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Samah A. M. Ghanem

Publications and source records attributed to Samah A. M. Ghanem.

15 recordsLinked to original sources
arXiv2025

Flowshop Machine Scheduling: Markov Modeling, Optimal Schedules and Heuristics

Flowshop machine scheduling has been of main interest in several applications where the timing of its processes plays a fundamental role in the utilization of system resources. Addressing the optimal sequencing of the jobs when equivalent failures across machines exist is a decision of particular relevance to the general scheduling problem. Such failures allow for unpredictable time consumption and improper utilization of the machines. Therefore, it is of particular relevance to address the problem with new modeling approaches considering the parallel and sequential components of the manufacturing process under equivalent failure in the jobs at each machine. In this paper, we propose a novel Markov chain to model the N/ M/P/F permutation flowshop. We analyze the time cost encountered due to M consecutive machine equivalent failures in processing N jobs. We derive new closed form expressions of the completion time under such setup. We extend the Markov model into its underlying components, providing another new Markov model with processes that dont encounter failures and compare both systems. We provide new insights on job ordering decision rules and new approaches in a set of proposed algorithms that provide novel optimal and heuristic methods that provides optimal or near optimal schedules. We derive closed form expressions that divide per machine CT and per machine processing and waiting times. Further, we provide a novel scheme that proves intimate connections between such time components and the maximum number of rounds per machine that allows optimal utilization of the machines in one CT.

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arXiv2023

Network Coding Power Control Mechanisms for Time Varying Channels

In this paper, we propose a model for large scale fading channels via markov process. We exploit the channel delay profile and the dependency between channel states via a first order autoregressive model that cast insight to the channel variations under fading and the closed form delay induced. We propose a network-coding structure that can be employed to compensate for the channel variations under fixed power and to the period of zero packet transmissions under adaptive power control. Satellite communications is an application to the model proposed.

cs.IT↗
arXiv2018

MIMO Mutli-Cell Processing: Optimal Precoding and Power Allocation

We investigate the optimal power allocation and optimal precoding for a cluster of two BSs which cooperate to jointly maximize the achievable rate for two users connecting to each BS in a MCP framework. This framework is modeled by a virtual network MIMO channel due to the framework of full cooperation. In particular, due to sharing the CSI and data between the two BSs over the backhaul link. We provide a generalized fixed point equation of the optimal precoder in the asymptotic regimes of the low- and high-snr. We introduce a new iterative approach that leads to a closed-form expression for the optimal precoding matrix in the high-snr regime which is known to be an NP-hard problem. Two MCP distributed algorithms have been introduced, a power allocation algorithm for the UL, and a precoding algorithm for the DL.

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arXiv2018

Network Coded Handover in IEEE 802.11

We propose a network coded handover of a station moving between two IEEE 802.11 access points (AP). To address such novel proposed framework on a small cell WiFi to WiFi AP handoff, we propose a novel model for the Distributed Coordination Function (DCF) of the WiFi IEEE 802.11 with fixed average contention window. We provide a single packet tranmission model which has been extended to N-packets transmission models with and without fragmentation. We also model the N-packet transmission for the uncoded/coded packets broadcast in order to compare the IEEE 802.11 unreliable to reliable coded broadcast with ACK. We analyze the delay over all, unicast and broadcast transmissions, for the scenario considered with a topology with one WiFi AP before the handover. Capitalizing on the set of models and their corresponding mean completion times (delay), we analyze the performance of different mechanisms. Finally, we provide a novel formulation of the Network Coding on the Edge handover when the station is mobile allowing for the derivation of optimal transmission strategies that can define an optimal time, when to switch to the other AP.

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arXiv2017

Generalized I-MMSE for K-User Gaussian Channels

In this paper, we generalize the fundamental relation between the mutual information and the minimum mean squared error (MMSE) by Guo, Shamai, and Verdu [1] to K-User Gaussian channels. We prove that the derivative of the multiuser mutual information with respect to the signal to noise ratio (SNR) is equal to the total MMSE plus a covariance term with respect to the cross correlation of the multiuser input estimates, the channels and the precoding matrices. We shed light that such relation is a generalized I-MMSE with one step lookahead and lookback, applied to the Successive Interference Cancellation (SIC) in the decoding process.

cs.IT↗
arXiv2017

Piggybacking Codes for Network Coding: The High/Low SNR Regime

We propose a piggybacking scheme for network coding where strong source inputs piggyback the weaker ones, a scheme necessary and sufficient to achieve the cut-set upper bound at high/low-snr regime, a new asymptotically optimal operational regime for the multihop Amplify and Forward (AF) networks.

cs.IT↗
arXiv2017

Energy Efficient Adaptive Network Coding Schemes for Satellite Communications

In this paper, we propose novel energy efficient adaptive network coding and modulation schemes for time variant channels. We evaluate such schemes under a realistic channel model for open area environments and Geostationary Earth Orbit (GEO) satellites. Compared to non-adaptive network coding and adaptive rate efficient network-coded schemes for time variant channels, we show that our proposed schemes, through physical layer awareness can be designed to transmit only if a target quality of service (QoS) is achieved. As a result, such schemes can provide remarkable energy savings.

cs.IT↗
arXiv2017

Network Coding Channel Virtualization Schemes for Satellite Multicast Communications

In this paper, we propose two novel schemes to solve the problem of finding a quasi-optimal number of coded packets to multicast to a set of independent wireless receivers suffering different channel conditions. In particular, we propose two network channel virtualization schemes that allow for representing the set of intended receivers in a multicast group to be virtualized as one receiver. Such approach allows for a transmission scheme not only adapted to per-receiver channel variation over time, but to the network-virtualized channel representing all receivers in the multicast group. The first scheme capitalizes on a maximum erasure criterion introduced via the creation of a virtual worst per receiver per slot reference channel of the network. The second scheme capitalizes on a maximum completion time criterion by the use of the worst performing receiver channel as a virtual reference to the network. We apply such schemes to a GEO satellite scenario. We demonstrate the benefits of the proposed schemes comparing them to a per-receiver point-to-point adaptive strategy.

cs.IT↗
arXiv2017

Adaptive Network Coding Schemes for Satellite Communications

In this paper, we propose two novel physical layer aware adaptive network coding and coded modulation schemes for time variant channels. The proposed schemes have been applied to different satellite communications scenarios with different Round Trip Times (RTT). Compared to adaptive network coding, and classical non-adaptive network coding schemes for time variant channels, as benchmarks, the proposed schemes demonstrate that adaptation of packet transmission based on the channel variation and corresponding erasures allows for significant gains in terms of throughput, delay and energy efficiency. We shed light on the trade-off between energy efficiency and delay-throughput gains, demonstrating that conservative adaptive approaches that favors less transmission under high erasures, might cause higher delay and less throughput gains in comparison to non-conservative approaches that favor more transmission to account for high erasures.

cs.IT↗
arXiv2017

Multiuser I-MMSE

In this paper, we generalize the fundamental relation between the derivative of the mutual information and the minimum mean squared error (MMSE) to multiuser setups. We prove that the derivative of the mutual information with respect to the signal to noise ratio (SNR) is equal to the MMSE plus a covariance induced due to the interference, quantified by a term with respect to the cross correlation of the multiuser input estimates, the channels and the precoding matrices. We also derive new relations for the gradient of the conditional and non-conditional mutual information with respect to the MMSE. Capitalizing on the new fundamental relations, we derive closed form expressions of the mutual information for the multiuser channels, particularly the two user multiple access Gaussian channel driven by binary phase shift keying (BPSK) to illustrate and shed light on methods to derive similar expressions for higher level constellations. We capitalize on the new unveiled relation to derive the multiuser MMSE and mutual information in the low-SNR regime.

cs.IT↗
arXiv2016

Network Coding: Connections Between Information Theory And Estimation Theory

In this paper, we prove the existence of fundamental relations between information theory and estimation theory for network-coded flows. When the network is represented by a directed graph G=(V, E) and under the assumption of uncorrelated noise over information flows between the directed links connecting transmitters, switches (relays), and receivers. We unveil that there yet exist closed-form relations for the gradient of the mutual information with respect to different components of the system matrix M. On the one hand, this result opens a new class of problems casting further insights into effects of the network topology, topological changes when nodes are mobile, and the impact of errors and delays in certain links into the network capacity which can be further studied in scenarios where one source multi-sinks multicasts and multi-source multicast where the invertibility and the rank of matrix M plays a significant role in the decoding process and therefore, on the network capacity. On the other hand, it opens further research questions of finding precoding solutions adapted to the network level.

cs.IT↗
arXiv2016

Multi-Cell Processing with Limited Cooperation: A Novel Framework to Timely Designs and Reduced CSI Feedback with General Inputs

We investigate the optimal power allocation and optimal precoding for a multi-cell-processing (MCP) framework with limited cooperation. In particular, we consider two base stations(BSs) which maximize the achievable rate for two users connecting to each BS and sharing channel state information (CSI). We propose a two way channel estimation or prediction process. Such framework has promising outcomes in terms of feedback reduction and acheivable rates moving the system from one with unkown CSI at the transmitter to a system with instantanous CSI at both sides of the communication. We derive new extentions of the fundamental relation between the gradient of the mutual information and the MMSE for the conditional and non-conditional mutual information. Capitalizing on such relations, we provide the optimal power allocation and optimal precoding designs with respect to the estimated channel and MMSE. The designs introduced are optimal for multiple access (MAC) Gaussian coherent time-varying fading channels with general inputs and can be specialized to multiple input multiple output (MIMO) channels by decoding interference. The impact of interference on the capacity is quantified by the gradient of the mutual information with respect to the power, channel, and error covariance of the interferer. We provide two novel distributed MCP algorithms that provide the solutions for the optimal power allocation and optimal precoding for the UL and DL with a two way channel estimation to keep track of the channel variations over blocks of data transmission. Therefore, we provide a novel solution that allows with limited cooperation: a significant reduction in the CSI feedback from the receiver to the transmitter, and timely optimal designs of the precoding and power allocation.

cs.IT↗
arXiv2014

Multiple Access Gaussian Channels with Arbitrary Inputs: Optimal Precoding and Power Allocation

In this paper, we derive new closed-form expressions for the gradient of the mutual information with respect to arbitrary parameters of the two-user multiple access channel (MAC). The derived relations generalize the fundamental relation between the derivative of the mutual information and the minimum mean squared error (MMSE) to multiuser setups. We prove that the derivative of the mutual information with respect to the signal to noise ratio (SNR) is equal to the MMSE plus a covariance induced due to the interference, quantified by a term with respect to the cross correlation of the multiuser input estimates, the channels and the precoding matrices. We also derive new relations for the gradient of the conditional and non-conditional mutual information with respect to the MMSE. Capitalizing on the new fundamental relations, we investigate the linear precoding and power allocation policies that maximize the mutual information for the two-user MAC Gaussian channels with arbitrary input distributions. We show that the optimal design of linear precoders may satisfy a fixed-point equation as a function of the channel and the input constellation under specific setups. We show also that the non-mutual interference in a multiuser setup introduces a term to the gradient of the mutual information which plays a fundamental role in the design of optimal transmission strategies, particularly the optimal precoding and power allocation, and explains the losses in the data rates. Therefore, we provide a novel interpretation of the interference with respect to the channel, power, and input estimates of the main user and the interferer.

cs.IT↗
arXiv2014

Secure Data Transmission in Cooperative Modes: Relay and MAC

Cooperation in clouds provides a promising technique for 5G wireless networks, supporting higher data rates. Security of data transmission over wireless clouds could put constraints on devices; whether to cooperate or not. Therefore, our aim is to provide analytical framework for the security on the physical layer of such setup and to define the constraints embodied with cooperation in small size wireless clouds. In this paper, two legitimate transmitters Alice and John cooperate to increase the reliable transmission rate received by their common legitimate receiver Bob, where one eavesdropper, Eve exists. We provide the achievable secure data transmission rates with cooperative relaying and when no cooperation exists creating a Multiple Access Channel (MAC). The paper considers the analysis of different cooperative scenarios: a cooperative scenario with two relaying devices, a cooperative scenario without relaying, a non-cooperative scenario, and cooperation from one side. We derive analytical expressions for the optimal power allocation that maximizes the achievable secrecy rates for the different set of scenarios where the implication of cooperation on the achievable secrecy rates was analyzed. We propose a distributed algorithm that allows the devices to select whether to cooperate or not and to choose their optimal power allocation based on the cooperation framework selected. Moreover, we defined distance constraints to enforce the benefits of cooperation between devices in a wireless cloud.

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