Power Allocation with Max–Min and Min–Max Fairness for Cognitive Radio Networks with Imperfect CSI

This paper consider the power allocation strategies in the cognitive radio (CR) system in the presence of channel estimation errors. As the user has different channel condition in CR systems, different amount of power resource is required to meets the QoS request. In order to guarantee the fairness of each CR user, ensure the interference from the primary user and other CR users meet the QoS requirement of the CR user and limit the interference that is caused by CR users on primary user within the range into the level that primary user can tolerate, we proposed some new power allocation schemes. The targets are to minimize the maximum power allocated to CR users, to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all CR users and to minimize the maximum outage probability over all CR users. The first power allocation scheme can be formulated using Geometric Programming (GP). Since GP problem is equivalent to the convex optimization problem, we can obtain the optimal solutions for the first scheme. The latter two power allocation schemes are not GP problems. We propose iterative algorithms to solve them. Simulation results show that proposed schemes can efficiently guarantee the fairness of CR users under the QoS constraint of the primary user and CR users.     

Achieving Max–Min lifetime and fairness with rate allocation for data aggregation in sensor networks

We consider the rate allocation problem for data aggregation in wireless sensor networks with two objectives: (1) maximizing the minimum (Max–Min) lifetime of an aggregation cluster and (2) achieving fairness among all data sources. The two objectives are generally correlated with each other and usually, they cannot be maximized simultaneously. We adopt a lexicographic method to solve this multi-objective programming problem. First, we recursively induce the Max–Min lifetime for the aggregation cluster. Under the given Max–Min lifetime, we then formulate the problem of maximizing fairness as a convex optimization problem, and derive the optimal rate allocation strategy by iterations. We also present low-complexity algorithms that an aggregation cluster can use to determine the Max–Min network lifetime and the fair rate allocation. Our simulation results validate our analytical results and illustrate the effectiveness of the approach.     

Reducing Near–Far Problem in a VDSL Network with Modified IWF Algorithm by Using Adaptive Spectral Mask Yielding Improved Data Rate of Near End Users

Wireless Personal Communications - In contrast to the orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA) was shown to have outstanding performance in terms of spectrum...