Ahmed Shaharyar Khwaja

Appliance Scheduling Optimization in Smart Home Networks

In this paper, we propose a solution to the problem of scheduling of a smart home appliance operation in a given time range. In addition to power-consuming appliances, we adopt a photovoltaic (PV) panel as a power-producing appliance that acts as a micro-grid. An appliance operation is modeled in terms of uninterruptible sequence phases, given in a load demand profile with a goal of minimizing electricity cost fulfilling duration, energy requirement, and user preference constraints. An optimization algorithm, which can provide a schedule for smart home appliance usage, is proposed based on the mixed-integer programming technique. Simulation results demonstrate the utility of our proposed solution for appliance scheduling. We further show that adding a PV system in the home results in the reduction of electricity bills and the export of energy to the national grid in times when solar energy production is more than the demand of the home.

Joint Admission Control, Mode Selection, and Power Allocation in D2D Communication Systems

Device-to-device (D2D) communications can help in achieving the higher data rate targets in emerging wireless networks. The use of D2D communication imposes certain challenges such as interference with the cellular and D2D users. A well-designed joint admission control, network mode selection, and power allocation technique in a cellular network with D2D capability can improve overall throughput. The proposed technique jointly maximizes the total throughput and number of admitted users in cellular networks under quality-of-service (QoS) and interference constraints. The joint admission control, mode selection, and power allocation problem (JACMSPA) falls into a class of mixed-integer nonlinear constraint optimization problems that are generally NP-hard. Due to the combinatorial nature of the problem, its optimal solution needs exhaustive search of integer variables whose complexity increases exponentially with the number of user pairs. In this paper, we invoke outer approximation approach (OAA)-based linearization technique to solve the JACMSPA. The proposed method gives guaranteed ε-optimal solution with reasonable computational complexity. Simulation results verify the effectiveness of the proposed approach method.

Compressed Sensing ISAR Reconstruction in the Presence of Rotational Acceleration

In this paper, we present an inverse synthetic aperture radar (ISAR) reconstruction method from compressively sensed data using a new dictionary that takes into account rotational acceleration. Unlike traditional compressed sensing (CS) ISAR imaging methods, where the dictionary either ignores this acceleration or assumes the scatterers as static, our method can deal with maneuvering motion consisting of rotational acceleration. The method can also focus images when data are not acquired in a continuous frame. The effectiveness of the method is demonstrated by analysis. Simulation examples verify this analysis and show that the presented method can focus data consisting of scatterers undergoing rotational acceleration.

Green Cooperative Cognitive Radio: A Multiobjective Optimization Paradigm

In this paper, we apply the cross-entropy optimization (CEO) to the problem of joint multiple relay assignment and source/relay power allocation in green cooperative cognitive radio (GCCR) networks. We use shared-band amplify-and-forward relaying for cooperative communication in this problem. The proposed joint multiple relay assignment and source/relay power allocation jointly performs relay assignment and power allocation in GCCR while optimizing two conflicting objectives: The first one is to maximize the total rate, and the second one is to minimize the greenhouse gas emissions in GCCR networks. This multiobjective optimization problem is a nonconvex combinatorial optimization problem and is NP-hard. We use a Monte-Carlo-based CEO algorithm to solve this nonconvex problem. The CEO has a simplistic model, and its robustness in avoiding local minima/maxima makes it a suitable candidate for solving complex combinatorial optimization problems. We present simulation results that verify the effectiveness of the proposed CEO method for joint multiple relay assignment and source/relay power allocation.

Compressed sensing based image formation of SAR/ISAR data in presence of basis mismatch

This paper examines compressed sensing (CS) based image formation of synthetic aperture radar (SAR) and inverse synthetic aperture radar (ISAR) data for sparse scenes containing moving targets. We consider basis mismatch for the case when the basis used for reconstruction is different from the actual one in which the reconstructed data are sparse. We use orthogonal matching pursuit (OMP) algorithm for reconstruction and show using simulated data that error between original and reconstructed data increases in presence of basis mismatch. We also show that a certain level of basis mismatch in range velocity, positions and chirp rate is acceptable to achieve reasonable image formation.

An energy-aware load-balanced routing protocol for ad hoc M2M communications

Machine-to-machine (M2M) communications will become ubiquitous in the future Internet of Things, and it is important that current wireless networks are developed to support M2M communications. In this paper, we propose an energy-aware load-balanced routing protocol for ad hoc M2M communications. Routing is a challenging issue in ad hoc M2M communication networks due to a large number of machine-type communication (MTC) devices and a lack of infrastructure. Wireless nodes that are used as MTC devices are powered by batteries only. This makes energy efficiency a major issue as each MTC device in the network acts as a router and consumes energy in the routing process. The energy consumption should be reduced to prolong the lifetime of the batteries. Most existing research on energy-aware routing only focuses on minimising the total energy consumption from the source to the destination device, regardless of the performance degradation caused by the heavy traffic load in the network. The unbalanced traffic load distribution among devices may cause more packet loss and quick battery depletion due to the frequent usage. Unlike existing research, we classify the devices as energy-critical and load-critical devices and protect them from participating in the routing frequently. Simulation results demonstrate that the proposed routing protocol significantly increases the packet delivery ratio, reduces delay and prolongs the network lifetime compared to ad hoc on-demand distance vector and dynamic source routing in the heavy load network. Energy-aware load-balanced can also provide better performance compared with delay-aware MChannel and energy-aware MChannel protocols when devices have very low energy levels in congested networks. Copyright

Performance of Energy-Efficient Cooperative MAC Protocol with Power Backoff in MANETs

This paper presents an energy-efficient cooperative MAC (EECO-MAC) protocol using power control in mobile ad hoc networks. Cooperative communications improve network performance by taking full advantage of the broadcast nature of wireless channels. The power control technique improves the network lifetime by adjusting the transmission power dynamically. We propose the best partnership selection algorithm, which takes energy consumption into consideration for selection of the optimal cooperative helper to join in the transmission. Through exchanging control packets, the optimal transmission power is allocated for senders to transmit data packets to receivers. In order to enhance energy saving, space–time backoff and time–space backoff algorithms are proposed. Simulation results show that EECO-MAC consumes less energy and prolongs the network lifetime compared to IEEE 802.11 DCF and CoopMAC at the cost of delay. Performance improvement offered by our proposed protocol is apparent in congested networks where nodes have low and limited energy.

Pattern-Search-Based Nonconvex Cooperative Sensing in Multiband Cognitive Radio Systems

In this paper, a pattern search (PS)-based solution is proposed for nonconvex multiband cooperative sensing (NCMCS) problem in cognitive radio systems. This problem consists of maximizing cumulative throughput subject to constraints on cumulative interference, probability of detection, and probability of false alarm. Initially in existing literature, this problem was solved under constraints that make it convex. However, removing the conditions for convexity and solving the NCMCS problem have been shown to improve performance. A two-step PS-based solution is presented: The first step uses uniformly distributed random sets of input points to find a solution. The set of points that gives the maximum throughput is chosen as input to the PS algorithm. Numerical examples show the improvement of the proposed method over existing genetic-algorithm-based solution, as well as PS-algorithm-based solution that uses a single set of random points as inputs. The proposed two-step solution gives higher cumulative throughput and is not sensitive to the choice of input, unlike the PS-based solution using a single set of random points as input.

Energy-Efficient Cooperative MAC Protocol Based on Power Control in MANETs

Cooperative communications take full advantage of the broadcast nature of wireless channels and create spatial diversity, thereby achieving tremendous improvement in the network performance. This paper presents an energy-efficient cooperative MAC (EECO-MAC) protocol using cooperative communication and power control techniques in mobile ad hoc networks. The best partnership selection algorithm, which takes energy consumption into consideration is proposed to select the optimal cooperative helper for the cooperative transmission. Through exchanging control packets, the optimal transmission power is allocated for senders to transmit data packets to receivers. In order to reduce the influence induced by interference, space-time back off and time-space back off algorithms are proposed. Simulation results show that EECO-MAC consumes less energy and prolongs the network lifetime compared to IEEE 802.11 DCF and Coop MAC.

Wireless Resource Allocation in Next Generation Healthcare Facilities

Healthcare facilities with intelligent wireless devices can reduce the workload of the paramedic staff. These devices include low-power wireless sensors, personal wireless hub (PWH), and receivers. The PWH can act as a relay in the hospital network. To help the wireless sensor devices, we use multiple PWHs to transfer sensor data to the main central controller. The use of multiple PWHs can increase the performance of the wireless network in the hospital. It also adds reliability to the coverage of the wireless network. In this paper, we propose a framework and low-complexity algorithm for interference aware joint power control and multiple PWH assignment (IAJPCPA) in a hospital building with cognitive radio capability. In the proposed framework, any wireless sensor device can send and receive data from multiple PWHs. The proposed IAJPCPA is a nonconvex mixed integer nonlinear optimization problem, which is generally NP-hard. The main objective of IAJPCPA is to maximize the total transmission data rate by assigning PWHs to the wireless sensor devices under the constraint of acceptable interference to the licensed wireless devices. To this end, we present an efficient PWH assignment and power control scheme for IAJPCPA problem by employing an upper bound on the IAJPCPA that converts the nonconvex problem into a convex optimization problem. Finally, we examine the effect of different system parameters on the performance of the proposed algorithm.