Mahdi Pirmoradian

Implicit enumeration based 0–1 integer programming for generation maintenance scheduling

This paper presents an implicit enumeration based 0-1 integer programming methodology for finding the optimum preventive maintenance schedule of generating units. The objective function is to maintain the units as earlier as possible. Various constraints such as spinning reserve, duration of maintenance and maintenance crew are being taken into account. In a case study, using the power system of the first reference with six generating units, and implying implicit enumeration, we obtain one optimum solution and seven other feasible solutions. Finally with respect to the mentioned reference, we make a conclusion.

Intelligent channel access technique in Cognitive Radio networks

Future networks, especially in the framework of smart cities will be populated with various kinds of equipment accessing wireless communication channels. A much higher device variety will arise, ranging from identifiable objects to notebooks and smart phones. These aspects require high-level intelligent wireless access network. In order to cope with the vast number of technologies (machine-to-machine communications and sensor networks), cognitive radio network will be a key enabling technology. Cognitive Radio (CR) significantly utilizes current static radio frequency bands in an opportunistic manner. In this paper, we propose two intelligent channel access methods; Minimum Collision Technique (MCT) and Maximum Residual Lifetime Technique (MRLT) in CR networks. The proposed techniques are evaluated by average channel utilization and average channel collision on four dedicated channels in a specific period of time (3000ms). The numerical results confirm that the MRLT technique on cognitive radio side approaches more channel utilization and less data transmission collision among users, compared with MCT.

Sensing Optimization in Cooperative Cognitive Radio Networks

Cooperative spectrum sensing is a key function in cognitive radio networks in order to provide unused spectrum access opportunities and mitigate the impact of interference to the primary networks. Cooperative sensing can incur additional cooperation overhead, increased energy consumption, extra sensing time and delay in heterogeneous networks. In this paper, the sensing time period is optimized to minimize energy consumption in a diverse cooperative network using square law combining decision rule. The evaluation results confirm significant improvement in the sensing time and sensing task energy consumption.

Power allocation in cognitive spectrum sharing area using effective capacity in imperfect fading channel

In this paper we propose a power control policy over an imperfect fading channel within a cognitive spectrum sharing area. In particular, our proposed scheme maximizes the secondary user effective capacity subject to the average interference power and the secondary user transmit power constraints. We also investigate the minimization of average interference power at the Primary Receiver (PR) under required effective capacity of the secondary user with respect to imperfect Channel State Information (CSI) between cognitive radio transmitter and the PR link. Furthermore the impact of the Quality of Service (QoS) exponent on effective capacity in imperfect channel is studied. The analytical results reveal that the effective capacity of the Secondary User (SU) under given average interference power and peak power constraints increases due to growing channel state error of the secondary transmitter-primary receiver link. Moreover, results show that cross channel error increases the average interference power at the primary receiver with regards to the changing QoS exponent. The numerical analysis confirms our theoretical results.

Entropy-based opportunistic spectrum access for cognitive radio networks

This paper proposes an opportunistic spectrum decision scheme based on the weighted residual entropy concept for cognitive radio networks. The proposed scheme maximum entropy channel access selects appropriate spectrum opportunities based on the usefulness of the idle-channel remaining lifetime estimated through the weighted residual entropy function for the unoccupied channels. The performance of the proposed spectrum decision scheme is evaluated using a wealth of efficiency metrics, namely channel utilisation, channel collision, spectrum handoff rate and collision probability in perfect and imperfect spectrum sensing environments. The probabilities of primary signal detection and false detection are taken into the proposed spectrum hole selection technique. Despite the increasing probability of false detection, simulation results show that this central spectrum decision scheme greatly improves spectrum utilisation when the stated performance metrics were compared with those of known spectrum decision schemes such as random channel access, first-opportunity channel access and maximum remaining lifetime. Copyright

Radio Spectrum Issues and Cognitive Mobile Computing

The rapid proliferation of mobile wireless devices, astronomical data traffic transmission and development of multifarious technologies has resulted in huge demand for usable radio spectrum bands. Allocation of new spectrum bands and maximizing the usage of currently allocated radio spectrum bands have become of vital importance in emerging mobile computing networks. This chapter highlights the importance and issues of radio spectrum in mobile computing networks and also presents cognitive functionalities as an appropriate solution to cope with the scarcity of usable radio spectrum in emerging cognitive mobile computing networks.

An Efficient Power Control Algorithm for Supporting Cognitive Communications in Shared Spectrum Areas

The concept of Cognitive Radio (CR) is meant to be utilised by both licensed and license-exempt users that coexist in a shared spectrum area whenever they need to avoid causing unaffordable interference to each other by following some rules. In fact, primary users should be protected by any license-exempt transmission. To this end, power control is a pivotal mechanism to be used for interference management in these scenarios. Especially, transmit power control is a vehicle to mitigate interference, in presence of CR technology, when primary receivers are attempting to reach a desired Signal-to Interference Noise Ratio (SINR) level. In this work we assume that a CR network relies on the same spectrum area with a primary network. Our scope is to measure the introduced interference level caused by the CR transmitter and to properly modify its power to allow a legacy user to reach a required SINR according to location of the primary user in presence of interference. A series of results are presented to prove the efficiency of our proposed scheme.

Adaptive Power Control Policy Using Effective Capacity in Spectrum Sharing Area

In this paper, we propose and analyses a power control policy in terms of maximizing effective capacity at physical and link layers under average interference and transmit power constraint of the cognitive transmitter in spectrum sharing area. The quality of service constraint and proposed power policy in physical layer drives the data queue at link layer to maximize the required statistical quality of service (QoS) of the cognitive users. In this work we also take into account the average transmit power constraint and channel state information at both transmitter and receiver sides. The numerical evaluations are confirmed our theoretical results.

Revenue based maintenance scheduling of a GENCO in restructured power systems

In a restructured power system, the problem of maintenance scheduling is different from the traditional centralized power system. This paper is demonstrated how GENCOs (generating companies) in a competitive environment prepare the maintenance schedule of their facilities. Taking into account that in the new structure the main purposes of GENCOs are selling electricity as much as possible and making higher profit, the model is setting up. The model consists of an objective function and related constraints, e.g. maintenance window, generation capacity, load and network flow. We apply the branch-and-bound optimization methodology on a GENCO and finally make a discussion about the simulation results.