This paper proposes a novel channel allocation method for multi-cells OFDMA-FDD networks with a reused frequency factor (RFF) of one. The proposed algorithm predicts the co-channel interference (CCI) of active mobile stations (MSs) before allocating suitable subcarriers to a new MS. In order to maintain a desired quality of service (QoS) of the network, only subcarriers having signal-to-interference-plus-noise ratio (SINR) higher than a given threshold SINR min are selected. The simulation results show that the number of sub-carriers which are assigned to MSs increases when decreasing the threshold SINR min , or increasing the number of MSs.

We mainly present the design and implement a mobile vehicle monitoring system using android smartphones.Users can observe the their vehicles' information using a mobile screen anytime, anywhere. Our proposed design is composed of small the GPS/GNSS receiver terminal, modern data acquisition modem, cellular data transmission network, and the smartphone application. We comprehensively discuss the key technologies in terms of hardware and software aspects employed in the system including posible indoor positioning wireless technologies.The designed system in the paper is implemented and tested in practical experiments. Experimental results have proved that the proposed monitoring system is correct and feasible for vehicle owners.

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This paper proposes an efficient and low complexity power-loading algorithm for MIMO-OFDM downlink based cognitive radio system that maximizes the sum rate of single secondary user (SU) under constraints on the tolerable interference thresholds between secondary user and primary user's frequency bands and the total transmission power. Our suboptimal algorithm is based on the 2 nd order interference tracking and nulling mechanism to allocate transmission power of the subcarriers among SU's scheme. The performance of our proposed suboptimal scheme is compared with the performance of the classical power loading algorithms, e.g., water filling, 1 st order interference tracking, nulling, and other suboptimal schemes. Numerical results show that our algorithm has low complexity but obtains a higher channel capacity than that of some previous suboptimal algorithms in some scenarios. We dedicate also that for a given interference threshold, the 2 nd order interference tracking mechanism has dynamic number of nulling position instead fixed number of nulling position.

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