John Tadrous - Academia.edu (original) (raw)

Papers by John Tadrous

The deployment of low earth orbit (LEO) satellites with terrestrial networks can potentially incr... more The deployment of low earth orbit (LEO) satellites with terrestrial networks can potentially increase the efficiency and reduce the cost of relaying content from a data center to a set of edge caches hosted by 6G and beyond enabled macro base stations. In this work, the characteristics of the communication system and the mobility of LEO satellites are thoroughly discussed to describe the channel characteristics of LEO satellites, in terms of their frequency bands, latency, Doppler shifts, fading effects, and satellite access. Three different scenarios are proposed for the relay of data from data centers to edge caches via LEO satellites, which are the "Immediate Forward", "Relay and Forward", and "Store and Forward" scenarios. A comparative problem formulation is utilized to obtain numerical results from simulations to demonstrate the effectiveness and validity as well as the trade-offs of the proposed system model. The simulation results indicate that ...

2018 IEEE International Conference on Communications Workshops (ICC Workshops), 2018

This paper studies the potential of proactive resource allocation to prolong the communication se... more This paper studies the potential of proactive resource allocation to prolong the communication sessions in networks with limited energy budgets and stringent quality-of-service (QoS) requirement, particularly a regular service guarantee. A threshold-based proactive communication policy is proposed to minimize the consumed transmission energy and maximize the network lifetime based on the different link states and the buffer state at the destination node. A closed-form expression is presented for the proactive gain in terms of the channel gain threshold, the amount of the proactively- transmitted data, the QoS requirement, and the channel statistics. The optimal amount of proactively-transmitted data is also provided in closed-form. Finally, corroborated by numerical simulations, the performance of the proposed proactive policy is compared to simple non-proactive communication, as well as non-causal transmission with perfect genie-aided channel knowledge. The presented results show the promising proactivity gains that can be reaped when channel statistics are further taken into account, as compared to legacy myopic approaches which allocate power based solely on instantaneous channel conditions.

An achievable rate region is obtained for a primary multiple access network coexisting with a sec... more An achievable rate region is obtained for a primary multiple access network coexisting with a secondary link of one transmitter and a corresponding receiver. The rate region depicts the sum primary rate versus the secondary rate and is established assuming that the secondary link performs rate-splitting. The achievable rate region is the union of two types of achievable rate regions. The first type is a rate region established assuming that the secondary receiver cannot decode any primary signal, whereas the second is established assuming that the secondary receiver can decode the signal of one primary receiver. The achievable rate region is determined first assuming discrete memoryless channel (DMC) then the results are applied to a Gaussian channel. In the Gaussian channel, the performance of rate-splitting is characterized for the two types of rate regions. Moreover, a necessary and sufficient condition to determine which primary signal that the secondary receiver can decode without degrading the range of primary achievable sum rates is provided. When this condition is satisfied by a certain primary user, the secondary receiver can decode its signal and achieve larger rates without reducing the primary achievable sum rates from the case in which it does not decode any primary signal. It is also shown that, the probability of having at least one primary user satisfying this condition grows with the primary signal to noise ratio.

IEEE/ACM Transactions on Networking

IEEE/ACM Transactions on Networking

2016 IEEE 84th Vehicular Technology Conference (VTC-Fall), 2016

IEEE Transactions on Wireless Communications, 2016

Multiple transmitting antennas can considerably increase the downlink spectral efficiency by beam... more Multiple transmitting antennas can considerably increase the downlink spectral efficiency by beamforming to multiple users at the same time. However, multiuser beamforming requires channel state information (CSI) at the transmitter, which leads to training overhead and reduces overall achievable spectral efficiency. In this paper, we propose and analyze a sequential beamforming strategy that utilizes full-duplex base station to implement downlink data transmission concurrently with CSI acquisition via in-band closed or open loop training. Our results demonstrate that full-duplex capability can improve the spectral efficiency of uni-directional traffic, by leveraging it to reduce the control overhead of CSI estimation. In moderate SNR regimes, we analytically derive tight approximations for the optimal training duration and characterize the associated respective spectral efficiency. We further characterize the enhanced multiplexing gain performance in the high SNR regime. In both regimes, the performance of the proposed full-duplex strategy is compared to the half-duplex counterpart to quantify spectral efficiency improvement. With experimental data [1] and 3D channel model [2] from 3GPP, in a 1.4 MHz 8 × 8 system LTE system with the block length of 500 symbols, the proposed strategy attains a spectral efficiency improvement of 130% and 8% with closed and open loop training, respectively.

2016 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2016

2010 Ieee Global Telecommunications Conference Globecom 2010, 2010

We investigate power allocation for users in a shared spectrum network. In such a network, the pr... more We investigate power allocation for users in a shared spectrum network. In such a network, the primary (licensed) users communicate under a minimum guaranteed quality of service (QoS) requirements, whereas the secondary users opportunistically access the primary band. Our objective is to find a power control scheme that determines the transmit power for both primary and secondary users so that the overall network throughput is maximized while maintaining the quality of service of the primary users greater than a specified minimum limit. In the assumed model, no interference cancellation is done at the receivers resulting in a non-convex optimization problem. It has been shown previously that binary power control almost always achieves the global optimum solution when no QoS constraints are imposed. This is not necessarily the case in our scenario, however. We introduce a distributed algorithm for "ternary" power allocation to be used when individual measurements are available at each node. We show via simulations the relative efficiency of the proposed algorithm compared to previously suggested ones. If a central controller exists with available information about the system parameters, we enhance the performance of the proposed algorithm through an iterative geometric programming (GP) algorithm and prove its convergence to a better solution than ternary power allocation.

2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2015

Mobile data traffic has surpassed that of voice to become the main component of the system load o... more Mobile data traffic has surpassed that of voice to become the main component of the system load of today's wireless networks. Recent studies indicate that the data demand patterns of mobile users are predictable. Moreover, the channel quality of mobile users along their navigation paths is predictable by exploiting their location information. This work aims at fusing the statistically predictable demand and channel patterns in devising proactive caching strategies that alleviate network congestion. Specifically, we establish a fundamental bound on the minimum possible cost achievable by any proactive scheduler under time-invariant demand and channel statistics as a function of their prediction uncertainties, and develop an asymptotically optimal proactive service policy that attains this bound as the prediction window grows. In addition, the established bound yields insights on how the demand and channel statistics affect proactive caching decisions. We reveal some of these insights through numerical investigations.

In this paper, full-duplex radios are used to continuously update the channel state information a... more In this paper, full-duplex radios are used to continuously update the channel state information at the transmitter, which is required to compute the downlink precoding matrix in MIMO broadcast channels. The full-duplex operation allows leveraging channel reciprocity for open-loop uplink training to estimate the downlink channels. However, the uplink transmission of training creates interference at the downlink receiving mobile nodes. We characterize the optimal training resource allocation and its associated spectral efficiency, in the proposed open-loop training based full-duplex system. We also evaluate the performance of the half-duplex counterpart to derive the relative gains of full-duplex training. Despite the existence of inter-node interference due to full-duplex, significant spectral efficiency improvement is attained over half-duplex operation.

2015 49th Asilomar Conference on Signals, Systems and Computers, 2015

Eprint Arxiv 1102 1498, Feb 7, 2011

An achievable rate region is obtained for a primary multiple access network coexisting with a sec... more An achievable rate region is obtained for a primary multiple access network coexisting with a secondary link of one transmitter and a corresponding receiver. The rate region depicts the sum primary rate versus the secondary rate and is established assuming that the secondary link performs rate-splitting. The achievable rate region is the union of two types of achievable rate regions. The first type is a rate region established assuming that the secondary receiver cannot decode any primary signal, whereas the second is established assuming that the secondary receiver can decode the signal of one primary receiver. The achievable rate region is determined first assuming discrete memoryless channel (DMC) then the results are applied to a Gaussian channel. In the Gaussian channel, the performance of rate-splitting is characterized for the two types of rate regions. Moreover, a necessary and sufficient condition to determine which primary signal that the secondary receiver can decode without degrading the range of primary achievable sum rates is provided. When this condition is satisfied by a certain primary user, the secondary receiver can decode its signal and achieve larger rates without reducing the primary achievable sum rates from the case in which it does not decode any primary signal. It is also shown that, the probability of having at least one primary user satisfying this condition grows with the primary signal to noise ratio.

Corr, Feb 8, 2010

We investigate power allocation for users in a spectrum underlay cognitive network. Our objective... more We investigate power allocation for users in a spectrum underlay cognitive network. Our objective is to find a power control scheme that allocates transmit power for both primary and secondary users so that the overall network throughput is maximized while maintaining the quality of service (QoS) of the primary users greater than a certain minimum limit. Since an optimum solution to our problem is computationally intractable, as the optimization problem is non-convex, we propose an iterative algorithm based on sequential geometric programming, that is proved to converge to at least a local optimum solution. We use the proposed algorithm to show how a spectrum underlay network would achieve higher throughput with secondary users operation than with primary users operating alone. Also, we show via simulations that the loss in primary throughput due to the admission of the secondary users is accompanied by a reduction in the total primary transmit power. 1

IEEE/ACM Transactions on Networking, 2015

2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2015

IEEE/ACM Transactions on Networking, 2015

2014 48th Asilomar Conference on Signals, Systems and Computers, 2014

IEEE/ACM Transactions on Networking, 2014

In this work, we propose and study optimal proactive resource allocation and demand shaping for d... more In this work, we propose and study optimal proactive resource allocation and demand shaping for data networks. Motivated by the recent findings on the predictability of human behavior patterns in data networks, and the emergence of highly capable handheld devices, our design aims to smooth out the network traffic over time and minimize the data delivery costs. Our framework utilizes proactive data services as well as smart content recommendation schemes for shaping the demand. Proactive data services take place during the off-peak hours based on a statistical prediction of a demand profile for each user, whereas smart content recommendation assigns modified valuations to data items so as to render the users' demand less uncertain. Hence, our recommendation scheme aims to boost the performance of proactive services within the allowed flexibility of user requirements. We conduct theoretical performance analysis that quantifies the leveraged cost reduction through the proposed framework. We show that the cost reduction scales at the same rate as the cost function scales with the number of users. Further, we prove that demand shaping through smart recommendation strictly reduces the incurred cost even below that of proactive downloads without recommendation.

The deployment of low earth orbit (LEO) satellites with terrestrial networks can potentially incr... more The deployment of low earth orbit (LEO) satellites with terrestrial networks can potentially increase the efficiency and reduce the cost of relaying content from a data center to a set of edge caches hosted by 6G and beyond enabled macro base stations. In this work, the characteristics of the communication system and the mobility of LEO satellites are thoroughly discussed to describe the channel characteristics of LEO satellites, in terms of their frequency bands, latency, Doppler shifts, fading effects, and satellite access. Three different scenarios are proposed for the relay of data from data centers to edge caches via LEO satellites, which are the "Immediate Forward", "Relay and Forward", and "Store and Forward" scenarios. A comparative problem formulation is utilized to obtain numerical results from simulations to demonstrate the effectiveness and validity as well as the trade-offs of the proposed system model. The simulation results indicate that ...

2018 IEEE International Conference on Communications Workshops (ICC Workshops), 2018

This paper studies the potential of proactive resource allocation to prolong the communication se... more This paper studies the potential of proactive resource allocation to prolong the communication sessions in networks with limited energy budgets and stringent quality-of-service (QoS) requirement, particularly a regular service guarantee. A threshold-based proactive communication policy is proposed to minimize the consumed transmission energy and maximize the network lifetime based on the different link states and the buffer state at the destination node. A closed-form expression is presented for the proactive gain in terms of the channel gain threshold, the amount of the proactively- transmitted data, the QoS requirement, and the channel statistics. The optimal amount of proactively-transmitted data is also provided in closed-form. Finally, corroborated by numerical simulations, the performance of the proposed proactive policy is compared to simple non-proactive communication, as well as non-causal transmission with perfect genie-aided channel knowledge. The presented results show the promising proactivity gains that can be reaped when channel statistics are further taken into account, as compared to legacy myopic approaches which allocate power based solely on instantaneous channel conditions.

An achievable rate region is obtained for a primary multiple access network coexisting with a sec... more An achievable rate region is obtained for a primary multiple access network coexisting with a secondary link of one transmitter and a corresponding receiver. The rate region depicts the sum primary rate versus the secondary rate and is established assuming that the secondary link performs rate-splitting. The achievable rate region is the union of two types of achievable rate regions. The first type is a rate region established assuming that the secondary receiver cannot decode any primary signal, whereas the second is established assuming that the secondary receiver can decode the signal of one primary receiver. The achievable rate region is determined first assuming discrete memoryless channel (DMC) then the results are applied to a Gaussian channel. In the Gaussian channel, the performance of rate-splitting is characterized for the two types of rate regions. Moreover, a necessary and sufficient condition to determine which primary signal that the secondary receiver can decode without degrading the range of primary achievable sum rates is provided. When this condition is satisfied by a certain primary user, the secondary receiver can decode its signal and achieve larger rates without reducing the primary achievable sum rates from the case in which it does not decode any primary signal. It is also shown that, the probability of having at least one primary user satisfying this condition grows with the primary signal to noise ratio.

IEEE/ACM Transactions on Networking

IEEE/ACM Transactions on Networking

2016 IEEE 84th Vehicular Technology Conference (VTC-Fall), 2016

IEEE Transactions on Wireless Communications, 2016

Multiple transmitting antennas can considerably increase the downlink spectral efficiency by beam... more Multiple transmitting antennas can considerably increase the downlink spectral efficiency by beamforming to multiple users at the same time. However, multiuser beamforming requires channel state information (CSI) at the transmitter, which leads to training overhead and reduces overall achievable spectral efficiency. In this paper, we propose and analyze a sequential beamforming strategy that utilizes full-duplex base station to implement downlink data transmission concurrently with CSI acquisition via in-band closed or open loop training. Our results demonstrate that full-duplex capability can improve the spectral efficiency of uni-directional traffic, by leveraging it to reduce the control overhead of CSI estimation. In moderate SNR regimes, we analytically derive tight approximations for the optimal training duration and characterize the associated respective spectral efficiency. We further characterize the enhanced multiplexing gain performance in the high SNR regime. In both regimes, the performance of the proposed full-duplex strategy is compared to the half-duplex counterpart to quantify spectral efficiency improvement. With experimental data [1] and 3D channel model [2] from 3GPP, in a 1.4 MHz 8 × 8 system LTE system with the block length of 500 symbols, the proposed strategy attains a spectral efficiency improvement of 130% and 8% with closed and open loop training, respectively.

2016 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2016

2010 Ieee Global Telecommunications Conference Globecom 2010, 2010

We investigate power allocation for users in a shared spectrum network. In such a network, the pr... more We investigate power allocation for users in a shared spectrum network. In such a network, the primary (licensed) users communicate under a minimum guaranteed quality of service (QoS) requirements, whereas the secondary users opportunistically access the primary band. Our objective is to find a power control scheme that determines the transmit power for both primary and secondary users so that the overall network throughput is maximized while maintaining the quality of service of the primary users greater than a specified minimum limit. In the assumed model, no interference cancellation is done at the receivers resulting in a non-convex optimization problem. It has been shown previously that binary power control almost always achieves the global optimum solution when no QoS constraints are imposed. This is not necessarily the case in our scenario, however. We introduce a distributed algorithm for "ternary" power allocation to be used when individual measurements are available at each node. We show via simulations the relative efficiency of the proposed algorithm compared to previously suggested ones. If a central controller exists with available information about the system parameters, we enhance the performance of the proposed algorithm through an iterative geometric programming (GP) algorithm and prove its convergence to a better solution than ternary power allocation.

2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2015

Mobile data traffic has surpassed that of voice to become the main component of the system load o... more Mobile data traffic has surpassed that of voice to become the main component of the system load of today's wireless networks. Recent studies indicate that the data demand patterns of mobile users are predictable. Moreover, the channel quality of mobile users along their navigation paths is predictable by exploiting their location information. This work aims at fusing the statistically predictable demand and channel patterns in devising proactive caching strategies that alleviate network congestion. Specifically, we establish a fundamental bound on the minimum possible cost achievable by any proactive scheduler under time-invariant demand and channel statistics as a function of their prediction uncertainties, and develop an asymptotically optimal proactive service policy that attains this bound as the prediction window grows. In addition, the established bound yields insights on how the demand and channel statistics affect proactive caching decisions. We reveal some of these insights through numerical investigations.

In this paper, full-duplex radios are used to continuously update the channel state information a... more In this paper, full-duplex radios are used to continuously update the channel state information at the transmitter, which is required to compute the downlink precoding matrix in MIMO broadcast channels. The full-duplex operation allows leveraging channel reciprocity for open-loop uplink training to estimate the downlink channels. However, the uplink transmission of training creates interference at the downlink receiving mobile nodes. We characterize the optimal training resource allocation and its associated spectral efficiency, in the proposed open-loop training based full-duplex system. We also evaluate the performance of the half-duplex counterpart to derive the relative gains of full-duplex training. Despite the existence of inter-node interference due to full-duplex, significant spectral efficiency improvement is attained over half-duplex operation.

2015 49th Asilomar Conference on Signals, Systems and Computers, 2015

Eprint Arxiv 1102 1498, Feb 7, 2011

An achievable rate region is obtained for a primary multiple access network coexisting with a sec... more An achievable rate region is obtained for a primary multiple access network coexisting with a secondary link of one transmitter and a corresponding receiver. The rate region depicts the sum primary rate versus the secondary rate and is established assuming that the secondary link performs rate-splitting. The achievable rate region is the union of two types of achievable rate regions. The first type is a rate region established assuming that the secondary receiver cannot decode any primary signal, whereas the second is established assuming that the secondary receiver can decode the signal of one primary receiver. The achievable rate region is determined first assuming discrete memoryless channel (DMC) then the results are applied to a Gaussian channel. In the Gaussian channel, the performance of rate-splitting is characterized for the two types of rate regions. Moreover, a necessary and sufficient condition to determine which primary signal that the secondary receiver can decode without degrading the range of primary achievable sum rates is provided. When this condition is satisfied by a certain primary user, the secondary receiver can decode its signal and achieve larger rates without reducing the primary achievable sum rates from the case in which it does not decode any primary signal. It is also shown that, the probability of having at least one primary user satisfying this condition grows with the primary signal to noise ratio.

Corr, Feb 8, 2010

We investigate power allocation for users in a spectrum underlay cognitive network. Our objective... more We investigate power allocation for users in a spectrum underlay cognitive network. Our objective is to find a power control scheme that allocates transmit power for both primary and secondary users so that the overall network throughput is maximized while maintaining the quality of service (QoS) of the primary users greater than a certain minimum limit. Since an optimum solution to our problem is computationally intractable, as the optimization problem is non-convex, we propose an iterative algorithm based on sequential geometric programming, that is proved to converge to at least a local optimum solution. We use the proposed algorithm to show how a spectrum underlay network would achieve higher throughput with secondary users operation than with primary users operating alone. Also, we show via simulations that the loss in primary throughput due to the admission of the secondary users is accompanied by a reduction in the total primary transmit power. 1

IEEE/ACM Transactions on Networking, 2015

2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2015

IEEE/ACM Transactions on Networking, 2015

2014 48th Asilomar Conference on Signals, Systems and Computers, 2014

IEEE/ACM Transactions on Networking, 2014

In this work, we propose and study optimal proactive resource allocation and demand shaping for d... more In this work, we propose and study optimal proactive resource allocation and demand shaping for data networks. Motivated by the recent findings on the predictability of human behavior patterns in data networks, and the emergence of highly capable handheld devices, our design aims to smooth out the network traffic over time and minimize the data delivery costs. Our framework utilizes proactive data services as well as smart content recommendation schemes for shaping the demand. Proactive data services take place during the off-peak hours based on a statistical prediction of a demand profile for each user, whereas smart content recommendation assigns modified valuations to data items so as to render the users' demand less uncertain. Hence, our recommendation scheme aims to boost the performance of proactive services within the allowed flexibility of user requirements. We conduct theoretical performance analysis that quantifies the leveraged cost reduction through the proposed framework. We show that the cost reduction scales at the same rate as the cost function scales with the number of users. Further, we prove that demand shaping through smart recommendation strictly reduces the incurred cost even below that of proactive downloads without recommendation.