Conjoint Routing and Resource Allocation in OFDMA-based D2D Wireless Networks

In this paper, we develop a highly efficient twotier technique for jointly optimizing the routes, the subcarrier schedules, th

Optimization of a class of non-convex objectives on the Gaussian MIMO multiple access channel: Algorithm development and convergence analysis

In this paper we develop an algorithm for computing the optimal transmission parameters, which include the transmission covariance, the time-shares and the user-orderings that minimize a particular class of objectives defined over the capacity region of Gaussian multiple antenna multiple access channels. This class includes objectives that are twice-differentiable, non-increasing and convex in the users' rates, but not necessarily convex in the aforementioned transmission par

Polar Code Design for Irregular Multidimensional Constellations

Polar codes, ever since their introduction, have been shown to be very effective for various wireless communication channels. This, together with their relatively low implementation complexity, has made them an attractive coding scheme for wireless communications. Polar codes have been extensively studied for use with binary-input symmetric memoryless channels but little is known about their effectiveness in other channels. In this paper, a novel methodology for designing multilevel polar codes that works effectively with arbitrary multidimensional constellations is presented. In order for this multilevel design to function, a novel set merging algorithm, able to label such constellations, is proposed.We then compare the error rate performance of our design with that of existing schemes and show that we were able to obtain unprecedented results in many cases over the previously known best techniques at relatively low decoding complexity

Joint optimization of the transmit covariance and the relay precoder in general Gaussian amplify-and-forward relay channels

The capacity of the amplify-and-forward (AF) scheme in general full-duplex Gaussian relay channels is achieved by Gaussian codebooks and can be cast as the solution of an optimization problem of the input transmit covariance and the relay precoder. This problem is non-convex. To circumvent this difficulty, the Karush-Kuhn-Tucker (KKT) conditions are used to obtain closed form expressions of the optimal input covariance that corresponds to an arbitrary relay precoder. Using these expressions, it is shown the maximum rate of the AF scheme is achieved by subdiagonal precoders. This observation is used to facilitate the search for the optimal relay precoder, and to show that at high transmit powers, it is optimal for the relay to remain silent and, at low transmit powers, it is optimal to operate in a mode that resembles half-duplex operation

A sufficient convergence condition for the quantized iterative water-filling algorithm

In this paper we derive a sufficient condition under which the iterative water-filling (IWF) algorithm with quantized noise-plus-interference levels is guaranteed to converge and has a unique Nash equilibrium. This condition is shown to approach the corresponding condition for standard IWF when the quantization resolution or the transmission powers are sufficiently high

Grassmannian signalling achieves tight bounds on the ergodic high-SNR capacity of the noncoherent MIMO full-duplex relay channel

This paper considers the ergodic noncoherent capacity of a multiple-input multiple-output frequency-flat block Rayleigh fading full duplex relay channel at high signal-to-noise ratios (SNRs). It is shown that, for these SNRs, restricting the input distribution to be isotropic on a compact Grassmann manifold maximizes an upper bound on the cut-set bound. Furthermore, it is shown that, from a degrees of freedom point of view, no relaying is necessary and Grassmannian signalling at the source achieves the upper bound within an SNR-independent gap. When the source-relay channel is sufficiently stronger than the source-destination and relay-destination channels, it is shown that, with the number of relay transmit antennas appropriately chosen, a Grassmannian decode-And-forward scheme, which is devised herein, achieves the ergodic noncoherent capacity of the relay channel within an approximation gap that goes to zero as the SNR goes to infinity. Closed-form expressions for the optimal number of relay transmit antennas indicate that this number decreases monotonically with the source transmit power

Grassmannian signalling achieves the ergodic high SNR capacity of the non-coherent MIMO relay channel within an SNR-independent gap

This paper considers the ergodic non-coherent capacity of a multiple-input multiple-output frequency-flat block Rayleigh fading relay channel. It is shown that for this channel restricting the input distribution to be isotropic on a compact Grassmann manifold maximizes an upper bound on the cut-set bound at high signal-to-noise ratios (SNRs). Furthermore, Grassmannian signalling at the source achieves this bound within an SNR-independent gap. For moderate-to-high SNRs, a Grassmannian decode-and-forward (DF) relaying scheme is devised, and the optimal signalling dimensionality that minimizes the gap to the upper bound is obtained

On the accuracy of the high SNR approximation of the differential entropy of signals in additive Gaussian noise

One approach for analyzing the high signal-to-noise ratio (SNR) capacity of non-coherent wireless communication systems is to ignore the noise component of the received signal in the computation of its differential entropy. In this paper we consider the error incurred by this approximation when the transmitter and the receiver have one antenna each, and the noise has a Gaussian distribution. For a general instance of this case, we show that the approximation error decays as 1/SNR. In addition, we consider the special instance in which the received signal corresponds to a signal transmitted over a channel with additive Gaussian noise and a Gaussian fading coefficient. For that case, we provide an explicit expression for the second order term of the Taylor series expansion of the differential entropy. To circumvent the difficulty that arises in the direct computation of that term, we invoke Schwartz's inequality to obtain an efficiently computable bound on it, and we provide examples that illustrate the utility of this bound

The ergodic high SNR capacity of the spatially-correlated non-coherent MIMO channel within an SNR-independent gap

The ergodic capacity of spatially-correlated non-coherent multiple-input multiple-output channels is not known. In this paper upper and lower bounds are derived for this capacity at asymptotically high signal-to-noise ratios (SNRs). The bounds are accurate within an approximation error that decays as 1/SNR, and the gap between these bounds depends solely on the signalling dimensions and the condition number of the transmitter correlation matrix. The upper bound on the high SNR ergodic capacity is shown to decrease monotonically with the logarithm of the condition number of the transmitter correlation matrix. Furthermore, the lower bound on this capacity is achieved by input signals in the form of the product of an isotropically distributed random Grassmannian component and a deterministic component comprising the eigenvectors and the inverse of the eigenvalues of the transmitter correlation matrix