significant manner.

Energy-Aware Social-Based Multicast in Delay-Tolerant Networks

In Delay-Tolerant Networks (DTNs), nodes forward data opportunistically upon contact because of irregular connectivity and low network-denseness. In this type of networks, energy plays an important role in successful data delivery and enhancement of network lifetime. To address the problem of selecting appropriate relay nodes for data forwarding, recently researchers are using concepts of social networks in the design of DTN routing schemes. This is because of its ability to make forwarding decisions based on the knowledge of long-term and more stable social characteristics of the nodes. In this paper, we propose an energy-aware relay selection scheme to support multiple multicast sessions based on an existing social-based single-data multicast scheme. The proposed scheme selects relays for delivering data to the destinations based on the centrality, one of the important social network characteristics, as well as on the residual energy of the DTN nodes. Our proposed scheme is shown to have polynomial-time complexity. We claim that our scheme supports higher number of multicast sessions thereby maintaining longer lifetime of the network while achieving required data delivery ratio compared to a prominent single-data multicast scheme. Our claim is validated through quantitative performance analysis.

An energy efficient audio compression scheme using wavelet with dynamic difference detection technique in wireless sensor network

The availability of low-cost hardware coupled with the advancement of VLSI (Very Large Scale Integration) technology has promoted the development of wireless multimedia sensor network (WMSN). However, the strict constraints in terms of processing power, storage, bandwidth etc. pose a great challenge to data processing in WMSN. Transmitting raw data is very costly while limited processing power prevents sophisticated multimedia processing. Exploring low-overhead data compression technique is a solution towards this problem. In this paper we propose an energy-saving audio data compression technique for WMSN combining wavelet lifting with a newly proposed difference detection technique. We consider the application domain where data are co-related. To exploit this co-relation we propose to run one wavelet round followed by a dynamic number of difference round and thereby, local communication overhead is saved compared to pure wavelet based scheme without sacrificing the target of sending data with less number of bits to the sink. Moreover, in addition to capturing spatial correlation by wavelet, this scheme captures temporal correlation by introducing the difference detection round. Performance of the proposed scheme is evaluated through simulation where efficacy of the scheme is not only evaluated in terms of energy consumption but also by computing SNR. The scheme is compared with one of the existing schemes. The results confirm our schemes supremacy over the competing scheme both in terms of energy saving and signal reconstruction quality (SNR).

Social-based energy-aware multicasting in delay tolerant networks

In a post-disaster environment, traditional network infrastructure is mostly unavailable due to incidental destruction and damages. In such scenarios, delay/disruption tolerant networking may be considered as an alternative approach to meet the quintessential communication needs between the victims, field workers and centralized authority. In such applications, multicast communication is imperative because rescue and relief messages may often need to be shared among many volunteers. In this paper, we address the problem of relay selection for multicasting single and multiple data items in DTNs considering the application in disaster management. Both the single-data and multiple-data multicast problems are formulated as bi-objective optimization problems under the constraints of target delivery time, buffer space and residual energy levels of relay nodes. Both the problems are shown to be NP-hard. Hence, we propose two heuristic relay selection schemes exploiting social properties in DTNs. Theoretical analysis is performed for energy consumption and exhaustive simulation is carried out to evaluate performance of our proposed schemes in ONE simulator considering real-life data in post-disaster scenarios. Results show that our schemes are energy-saving thereby ensure longer network lifetime compared to other prominent schemes.

Fuzzy C-Means Clustering in Energy Detection for Cooperative Spectrum Sensing in Cognitive Radio System

An energy detection based cooperative spectrum sensing approach using Fuzzy c-means clustering is proposed in this work for cognitive radio system. The objective here is to categorize first the measured PU energy contents into multiple classes to highlight the relative degree in presence or absence of PU and Fuzzy c-means (FCM) algorithm is utilized for this purpose. A soft decision based spectrum sensing is proposed here to categorize the presence or absence of PU in four different classes which then develop individual binary decision functions. Resultant binary decision function is then developed using OR fusion rule. Simulation results highlight that the proposed scheme provides high detection probability at low diversity and less number of samples. The results are further compared with the performance of the conventional energy detector methods to highlight the significance of the proposed scheme.