Arama Sonuçları

Listeleniyor 1 - 6 / 6
  • Yayın
    Energy harvesting cooperative multiple access channel with data arrivals
    (IEEE, 2016) Gürakan, Berk; Kaya, Onur; Ulukuş, Şennur
    We consider an energy harvesting two user cooperative Gaussian multiple access channel (MAC), where both of the users harvest energy from nature. The data packets arrive intermittently over time. The users overhear each other's transmitted signals and can cooperate by forming common messages. We find the optimal offline transmit power and rate allocation policy that maximize the departure region. We first show that there exists an optimal policy, in which the single user rate constraints in each time slot are tight, yielding a one to one relation between the powers and rates. Then, we formulate the departure region maximization problem as a weighted sum rate maximization in terms of rates only. Next, we propose a sequential convex approximation method to approximate the problem at each step and show that it converges to the optimal solution. Finally, we solve the approximate problems using an inner outer decomposition method. Numerically, we observe that higher data rates can be supported with the same amount of energy.
  • Yayın
    Maximum likelihood blind channel estimation for space-time coding systems
    (Hindawi Publishing Corporation, 2002-05) Çırpan, Hakan Ali; Panayırcı, Erdal; Çekli, Erdinç
    Sophisticated signal processing techniques have to be developed for capacity enhancement of future wireless communication systems, In recent years, space-time coding is proposed to provide significant capacity gains over the traditional communication systems in fading wireless channels. Space-time codes are obtained by combining channel coding, modulation, transmit diversity, and optional receive diversity in order to provide diversity at the receiver and coding gain without sacrificing the bandwidth. In this paper, we consider the problem of blind estimation of space-time coded signals along with the channel parameters. Both conditional and unconditional maximum likelihood approaches are developed and iterative solutions are proposed. The conditional maximum likelihood algorithm is based on iterative least squares with projection whereas the unconditional maximum likelihood approach is developed by means of finite state Markov process modelling. The performance analysis issues of the proposed methods are studied. Finally, some simulation results are presented.
  • Yayın
    MIMO sinyalleri için uzay-zaman blok kodu klasifikasyonu
    (IEEE, 2014-04-26) Turan, Merve; Öner, Mustafa Mengüç; Çırpan, Hakan Ali
    Bilinmeyen haberleşme sinyallerinin gözü kapalı ve işbirliksiz tanınması için geliştirilen teknikler, hem askeri hem de sivil uygulamalarda kullanım bulmuştur. Çok Girdili Çok Çıktılı (MIMO) haberleşme sistemleri, sinyal tanıma sistemleri için üstesinden gelinmesi gereken yeni problemler ortaya koymaktadır. MIMO haberleşmesinde kullanılan uzay zaman kodlarının gözükapalı tanınması bu problemlerin en önemlilerinden biri olarak görülebilir. Bu çalışmada uzay zaman blok kodlanmış sinyal vektörlerinin döngüsel-durağan (cyclostationary) karakteristiklerinin farklı uzay zaman blok kodlarını birbirinden ayırdetmek amacıyla kullanıldığı yenilikçi uzay-zaman kodu tanıma algoritmaları öneriyoruz.
  • Yayın
    Power control in the cognitive cooperative multiple access channel
    (IEEE, 2012) Kaya, Onur; İşleyen, Murat
    We extend several encoding and decoding techniques from cooperative communications framework, to a cognitive radio system consisting of a primary user (PU) and a secondary user (SU), sending their messages to a common receiver. Assuming that the transmitters and the receiver have full channel state information (CSI) collected and distributed by the common receiver, and that the SU knows the PU's codebook, the cooperation is obtained by block Markov superposition coding, and backwards decoding, which yield a causal overlay scenario. We formulate two rate optimization problems with the aim of, (i) maximizing the sum rate of the system, and (ii) maximizing the rate of the secondary user. We obtain the optimal power allocations for both cases, and the resulting rate regions. The power controlled cooperation turns out to be especially useful when maximizing the sum rate of the system, as it gives the PU significant rate rewards for allowing the cognitive transmitter to access its resources.
  • Yayın
    Channel adaptive encoding and decoding strategies and rate regions for the three user cooperative multiple access channel
    (IEEE, 2008) Edemen, Çağatay; Kaya, Onur
    For a cooperative Gaussian multiple access channel (MAC), we propose a new channel adaptive three user cooperation strategy, based on a non-trivial extension of block Markov super-position encoding. We obtain the expressions for the resulting achievable rate region. We demonstrate through simulations that the participation of an extra user in cooperation provides significant rate improvements. The proposed strategy also improves upon our earlier results on the three user cooperative MAC [1], under certain channel conditions.
  • Yayın
    Pilot-aided bayesian MMSE channel estimation for OFDM systems: Algorithm and performance analysis
    (IEEE, 2004) Şenol, Habib; Çırpan, Hakan Ali; Panayırcı, Erdal
    This paper proposes a computationally efficient, pilot-aided minimum mean square error (MMSE) channel estimation algorithm for OFDM systems. The proposed approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and estimates uncorrelated series expansion coefficients. Moreover, optimal rank reduction is achieved in the proposed approach by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We first consider the stochastic Cramer-Rao bound and derive the closed-form expression for the random KL coefficients. We then exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE.