In this paper, we propose a highly efficient mobile visual search algorithm. For descriptor extraction process, we propose a low complexity feature detection which utilizes the detected local key points of the coarse octaves to guide the scale space construction and feature detection in the fine octave. The Gaussian and Laplacian operations are skipped for the unimportant area, and thus the computing time is saved. Besides, feature selection is placed before orientation computing to further reduce the complexity of feature detection by pre-discarding some unimportant local points. For the image retrieval process, we design a high-performance reranking method, which merges both the global descriptor matching score and the local descriptor similarity score (LDSS). In the calculating of LDSS, the tf-idf weighted histogram matching is performed to integrate the statistical information of the database. The results show that the proposed highly efficient approach achieves comparable performance with the state-of-the-art for mobile visual search, while the descriptor extraction complexity is largely reduced.

In this letter, we derive a lower bound on the diversity multiplexing tradeoff (DMT) in multiple-input multiple-output (MIMO) nonorthogonal amplify-and-forward (NAF) cooperative channels with resolution-constrained channel state feedback. It is shown that power control based on the feedback improves the DMT performance significantly in contrast to the no-feedback case. For instance, the maximum diversity increase is exponential in K with K-level feedback.

In this letter we investigate the relaying strategies for multihop transmission in wireless networks over Rayleigh fading channels. Theoretical analysis reveals that equally allocating power among all transmitters and placing relays equidistantly on the line between source and destination are optimal in terms of outage capacity. Then equal time duration for the transmission of each hop is also proved to be optimal. Furthermore, the optimum number of hops is also derived and shown to be inversely proportional to the signal-to-noise ratio (SNR). Numerical simulations agree well with the reported theoretical results.

Multi-cell resource allocation under minimum rate request for each user in OFDMA networks is addressed in this paper. Based on Lagrange dual decomposition theory, the joint multi-cell resource allocation problem is decomposed and modeled as a limited-cooperative game, and a distributed multi-cell resource allocation algorithm is thus proposed. Analysis and simulation results show that, compared with non-cooperative iterative water-filling algorithm, the proposed algorithm can remarkably reduce the ICI level and improve overall system performances.

In this letter, a novel power allocation scheme is proposed to improve the outage performance of an amplify-and-forward (AF) cooperative communication network with multiple potential relays under the assumption that only mean channel gains are available at the transmitters. In this scheme, power allocation is studied jointly with a relay selection algorithm which has low computational complexity. Simulation results demonstrate the performance improvement of the proposed scheme in terms of outage behavior.

In this letter, power allocation methods are devised for Amplify-and-Forward (AF) opportunistic relaying systems aiming at minimizing the outage probability. First, we extend the result on outage probability in and develop an approximate expression to simplify the power allocation problem. A corresponding optimization problem is constructed and proved to be convex. Then an iterative numerical method is proposed to find the optimal power allocation factor. We also propose a near-optimal method which can directly calculate the power allocation factor to reduce computational complexity. Numerical results show that the proposed methods have a similar performance with the ideal one, and outperform equal power allocation significantly with little overhead.