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We consider the target tracking problem using range-only measurements. Unlike the existing tracking methods, which are based on the minimum mean square errors (MMSE) criterion, we propose a maximum a posteriori (MAP) estimation method. Owing to the fact that the posterior density is multi-modal, we use a mixture of Gaussian distributions to approximate it to reduce the approximation errors using single-modal distributions. To obtain the initial distribution, we divide the initial angle estimate range to obtain a series of Gaussian distributions. Due to this, we name the proposed method as “angle-parameterized MAP” (APMAP) method. Simulation results show that the proposed method is a good trade-off between performance and computational complexity. [ABSTRACT FROM PUBLISHER]

In this paper, an improved blind spectrum sensing algorithm which exploits primary signal correlation is investigated based on actual Digital Video Broadcasting (DTV) signal measurements. There is trade-off between the effectiveness and the complexity of spectrum sensing algorithms. Compared with the covariance absolute value (CAV) detection, the proposed one has better performance and almost the same computational complexity. [ABSTRACT FROM PUBLISHER]

Several multiantenna based spectrum sensing detectors have been presented for overcoming noise uncertainty by exploiting antenna correlation. However, these detectors degrade seriously when the antenna correlation is low or the noises through antennas are correlated (i.e. spatial colored noise), and even fail to perform sensing when primary signals through antennas are uncorrelated (i.e., antenna uncorrelation). In order to address this issue, in this paper, we present a Friedman test based spectrum sensing detector which compares the power of the received signals through antennas and hence it needs no priori information of the noise and the primary signal. In addition, the decision threshold level of the presented detector is not related to the number of samples, but related only to the number of antennas and the required false alarm probability. Finally, the performance of the proposal is verified by numerical simulations. [ABSTRACT FROM PUBLISHER]

In this paper, we study adaptive resource allocation algorithm in multi-relay-enhanced OFDMA systems and propose new relay selection and subcarrier allocation schemes. Previous works only focused the traditional optimization problem with total power constraints in the base station (BS) and each relay station (RS). While in our results, we introduce a new proportional constraint which denotes different quantity of service (QoS) of different service. We approach this problem using max-min method based on average power allocation (APA). Simulation results show that the proposed schemes perform well. [ABSTRACT FROM PUBLISHER]