arXiv subjects

Yahya H. Ezzeldin

Publications and source records attributed to Yahya H. Ezzeldin.

25 records · Page 2Linked to original sources

arXiv2017

Efficiently Finding Simple Schedules in Gaussian Half-Duplex Relay Line Networks

The problem of operating a Gaussian Half-Duplex (HD) relay network optimally is challenging due to the exponential number of listen/transmit network states that need to be considered. Recent results have shown that, for the class of Gaussian HD networks with N relays, there always exists a simple schedule, i.e., with at most N +1 active states, that is sufficient for approximate (i.e., up to a constant gap) capacity characterization. This paper investigates how to efficiently find such a simple schedule over line networks. Towards this end, a polynomial-time algorithm is designed and proved to output a simple schedule that achieves the approximate capacity. The key ingredient of the algorithm is to leverage similarities between network states in HD and edge coloring in a graph. It is also shown that the algorithm allows to derive a closed-form expression for the approximate capacity of the Gaussian line network that can be evaluated distributively and in linear time. Additionally, it is shown using this closed-form that the problem of Half-Duplex routing is NP-Hard.

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arXiv2017

Communication vs Distributed Computation: an alternative trade-off curve

In this paper, we revisit the communication vs. distributed computing trade-off, studied within the framework of MapReduce in [1]. An implicit assumption in the aforementioned work is that each server performs all possible computations on all the files stored in its memory. Our starting observation is that, if servers can compute only the intermediate values they need, then storage constraints do not directly imply computation constraints. We examine how this affects the communication-computation trade-off and suggest that the trade-off be studied with a predetermined storage constraint. We then proceed to examine the case where servers need to perform computationally intensive tasks, and may not have sufficient time to perform all computations required by the scheme in [1]. Given a threshold that limits the computational load, we derive a lower bound on the associated communication load, and propose a heuristic scheme that achieves in some cases the lower bound.

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arXiv2016

Consistency in the face of change: an adaptive approach to physical layer cooperation

Most existing works on physical-layer (PHY) cooperation (beyond routing) focus on how to best use a given, static relay network--while wireless networks are anything but static. In this paper, we pose a different set of questions: given that we have multiple devices within range, which relay(s) do we use for PHY cooperation, to maintain a consistent target performance? How can we efficiently adapt, as network conditions change? And how important is it, in terms of performance, to adapt? Although adapting to the best path when routing is a well understood problem, how to do so over PHY cooperation networks is an open question. Our contributions are: (1) We demonstrate via theoretical evaluation, a diminishing returns trend as the number of deployed relays increases. (2) Using a simple algorithm based on network metrics, we efficiently select the sub-network to use at any given time to maintain a target reliability. (3) When streaming video from Netflix, we experimentally show (using measurements from a WARP radio testbed employing DIQIF relaying) that our adaptive PHY cooperation scheme provides a throughput gain of 2x over nonadaptive PHY schemes, and a gain of 6x over genie-aided IP-level adaptive routing.

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arXiv2016

A Note on Antenna Selection in Gaussian MIMO Channels: Capacity Guarantees and Bounds

We consider the problem of selecting $k_t \times k_r$ antennas from a Gaussian MIMO channel with $n_t \times n_r$ antennas, where $k_t \leq n_t$ and $k_r \leq n_r$. We prove the following two results that hold universally, in the sense that they do not depend on the channel coefficients: (i) The capacity of the best $k_t \times k_r$ subchannel is always lower bounded by a fraction $\frac{k_t k_r}{n_t n_r}$ of the full capacity (with $n_t \times n_r$ antennas). This bound is tight as the channel coefficients diminish in magnitude. (ii) There always exists a selection of $k_t \times k_r$ antennas (including the best) that achieves a fraction greater than $\frac{\min(k_t ,k_r)}{\min(n_t,n_r)}$ of the full capacity within an additive constant that is independent of the coefficients in the channel matrix. The key mathematical idea that allows us to derive these universal bounds is to directly relate the determinants of principle sub-matrices of a Hermitian matrix to the determinant of the entire matrix.

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arXiv2016

Wireless Network Simplification : Beyond Diamond Networks

We consider an arbitrary layered Gaussian relay network with $L$ layers of $N$ relays each, from which we select subnetworks with $K$ relays per layer. We prove that: (i) For arbitrary $L, N$ and $K = 1$, there always exists a subnetwork that approximately achieves $\frac{2}{(L-1)N + 4}$ $\left(\mbox{resp.}\frac{2}{LN+2}\right)$ of the network capacity for odd $L$ (resp. even $L$), (ii) For $L = 2, N = 3, K = 2$, there always exists a subnetwork that approximately achieves $\frac{1}{2}$ of the network capacity. We also provide example networks where even the best subnetworks achieve exactly these fractions (up to additive gaps). Along the way, we derive some results on MIMO antenna selection and capacity decomposition that may also be of independent interest.

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arXiv2013

Sparse Reconstruction-based Detection of Spatial Dimension Holes in Cognitive Radio Networks

In this paper, we investigate a spectrum sensing algorithm for detecting spatial dimension holes in Multiple Inputs Multiple Outputs (MIMO) transmissions for OFDM systems using Compressive Sensing (CS) tools. This extends the energy detector to allow for detecting transmission opportunities even if the band is already energy filled. We show that the task described above is not performed efficiently by regular MIMO decoders (such as MMSE decoder) due to possible sparsity in the transmit signal. Since CS reconstruction tools take into account the sparsity order of the signal, they are more efficient in detecting the activity of the users. Building on successful activity detection by the CS detector, we show that the use of a CS-aided MMSE decoders yields better performance rather than using either CS-based or MMSE decoders separately. Simulations are conducted to verify the gains from using CS detector for Primary user activity detection and the performance gain in using CS-aided MMSE decoders for decoding the PU information for future relaying.

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arXiv2013

Pseudo-Lattice Treatment for Subspace Aligned Interference Signals

For multi-input multi-output (MIMO) K-user interference networks, we propose the use of a channel transformation technique for joint detection of the useful and interference signals in an interference alignment scenario. We coin our detection technique as "pseudo-lattice treatment" and show that applying our technique, we can alleviate limitations facing Lattice Interference Alignment (L-IA). We show that for a 3-user interference network, two of the users can have their interference aligned in lattice structure through precoding. For the remaining user, performance gains in decoding subspace interference aligned signals at the receiver are achieved using our channel transformation technique. Our "pseudo-lattice" technique can also be applied at all users in case of Subspace Interference Alignment (S-IA). We investigate different solutions for applying channel transformation at the third receiver and evaluate performance for these techniques. Simulations are conducted to show the performance gain in using our pseudo-lattice method over other decoding techniques using different modulation schemes.

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