Joint power loading of data and pilots in OFDM using imperfect channel state information at the transmitter

Abstract- The search for optimality in the design of channel precoders and training symbols in block processing communication systems is one of paramount importance. Finding the best tradeoff in terms of power distribution between information and pilot symbols for frequency selective channels, when channel estimation via feedback is available, however, has not been fully addressed. In this paper, we solve the problem of finding the optimal power distribution between pilots and data symbols in the mean-square-error (MSE) sense when a delayless error-free channel feedback path is available to the transmitter. The novel approach adaptively designs the optimal precoders and training vectors based on the frequency domain estimates of the channel

Orthonormal Realization Of Fast Fixed-Order Rls Adaptive Filters

The existing derivations of fast RLS adaptive filters are dependent on the shift structure in the input regression vectors. This structure arises when a tapped-delay line (FIR) filter is used as a modeling filter. In this paper, we show, unlike what original derivations may suggest, that fast fixed-order RLS adaptive algorithms are not limited to FIR filter structures. We show that fast recursions in both explicit and array forms exist for more general data structures, such as orthonormally-based models. One of the benefits of working with an orthonormal basis is that fewer parameters can be used to model long impulse responses. 1

Orthonormal realization of fast fixed-order RLS adaptive filters

The existing derivations of fast RLS adaptive filters are dependent on the shift structure in the input regression vectors. This structure arises when a tapped-delay line (FIR) filter is used as a modeling filter. In this paper, we show, unlike what original derivations may suggest that fast fixed-order RLS adaptive algorithms are not limited to FIR filter structures. We show that fast recursions in both explicit and array forms exist for more general data structures, such as orthononnally-based models. One of the benefits of working with an orthonormal basis is that fewer parameters can be used to model long impulse responses

RLS-Laguerre lattice adaptive filtering: error-feedback, normalized, and array-based algorithms

This paper develops several lattice structures for RLS-Laguerre adaptive filtering including a posteriori and a priori based lattice filters with error-feedback, array-based lattice filters, and normalized lattice filters. All structures are efficient in that their computational cost is proportional to the number of taps, albeit some structures require more multiplications or divisions than others. The performance of all filters, however, can differ under practical considerations, such as finite-precision effects and regularization. Simulations are included to illustrate these facts

Fast RLS Laguerre adaptive filtering

The existing derivations of conventional fast RLS adaptive filters are intrinsically dependent on the shift structure in the input regression vectors. This structure arises when a tapped-delay line (FIR) filter is used as a modeling filter. In this paper, we show that a more general data structure is induced by other filter implementations, such as Laguerre-based filters and, more importantly, that an exact fast RLS algorithm can still be derived for such Laguerre-induced data structures.One of the benefits of working with a Laguerre basis is that fewer parameters can be used to model long impulse responses

Block trigonometric transform adaptive filtering

Frequency-domain implementations improve the computational efficiency and the convergence rate of adaptive schemes. This paper develops frequency-domain adaptive structures that are based on the trigonometric transforms DCT and DST. The structures involve only real arithmetic and efficient algorithms exist for computing these transforms. The new filters are derived by first presenting a derivation for the classical DFT-based filter that allows us to pursue these extensions very immediately

Exact RLS Laguerre-lattice adaptive filtering

This paper solves the problem of designing an exact RLS lattice (or order-recursive) algorithms for adaptive filters that do not involve tapped-delay-line structures. As a special case, an exact RLS Laguerre lattice filter is obtained