Zain Ali

Achieving energy fairness in multiuser uplink CR transmission

This paper presents energy efficient resource allocation schemes for multi-user cognitive radio networks. The aim is to achieve the fairness in power consumption of different secondary users. A binary integer programming problem is formulated to jointly allocate sub-carriers to users and power loading over different sub-carriers. Energy fairness is achieved subject to individual power constraints at secondary nodes, interference constraint of primary network, and minimum required rate of the secondary system. Dual decomposition based approach is used to find a joint optimization solution. Further, a sub-optimal scheme is also designed where the power is optimized for fixed sub-carrier allocation. Simulation results are presented to evaluate the performance of proposed schemes.

Enhancing physical layer security in AF relay-assisted multicarrier wireless transmission: Enhancing physical layer security in AF relay-assisted multicarrier wireless transmission

In this paper, we study the physical layer security (PLS) problem in the dual hop orthogonal frequency division multiplexing (OFDM) based wireless communication system. First, we consider a single user single relay system and study a joint power optimization problem at the source and relay subject to individual power constraint at the two nodes. The aim is to maximize the end to end secrecy rate with optimal power allocation over different sub-carriers. Later, we consider a more general multi-user multi-relay scenario. Under high SNR approximation for end to end secrecy rate, an optimization problem is formulated to jointly optimize power allocation at the BS, the relay selection, sub-carrier assignment to users and the power loading at each of the relaying node. The target is to maximize the overall security of the system subject to independent power budget limits at each transmitting node and the OFDMA based exclusive sub-carrier allocation constraints. A joint optimization solution is obtained through duality theory. Dual decomposition allows to exploit convex optimization techniques to find the power loading at the source and relay nodes. Further, an optimization for power loading at relaying nodes along with relay selection and sub carrier assignment for the fixed power allocation at the BS is also studied. Lastly, a sub-optimal scheme that explores joint power allocation at all transmitting nodes for the fixed subcarrier allocation and relay assignment is investigated. Finally, simulation results are presented to validate the performance of the proposed schemes.

Resource optimization for dual-hop device to device networks

In this paper, we consider an orthogonal frequency division multiplexing based device to device network. The communication between source and destination is facilitated by a dual-hop transmission under amplify and forward relaying protocol. The sum throughput of the system is maximized with joint optimization over power allocation at each transmitting node and sub-carrier pairing over two hops. A dual decomposition based solution is proposed subject to separate transmit power constraint at each node. Simulation results are presented to validate the performance of the proposed algorithm where the results are compared with the existing works in literature as well as with a sub-optimal power optimization solution.

Optimizing D2D transmission for secure and reliable smart grid communication

Smart grid (SG) has been recognized as a promising solution to manage and distribute electricity in the next generation power systems. The large number of devices in power systems make the wired communication a non feasible solution, thus wireless transmission becomes necessary. However this demands a huge portion of radio spectrum. In this work, we aim to provide the secure and reliable SG communication through an efficient spectrum sharing mechanism. Specifically, we consider an underlay transmission and seek to minimize the interference under complete spectrum reuse while guaranteeing the required secrecy rate as well as end to end delay. A mathematical optimization problem is formulated and convex optimization techniques are exploited to find the near optimal solution. Further a suboptimal solution is also proposed to reduce the computational complexity. Simulation results are presented to verify the effectiveness of the proposed schemes.

On fair interference management in cognitive radio networks

In this paper, we consider power optimization problem in cognitive radio (CR) networks. The aim is to protect the licensed primary users (PUs) from unequal performance degradation by secondary users (SUs). A min-max optimization problem is formulated to minimize the maximum interference subject to transmission power constraint at base station (BS) and the individual interference constraint at each SU. Further, to guarantee the minimum quality of service (QoS) of each SU, a rate constraint per SU is considered in the problem. Based on convex optimization techniques, a step wise approach is adopted where first the sum interference is minimized and later the sum rate is maximized subject to various constraints.