ترغب بنشر مسار تعليمي؟ اضغط هنا

Approximate Random Matrix Models for Generalized Fading MIMO Channels

167   0   0.0 ( 0 )
 نشر من قبل Muralikrishnan Srinivasan
 تاريخ النشر 2017
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

Approximate random matrix models for $kappa-mu$ and $eta-mu$ faded multiple input multiple output (MIMO) communication channels are derived in terms of a complex Wishart matrix. The proposed approximation has the least Kullback-Leibler (KL) divergence from the original matrix distribution. The utility of the results are demonstrated in a) computing the average capacity/rate expressions of $kappa-mu$/$eta-mu$ MIMO systems b) computing outage probability (OP) expressions for maximum ratio combining (MRC) for $kappa-mu$/$eta-mu$ faded MIMO channels c) ergodic rate expressions for zero-forcing (ZF) receiver in an uplink single cell massive MIMO scenario with low resolution analog-to-digital converters (ADCs) in the antennas. These approximate expressions are compared with Monte-Carlo simulations and a close match is observed.



قيم البحث

اقرأ أيضاً

In this paper the performance limits and design principles of rateless codes over fading channels are studied. The diversity-multiplexing tradeoff (DMT) is used to analyze the system performance for all possible transmission rates. It is revealed fro m the analysis that the design of such rateless codes follows the design principle of approximately universal codes for parallel multiple-input multiple-output (MIMO) channels, in which each sub-channel is a MIMO channel. More specifically, it is shown that for a single-input single-output (SISO) channel, the previously developed permutation codes of unit length for parallel channels having rate LR can be transformed directly into rateless codes of length L having multiple rate levels (R, 2R, . . ., LR), to achieve the DMT performance limit.
A major performance degrading factor in free space optical communication (FSO) systems is atmospheric turbulence. Spatial diversity techniques provide a promising approach to mitigate turbulence-induced fading. In this paper, we study the error rate performance of FSO links with spatial diversity over atmospheric turbulence channels described by the Double Generalized Gamma distribution which is a new generic statistical model covering all turbulence conditions. We assume intensity modulation/direct detection with on-off keying and present the BER performance of single-input multiple-output (SIMO), multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) FSO systems over this new channel model.
Discrete-time Rayleigh fading multiple-input multiple-output (MIMO) channels are considered, with no channel state information at the transmitter and receiver. The fading is assumed to be correlated in time and independent from antenna to antenna. Pe ak and average transmit power constraints are imposed, either on the sum over antennas, or on each individual antenna. In both cases, an upper bound and an asymptotic lower bound, as the signal-to-noise ratio approaches zero, on the channel capacity are presented. The limit of normalized capacity is identified under the sum power constraints, and, for a subclass of channels, for individual power constraints. These results carry over to a SISO channel with delay spread (i.e. frequency selective fading).
In a typical MIMO radar scenario, transmit nodes transmit orthogonal waveforms, while each receive node performs matched filtering with the known set of transmit waveforms, and forwards the results to the fusion center. Based on the data it receives from multiple antennas, the fusion center formulates a matrix, which, in conjunction with standard array processing schemes, such as MUSIC, leads to target detection and parameter estimation. In MIMO radars with compressive sensing (MIMO-CS), the data matrix is formulated by each receive node forwarding a small number of compressively obtained samples. In this paper, it is shown that under certain conditions, in both sampling cases, the data matrix at the fusion center is low-rank, and thus can be recovered based on knowledge of a small subset of its entries via matrix completion (MC) techniques. Leveraging the low-rank property of that matrix, we propose a new MIMO radar approach, termed, MIMO-MC radar, in which each receive node either performs matched filtering with a small number of randomly selected dictionary waveforms or obtains sub-Nyquist samples of the received signal at random sampling instants, and forwards the results to a fusion center. Based on the received samples, and with knowledge of the sampling scheme, the fusion center partially fills the data matrix and subsequently applies MC techniques to estimate the full matrix. MIMO-MC radars share the advantages of the recently proposed MIMO-CS radars, i.e., high resolution with reduced amounts of data, but unlike MIMO-CS radars do not require grid discretization. The MIMO-MC radar concept is illustrated through a linear uniform array configuration, and its target estimation performance is demonstrated via simulations.
350 - Tobias Koch , Amos Lapidoth 2011
We study channel capacity when a one-bit quantizer is employed at the output of the discrete-time average-power-limited Rayleigh-fading channel. We focus on the low signal-to-noise ratio regime, where communication at very low spectral efficiencies t akes place, as in Spread Spectrum and Ultra-Wideband communications. We demonstrate that, in this regime, the best one-bit quantizer does not reduce the asymptotic capacity of the coherent channel, but it does reduce that of the noncoherent channel.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا