This paper presents the bit error rate (BER) upper bounds for trellis coded asymmetric 8PSK (TC-A8PSK) system using the Ka-band satellite in the rain fading environment. The probability density function (PDF) for the rain fading random variable can be theoretically derived by assuming that the rain attenuation can be approximated to a log-normal distribution and the rain fading parameters are calculated by using the rain precipitation data from the Crane global model. Furthermore, we analyze the BER upper bounds of TC-A8PSK system according to the number of states in the trellis diagram and the availability of channel state information (CSI). In the past, Divsalar and Simon has analyzed the BER upper bounds of 2-state TCM system in Rician fading channels; however, this paper is the first to analyze the BER upper bounds of TCM system in the rain fading channels. Finally, we summarize the dominant six factors which are closely related to the BER upper bounds of TC-A8PSK satellite system in the rain fading channel as follows: (1) frequency band, (2) rain intensity, (3) elevation angle, (4) bit energy to noise ratio, (5) asymmetric angle, and (6) availability of CSI.

In this paper, we propose a generalized frequency assignment algorithm to minimize the intermodulation products caused by nonlinear amplification in satellite transponder. We also analyze the performance of proposed algorithms in terms of C/IM and execution time. Most of the published algorithms are too restrictive to be applied to the frequency planning of many realistic systems that are usually characterized by multi-level and/or multi-bandwidth. In developing the proposed "TDTI algorithm," we utilized and modified basic concepts of Okinaka's DELINS-INSDEL algorithm to extend its applicability from one-level systems to more general systems. We also propose a modified version of TDTI algorithm called "WTDI-SDELINS" to circumvent the problem of relatively long execution time.

In this paper, low-complexity generalized singular value decomposition (GSVD) based beamforming schemes are proposed for a cognitive radio (CR) network in which multiple secondary users (SUs) with multiple antennas coexist with multiple primary users (PUs). In general, optimal beamforming, which suppresses the interference caused at PUs to below a certain threshold and maximizes the signal-to-interference-plus-noise ratios (SINRs) of multiple SUs simultaneously, requires a complicated iterative optimization process. To overcome the computational complexity, we introduce a signal-to-leakage-plus-noise ratio (SLNR) maximizing beamforming scheme in which the weight can be obtained by using the GSVD algorithm, and does not require any iterations or matrix squaring operations. Here, to satisfy the leakage constraints at PUs, two linear methods, zero forcing (ZF) preprocessing and power allocation, are proposed.

To estimate angle, velocity, and range information of multiple targets jointly in FMCW MIMO radar, two-dimensional (2D) MUSIC with matched filtering and FFT algorithm is proposed. By reformulating the received FMCW signal of the colocated MIMO radar, we exploit 2D MUSIC to estimate the angle and Doppler frequency of multiple targets. Then by using a matched filter together with the estimated angle and Doppler frequency and FFT operation, the range of the target is estimated. To effectively estimate the parameters of multiple targets with large distance differences, we also propose a successive interference cancellation method that uses the orthogonal projection. That is, rather than estimating the multiple target parameters simultaneously using 2D MUSIC, we estimate the target parameters sequentially, in which the parameters of the target having strongest reflected power are estimated first and then, their effect on the received signal is canceled out by using the orthogonal projection. Simulations verify the performance of the proposed algorithm.