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In this paper we consider signal detection in cognitive radio networks, under a non-parametric, multi-sensor detection scenario, and compare the cases of known and unknown noise level. The analysis is focused on two eigenvalue-based methods, namely Roy's largest root test, which requires knowledge of the noise variance, and the generalized likelihood ratio test, which can be interpreted as a test...
In this work the problem of non-cooperative resource optimization in the uplink of a relay-assisted MIMO MAC system with partial CSI at the transmitter is addressed. Each multiple access user pursues individual rate maximization, whereas the relay designs its amplify-and-forward matrix in order to optimize the system's sum-rate. From a game-theoretic perspective, the resource allocation process is...
We present a new MIMO precoding scheme using the LDL^H channel decomposition. The proposed method is verified to have lower complexity and better bit error rate (BER) performance than that of the conventional singular value decomposition (SVD). SVD is commonly used in decomposing the MIMO channel into parallel eigen-modes. However, the large variation of the singular values often leads to ill-conditioned...
The problem of positioning an unknown target is studied for a cooperative wireless sensor network using hybrid two-way time-of-arrival and time-difference-of-arrival measurements. A maximum likelihood estimator (MLE) can be employed to solve the problem. Due to the non-linear nature of the cost function in the MLE, a numerical method, e.g., an iterative search algorithm with a good initial point,...
In this paper, we consider channel estimation for amplify-and-forward (AF) relay network with orthogonal frequency division multiplexing (OFDM) modulation. We propose a superimposed training strategy at relay that allows the destination node to obtain the separate channel information of the source-->relay link and the relay-->destination link. The proposed training strategy only requires two...
A low-complexity, effective detection method for multiple-input multiple-output (MIMO) systems based on eigenspace search and linear equalization-based detection schemes is proposed in this paper. Based on the observation that solutions yielded by linear detectors are corrupted by color noise, the proposed method introduces a new constellation search procedure to augment linear detectors. Specifically,...
This paper investigates the optimum source transmission strategy to maximize the capacity of a multiple-input single-output (MISO) amplify-and-forward relay channel, assuming source-relay channel mean feedback at the source. The challenge here is that relaying introduces a nonconvex structure in the objective function, thereby excluding the possible use of previous methods dealing with mean feedback...
We address the Primary User (PU) detection (spectrum sensing) problem, relevant to cognitive radio, from a finite random matrix theoretical (RMT) perspective. Specifically, we employ recently-derived closed-form and exact expressions for the distribution of the standard condition number (SCN) of uncorrelated and semi-correlated random dual Wishart matrices of finite sizes, to design Hypothesis-Testing...
In this paper, we consider a bit-interleaved coded spatial multiplexing MIMO communication system over a frequency-selective MIMO channel. We present a factor-graph-based derivation of two different equalization algorithms. To this end, we propose a cycle-free factor graph representation of the equalizer, to which we apply the sum-product algorithm (SPA). By using different message representations...
Downlink multi user multiple input multiple output (MU-MIMO) systems are of increasing importance in current and upcoming wireless applications. The improvement in data rates offered by such systems depends on the design of precoding schemes for the broadcast channel (BC) which is their theoretical generalization. A precoding scheme based on generalized decision feedback equalizer (GDFE) is known...
In this paper, we investigate the interference mitigation from a cross-layer perspective for a cognitive radio (CR) multiple-input multiple-output (MIMO) network coexisting with a primary time-division-duplexing (TDD) system. The channel allocation in the media access control (MAC) layer and a subspace-based precoding scheme in the physical layer of the CR network are jointly considered to minimise...
In this paper, we present a thorough investigation on the impact of spatial smoothing and forward-backward averaging techniques for subspace-based channel estimation. The spatial smoothing technique requires the selection of a window size, which, if not selected properly, leads to dramatically performance breakdown of the subspace-based methods. We aim to provide an explanation of the performance...
We investigate multiple-input multiple-output broadcast channel with channel distribution information at the transmitter. We consider the fading-paper model with Nt transmit and Nr receive antennas. Near-optimal methods for designing the inflation factor matrix (choice of auxiliary random variable) to maximize the linear assignment capacity in a general fading channel model are proposed. Further,...
Free probability theory as a main branch of random matrix theory is a valuable tool for describing the asymptotic behavior of multiple systems, especially for those with large random matrices. But classical freeness results mainly focus on random matrices with independent and identically distributed (i.i.d.) entries. In this paper, by using the latest research results of random Vandermonde matrix...
In this paper, we consider the tracking of mobile terminals based on the received signal strength (RSS) measured from several base stations. The spatial correlation of the random shadowing is exploited in order to improve the position tracking. We define an auto-regressive (AR) model of the temporal evolution of the shadowing. This model allows for performing a joint tracking of the position and the...
Dynamic spectrum access has emerged as a promising paradigm for improving the Dynamic spectrum utilization efficiency of wireless networks. To enable this new paradigm, fast and accurate spectrum sensing has to be performed over very wide bandwidth in noisy channel environments under energy constraints. Cyclic feature based sensing approach works well under noise uncertainty, but requires very high...
The capacity optimization problem of MIMO links with interference has attracted an increasing interest. Due to the nonconvexity of the capacity problem, only suboptimal solutions can be found. In the previous works, a Gradient Projection (GP) algorithm [1] and a Quasi-Newton (QN) method [2] were proposed to provide suboptimal solutions subject to the constant power constraint. In this paper, we derive...
This paper proposes a constrained iterative optimal approach to estimate traffic matrix, namely all origin-destination traffic, in a large-scale backbone network. Based on the modified principal component analysis method, we denote traffic matrix estimation problem into an iterative optimal process under the constraints followed by it. In each iterative step, the covariance matrix of traffic matrix...
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