Most receiving antenna arrays suffer from the mutual coupling problem between antenna elements, which can critically influence the performance of the array. In this work, a novel and accurate form of compensation matrix is applied to compensate the mutual coupling in a uniform linear array (ULA). This is achieved by applying a new method based on solving a boundary value problem for the whole ULA. In this method, both self and mutual impedances are exploited in an accurate characterization of mutual impedance matrix which results in a perfect mutual coupling compensation method, and hence a very accurate direction of arrival (DOA) estimation. In the new scheme, the compensation ma- trix is obtained by using the relationship between measured voltage and theoretical coupled voltage based on the MOM. Numerical results show that using DOA estimation algorithms to the decoupled voltage obtained by using this method leads to an excellent performance of DOA estimation with higher accuracy and resolution.
The performance of the multi-input multi-output (MIMO) systems can be improved by spatial modulation. By using spatial modulation, the transmitter can select the best transmit antenna based on the channel variations using channel state information (CSI). Also, the modulation helps the transmitter to select the best modulation level such that the system has the best performance in all situations. Hence, in this paper, two issues are considered including spatial modulation and information modulation selection. For the spatial modulation, an optimal solution for obtaining the probability of selecting antenna is calculated and then Huffman coding is used such that the transmitter can select the best transmit antenna to maximize the channel capacity. For the information modulation, a multi quadrature amplitude modulation (MQAM) strategy is used. In this modulation, the modulation size is changed based on the channel state variations; therefore, the best modu- lation index is used for transmitting data in all channel situations. In simulation results, the optimal method is compared with Huffman mapping. In addition, the effect of modulation on channel capacity and a bit error rate (BER) is shown.
A novel method to improve the performance of the frequency band is cognitive radio that was introduced in 1999. Due to a lot of advantages of the OFDM, adaptive OFDM method, this technique is used in cognitive radio (CR) systems, widely. In adaptive OFDM, transmission rate and power of subcarriers are allocated based on the channel variations to improve the system performance. This paper investigates adaptive resource allocation in the CR systems that are used OFDM technique to transmit data. The aim of this paper is to maximize the achievable transmission rate for the CR system by considering the interference constraint. Although secondary users can be aware form channel information between each other, but in some wireless standards, it is impossible for secondary user to be aware from channel information between itself and a primary user. Therefore, due to practical limitation, statistical interference channel is considered in this paper. This paper introduces a novel suboptimal power allocation algorithm. Also, this paper introduces a novel bit loading algorithm. In the numerical results sections, the performance of our algorithm is compared by optimal and conventional algorithms. Numerical results indicate our algorithm has better performance than conventional algorithms while its complexity is less than optimal algorithm.