Space modulation techniques (SMTs) have emerged as promising candidates for spectral-and energy-efficient wireless communication systems since they strike a good balance among error performance, power efficiency, spectrum efficiency, and receiver complexity. In SMTs, the information is not only conveyed by the habitual M-ary signal constellations; rather, it is also conveyed by the indices of the transmit antennas. As such, the indices of the transmit antennas are harnessed in such a manner that they enhance the transmission efficiency compared with the other multiple-input multiple-output opponents. Despite their exceptional advantages, SMTs suffer from a major drawback, which lies in the logarithmic proportion between their achievable data rates and the number of transmit antennas. In this regard, the fully generalized spatial modulation (F-GSM) and the fully quadrature spatial modulation (F-QSM) are proposed in this paper in order to vanquish this controversial drawback. In F-GSM and F-QSM, the transmit antennas used for data transmission are varied from the state in which only one transmit antenna is activated to the state in which multiple/all transmit antennas are activated. Therefore, a linear relationship between the achievable data rates and the number of transmit antennas is acquired. Moreover, a novel mathematical framework for assessing the average bit error rate performance of different SMTs is delineated. The driven mathematical framework is considered as the first major attempt to generalize the analytical analysis of different SMTs. In addition, the receiver's computational complexity of the proposed schemes is obtained and analyzed in terms of the computational complexity of different SMTs. The simulation results substantiate the validity of the analytical analysis conducted throughout the paper, as they are very akin to the obtained analytical formulas.

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II. Bspline Based Wavelet Family In this paper we briefly describe the results of a recent In [7], a Bspline-based semi-orthogonal wavelet family research on how to construct and implement Bspline ' th waveet asi.Nxt,a nvel echiqu baed n uing has been constructed. It has been shown that the mh wavelet basis. Next, a novel technique based on using odrBpieplnma m( i aife h Bspline wavelet basis, is proposed for signal de-noising and image compression. Extensive simulation results, following 2-scale relation have shown that the proposed technique competes very bm (t) E pkbm (2t -k)(1) well with other methods using classical orthogonal and k bi-orthogonal wavelets. Bsplines example are given With a scaling analysis filter P(z), defined as 1 ka r~~+Zi jm

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