Secure Multi-Party Computation (MPC) is a promising privacy-preserving technology to enable multiple trustless parties to compute a function jointly without revealing private inputs to each other. With the fast development of MPC protocols, software implementation, and underlying computation infrastructure, MPC has developed from purely theoretical interest to tangible platform implementations for real-world applications. In this paper, we investigate multiple mechanisms to design efficient MPC algorithms by avoiding costly MPC operations and leveraging parallel operations. In order to speed up database table searching, a machine learning-based approach is proposed to completely avoid equality-check operations, playing the trade-off between efficiency and accuracy. According to our experimental results, a well-designed MPC algorithm could improve performance and scalability significantly, and thus make MPC technology practicable.

We investigate the problem of distributed scheduling and power control for vertical spectrum sharing in spatial-reuse time division multiple access (STDMA) networks. The objective is to minimize the transmission length (in term of time slots) of secondary users (e.g. users in femtocell networks) subject to the interference-limit constraint for primary users (e.g. users in cellular networks) and quality-of-service (QoS) guarantee of secondary users. This problem is known to be NP-complete. We therefore propose a novel distributed two-stage algorithm based on the distributed column generation method to find the near-optimal solution for the transmission schedule. In the first stage, the dual problem corresponding to the transmission length minimization problem subject to the minimum bandwidth requirement of secondary users, called the restricted master problem, is solved to obtain a dual optimal solution at each secondary transmitter. The dual optimal variables are passed to the second stage to solve the pricing problem. The pricing problem here finds a feasible channel access pattern such that the sum of dual optimal variables is greater than 1 subject to the interference constraints for primary users and the signal-to-interference-plus-noise ratio (SINR) constraints for secondary users so that the solution of the master restricted problem can be improved. We also develop a distributed algorithm for solving the pricing problem based on local measurement at each secondary transmitter and a limited number of message exchanges. The proposed algorithm is compared with previously proposed methods and is evaluated in terms of the schedule length and the number of message exchanges.

We investigate the distributed robust transmission scheduling and power control problem in a cognitive spatial-reuse time division multiple access (STDMA) network. In particular, we address the problem of minimizing the transmission length (in terms of time-slots) of the secondary links under their minimum quality-of-service (QoS) requirements without violating the maximum tolerable interference limit for the primary receivers. Traditionally, the joint transmission scheduling and power control problem only considers the average link gains; therefore, QoS violation can occur due to improper power allocation with respect to instantaneous channel gain realization. To overcome this problem of QoS violation, our problem formulation takes the channel gain uncertainty into account. Since an optimal solution cannot be obtained due to the NP-completeness of the problem, we propose a novel distributed two-stage algorithm based on the distributed column generation method to obtain the near-optimal solution for the robust transmission schedules in an ad-hoc cognitive radio network. To demonstrate its relative efficiency, our algorithm is compared with previously proposed algorithms. For the proposed algorithm, we also derive the bounds on the probability of signal-to-interference-plus-noise ratio (SINR) constraint violation and the expected number of additional time-slots required to satisfy the traffic demand requirements of secondary links.

We study the robust transmission scheduling and power control problem for spectrum sharing between secondary and primary users in a spatial reuse time-division multiple access (STDMA) network. The objective is to find a robust minimum-length schedule for secondary users (in terms of time slots) subject to the interference constraints for primary users and the traffic demand of secondary users. We consider the fact that power allocation based on average (or estimated) link gains can be improper since actual link gains can be different from the average link gains. Therefore, transmission of the secondary links may fail and require more time slots. We also consider this demand uncertainty arising from channel gain uncertainty. We propose a column generation-based algorithm to solve the scheduling and power control problem for secondary users. The column generation method breaks the problem down to a restricted master problem and a pricing problem. However, the classical column generation method can have convergence problem due to primal degeneracy. We propose an improved column generation algorithm to stabilize and accelerate the column generation procedure by using the perturbation and exact penalty methods. Furthermore, we propose an efficient heuristic algorithm for the pricing problem based on a greedy algorithm. For the simulation scenario considered in this paper, the proposed stabilized column generation algorithm can obtain the optimal schedules with 18.85% reduction of the number of iterations and 0.29% reduction of the number of time slots. Also, the heuristic algorithm can achieve the optimality with 0.39% of cost penalty but 1.67×10-4times reduction of runtime.

We consider the scheduling and power control problem for spectrum sharing between secondary users and primary users in a spatial reuse time-division multiple access (STDMA) network. The objective is to minimize the transmission length of secondary users in a frame subject to the interference constraints for primary users and the traffic demand of secondary users. The uncertainty of the channel gains is taken into account. Since the power allocation can be improper with respect to the link gain realization, transmissions in the secondary links may fail, and hence, require more time slots. Therefore, traffic demand uncertainty resulting from channel gain variation is also considered. We propose an efficient algorithm based on column generation for robust optimal scheduling and power control for secondary users in presence of channel gain and traffic demand uncertainty. Numerical results show that the proposed algorithm has high computation speed with very low penalty cost when compared to the optimal algorithm. By adjusting the degree of conservatism, we can balance the tradeoff between the robustness and the transmission length of secondary users in a frame.

We propose a robust optimization framework for the multiple-access problem in a hospital environment. The users of e-Health applications (referred to as secondary users) coexist with active and passive medical devices (referred to as primary and protected users, respectively) under uncertainty in the channel (i.e. propagation) conditions. In particular, we design robust transmission scheduling and power control methods for secondary users in multiple spatial reuse time-division multiple access (STDMA) networks. The objective of the optimization framework is to maximize the spectrum utilization of secondary users and minimize their power consumption subject to the electromagnetic interference constraints for primary and protected users. In this framework, we model the channel uncertainty as ellipsoidal uncertainty sets and the transmission scheduling and power control are optimized taking this uncertainty into account. Numerical results show that the proposed framework can achieve robust scheduling and power control against channel variations. By adjusting the robustness parameter (i.e. the degree of conservatism), we can balance the tradeoff between robustness and spectrum utilization.

We study the multiple access problem for e-Health applications (referred to as secondary users) coexisting with medical devices (referred to as primary or protected users) in a hospital environment. In particular, we focus on transmission scheduling and power control of secondary users in multiple spatial reuse time-division multiple access (STDMA) networks. The objective is to maximize the spectrum utilization of secondary users and minimize their power consumption subject to the electromagnetic interference (EMI) constraints for active and passive medical devices and minimum throughput guarantee for secondary users. The multiple access problem is formulated as a dual objective optimization problem which is shown to be NP-complete. We propose a joint scheduling and power control algorithm based on a greedy approach to solve the problem with much lower computational complexity. To this end, an enhanced greedy algorithm is proposed to improve the performance of the greedy algorithm by finding the optimal sequence of secondary users for scheduling. Using extensive simulations, the tradeoff in performance in terms of spectrum utilization, energy consumption, and computational complexity is evaluated for both the algorithms.

Wireless communications technologies can support efficient healthcare services in medical and patient-care environments. However, using wireless communications in a healthcare environment raises two crucial issues. First, the RF transmission can cause electromagnetic interference (EMI) to biomedical devices, which could critically malfunction. Second, the different types of electronic health (e-Health) applications require different quality of service (QoS). In this paper, we introduce an innovative wireless access scheme, called EMI-aware prioritized wireless access, to address these issues. First, the system architecture for the proposed scheme is introduced. Then, an EMI-aware handshaking protocol is proposed for e-Health applications in a hospital environment. This protocol provides safety to the biomedical devices from harmful interference by adapting transmit power of wireless devices based on the EMI constraints. A prioritized wireless access scheme is proposed for channel access by two different types of applications with different priorities. A Markov chain model is presented to study the queuing behavior of the proposed system. Then, this queuing model is used to optimize the performance of the system given the QoS requirements. Finally, the performance of the proposed wireless access scheme is evaluated through extensive simulations.