Browsing by Subject "Multipath propagation"

Now showing 1 - 6 of 6

Open Access
Capacity bounds for an ultra-wideband channel model
(IEEE, 2004-10) Arıkan, Erdal
There is an ongoing effort by the IEEE 802.15.3a subcommittee to reach a UWB personal area network standard. We estimate the achievable rates for such networks using a channel model specified by the same group. The analysis of this channel model is of interest in light of recent information-theoretic work on multipath fading channels which show that in order to take full advantage of such channels' capacity the transmitted signals have to be "peaky" in a certain sense. The immense bandwidth of the UWB channel also suggests at first that peaky signals should be used. However, unlike the many other wireless systems where the transmitter energy is limited, in the UWB channel only the power spectral density of the transmitted signal is constrained. As a result, the signal power can grow in proportion to the utilized bandwidth and peaky signals are not needed. © 2004 IEEE.
Open Access
Çok kullanıcılı çok antenli sistemlerde iş birlikli iletim
(IEEE, 2008-04) Yazarel, Y. K.; Aktaş, Defne
Bu çalışmada işbirlikli, çok kullanıcılı, ve çok antenli bir haberleşme sisteminde telsiz erişim terminallerinin en iyi veri iletimi tekniğine ortaklaşa karar vermeleri problemini inceliyoruz. Burada pek çok çalışmadan farklı olarak kullanıcıların bireysel başarım hedefleri ve anten başına iletim gücü kısıtlamaları olduğu durumu ele alıyoruz. Önceki bir çalışmamızda bu kısıtlamalar altında en iyi sonucu bulan döngülü bir algoritma sunmuştuk. Ancak bu algoritma merkezi bir yapıda olduğu için tam anlamıyla dağıtılmış şekilde gerçeklenememektedir. Bununla birlikte basit yaklaşıklıklar kullanarak en iyiye yakın bir başarım sağlayan ve kısıtlı ve yerel veri iletimi ile gerçeklenebilecek etkin bir algoritma öneriyoruz.
Open Access
Compressive sampling and adaptive multipath estimation
(IEEE, 2010) Pilancı, Mert; Arıkan, Orhan
In many signal processing problems such as channel estimation and equalization, the problem reduces to a linear system of equations. In this proceeding we formulate and investigate linear equations systems with sparse perturbations on the coefficient matrix. In a large class of matrices, it is possible to recover the unknowns exactly even if all the data, including the coefficient matrix and observation vector is corrupted. For this aim, we propose an optimization problem and derive its convex relaxation. The numerical results agree with the previous theoretical findings of the authors. The technique is applied to adaptive multipath estimation in cognitive radios and a significant performance improvement is obtained. The fact that rapidly varying channels are sparse in delay and doppler domain enables our technique to maintain reliable communication even far from the channel training intervals. ©2010 IEEE.
Open Access
Detection of sparse targets with structurally perturbed echo dictionaries
(Elsevier, 2013) Guldogan, M. B.; Arıkan, Orhan
In this paper, a novel algorithm is proposed to achieve robust high resolution detection in sparse multipath channels. Currently used sparse reconstruction techniques are not immediately applicable in multipath channel modeling. Performance of standard compressed sensing formulations based on discretization of the multipath channel parameter space degrade significantly when the actual channel parameters deviate from the assumed discrete set of values. To alleviate this off-grid problem, we make use of the particle swarm optimization (PSO) to perturb each grid point that reside in each multipath component cluster. Orthogonal matching pursuit (OMP) is used to reconstruct sparse multipath components in a greedy fashion. Extensive simulation results quantify the performance gain and robustness obtained by the proposed algorithm against the off-grid problem faced in sparse multipath channels.
Open Access
Nondata-aided channel estimation for OFDM systems with space-frequency transmit diversity
(Institute of Electrical and Electronics Engineers, 2006) Cırpan, H. A.; Panayırcı, E.; Doğan, H.
This paper proposes a computationally efficient nondata-aided maximum a posteriori (MAP) channel-estimation algorithm focusing on the space-frequency (SF) transmit diversity orthogonal frequency division multiplexing (OFDM) transmission through frequency-selective channels. The proposed algorithm properly averages out the data sequence and requires a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and estimates the complex channel parameters of each subcarrier iteratively, using the expectation maximization (EM) method. To further reduce the computational complexity of the proposed MAP algorithm, the optimal truncation property of the KL expansion is exploited. The performance of the MAP channel estimator is studied based on the evaluation of the modified Cramer-Rao bound (CRB). Simulation results confirm the proposed theoretical analysis and illustrate that the proposed algorithm is capable of tracking fast fading and improving overall performance. © 2006 IEEE.
Open Access
Recovery of sparse perturbations in Least Squares problems
(IEEE, 2011) Pilanci, M.; Arıkan, Orhan
We show that the exact recovery of sparse perturbations on the coefficient matrix in overdetermined Least Squares problems is possible for a large class of perturbation structures. The well established theory of Compressed Sensing enables us to prove that if the perturbation structure is sufficiently incoherent, then exact or stable recovery can be achieved using linear programming. We derive sufficiency conditions for both exact and stable recovery using known results of ℓ 0/ℓ 1 equivalence. However the problem turns out to be more complicated than the usual setting used in various sparse reconstruction problems. We propose and solve an optimization criterion and its convex relaxation to recover the perturbation and the solution to the Least Squares problem simultaneously. Then we demonstrate with numerical examples that the proposed method is able to recover the perturbation and the unknown exactly with high probability. The performance of the proposed technique is compared in blind identification of sparse multipath channels. © 2011 IEEE.