In this paper, we develop a new distributed adaptive power control framework for multi-cell OFDM systems based on the game theory. A specific utility function is defined considering the users' achieved average utility per power, i.e., power unit based utility. We solve the subcarrier allocation issue naturally as well as the power control. Each user tries to maximize its utility by adjusting the transmit power on each subcarrier. A Nash equilibrium for the game is shown to exist and the numerical results show that our proposal outperforms the pure water-filling algorithm in terms of efficiency and fairness.

In this paper, we propose an efficient rate and power allocation scheme for multiuser OFDM systems to minimize the total transmit power under the given QoS requirements. We deduce the optimal solution of transmit power minimization problem and develop a suboptimal algorithm with low complexity based on the theoretical analysis. Because of the avoidance of iterative procedure, it is less complex than the existing schemes. The simulation results show that our proposal outperforms the existing schemes and it is very close to the optimal solution.

In general, semi-supervised clustering can outperform unsupervised clustering. Since 2001, pairwise constraints for semi-supervised clustering have been an important paradigm in this field. In this paper, we show that pairwise constraints (ECs) can affect the performance of clustering in certain situations and analyze the reasons for this in detail. To overcome these disadvantages, we first outline some exemplars constraints. Based on these constraints, we then describe a semi-supervised clustering framework, and design an exemplars constraints expectation-maximization algorithm. Finally, standard datasets are selected for experiments, and experimental results are presented, which show that the exemplars constraints outperform the corresponding unsupervised clustering and semi-supervised algorithms based on pairwise constraints.

The quasi-ARX neurofuzzy (Q-ARX-NF) model has shown great approximation ability and usefulness in nonlinear system identification and control. It owns an ARX-like linear structure, and the coefficients are expressed by an incorporated neurofuzzy (InNF) network. However, the Q-ARX-NF model suffers from curse-of-dimensionality problem, because the number of fuzzy rules in the InNF network increases exponentially with input space dimension. It may result in high computational complexity and over-fitting. In this paper, the curse-of-dimensionality is solved in two ways. Firstly, a support vector regression (SVR) based approach is used to reduce computational complexity by a dual form of quadratic programming (QP) optimization, where the solution is independent of input dimensions. Secondly, genetic algorithm (GA) based input selection is applied with a novel fitness evaluation function, and a parsimonious model structure is generated with only important inputs for the InNF network. Mathematical and real system simulations are carried out to demonstrate the effectiveness of the proposed method.

This paper investigates two issues of cellular engineering for cellular systems enhanced with two-hop fixed relay nodes (FRNs): spectrum partitioning and relay positioning, under the assumption of frequency reuse distance being equal to one. A channel-dependent spectrum partitioning scheme is proposed. According to this scheme, the ensemble mean of signal-to-interference-ratio on respective sets of links are taken into account to determine the bandwidths assigned to links connecting base station (BS) and FRNs, those connecting FRNs and mobile terminals (MTs) and those connecting BS and MTs. The proper FRN positioning is formulated as a constraint optimization problem, which tries to maximize the mean user data rate while at the same time ensures in probability 95% users being better served than in conventional cellular systems without relaying. It is demonstrated with computer simulations that FRN positioning has a strong impact on system performance. In addition, when FRNs can communicate with BS over line-of-sight channels the FRN enhanced cellular system with our proposed spectrum partitioning can remarkably outperform that with a known channel-borrowing based scheme and the conventional cellular systems without relaying. Simulation results also show that with proper FRN positioning the proposed spectrum partitioning scheme is robust against the unreliability of links connecting BS and FRNs.