Ernest S. Lo

Centre Tecnologic de Telecomunicacions de Catalunya

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Derrick Wing Kwan Ng

UNSW Sydney

Robert Schober

Friedrich-Alexander-Universität Erlangen-Nürnberg

Khaled B. Letaief

Hong Kong University of Science and Technology

Ross Murch

Hong Kong University of Science and Technology

R.S. Cheng

Nanjing University of Information Science and Technology

Wai Ho Mow

Hong Kong University of Science and Technology

Vincent K. N. Lau

University of Hong Kong

Shigeru Shimamoto

Waseda University

Peter S. Chan

Tulane University

Peter W. Y. Chan

Zymeworks (Canada)

Cooperative Institutions

University of Hong Kong

Hong Kong University of Science and Technology

Applied Science and Technology Research Institute

Institute of Electrical and Electronics Engineers

City University of Hong Kong

Waseda University

Southern University of Science and Technology

Friedrich-Alexander-Universität Erlangen-Nürnberg

Canadian Standards Association

Huawei Technologies (China)

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Energy-Efficient Resource Allocation in OFDMA Systems with Hybrid Energy Harvesting Base Station

IEEE Transactions on Wireless Communications (2013)

Derrick Wing Kwan Ng Ernest S. Lo Robert Schober

We study resource allocation algorithm design for energy-efficient communication in an orthogonal frequency division multiple access (OFDMA) downlink network with hybrid energy harvesting base station (BS). Specifically, an energy harvester and a constant energy source driven by a non-renewable resource are used for supplying the energy required for system operation. We first consider a deterministic offline system setting. In particular, assuming availability of non-causal knowledge about energy arrivals and channel gains, an offline resource allocation problem is formulated as a non-convex optimization problem over a finite horizon taking into account the circuit energy consumption, a finite energy storage capacity, and a minimum required data rate. We transform this non-convex optimization problem into a convex optimization problem by applying time-sharing and exploiting the properties of non-linear fractional programming which results in an efficient asymptotically optimal offline iterative resource allocation algorithm for a sufficiently large number of subcarriers. In each iteration, the transformed problem is solved by using Lagrange dual decomposition. The obtained resource allocation policy maximizes the weighted energy efficiency of data transmission (weighted bit/Joule delivered to the receiver). Subsequently, we focus on online algorithm design. A conventional stochastic dynamic programming approach is employed to obtain the optimal online resource allocation algorithm which entails a prohibitively high complexity. To strike a balance between system performance and computational complexity, we propose a low complexity suboptimal online iterative algorithm which is motivated by the offline algorithm. Simulation results illustrate that the proposed suboptimal online iterative resource allocation algorithm does not only converge in a small number of iterations, but also achieves a close-to-optimal system energy efficiency by utilizing only causal channel state and energy arrival information.

Fractional programming

10.1109/twc.2013.052813.121589

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Citations (239)

Wireless Information and Power Transfer: Energy Efficiency Optimization in OFDMA Systems

IEEE Transactions on Wireless Communications (2013)

Derrick Wing Kwan Ng Ernest S. Lo Robert Schober

This paper considers orthogonal frequency division multiple access systems with simultaneous wireless information and power transfer. We study the resource allocation algorithm design for maximization of the energy efficiency of data transmission. In particular, we focus on power splitting hybrid receivers which are able to split the received signals into two power streams for concurrent information decoding and energy harvesting. Two scenarios are investigated considering different power splitting abilities of the receivers. In the first scenario, we assume receivers which can split the received power into a continuous set of power streams with arbitrary power splitting ratios. In the second scenario, we examine receivers which can split the received power only into a discrete set of power streams with fixed power splitting ratios. In both scenarios, we formulate the corresponding algorithm design as a non-convex optimization problem which takes into account the circuit power consumption, the minimum data rate requirements of delay constrained services, the minimum required system data rate, and the minimum amount of power that has to be delivered to the receivers. Subsequently, by exploiting fractional programming and dual decomposition, suboptimal iterative resource allocation algorithms are proposed to solve the non-convex problems. Simulation results illustrate that the proposed iterative resource allocation algorithms approach the optimal solution within a small number of iterations and unveil the trade-off between energy efficiency, system capacity, and wireless power transfer.

Maximization

Power budget

10.1109/twc.2013.103113.130470

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Citations (431)

Energy-Efficient Resource Allocation in OFDMA Systems with Hybrid Energy Harvesting Base Station

arXiv (Cornell University) (2013)

Derrick Wing Kwan Ng Ernest S. Lo Robert Schober

We study resource allocation algorithm design for energy-efficient communication in an OFDMA downlink network with hybrid energy harvesting base station. Specifically, an energy harvester and a constant energy source driven by a non-renewable resource are used for supplying the energy required for system operation. We first consider a deterministic offline system setting. In particular, assuming availability of non-causal knowledge about energy arrivals and channel gains, an offline resource allocation problem is formulated as a non-convex optimization problem taking into account the circuit energy consumption, a finite energy storage capacity, and a minimum required data rate. We transform this non-convex optimization problem into a convex optimization problem by applying time-sharing and fractional programming which results in an efficient asymptotically optimal offline iterative resource allocation algorithm. In each iteration, the transformed problem is solved by using Lagrange dual decomposition. The obtained resource allocation policy maximizes the weighted energy efficiency of data transmission. Subsequently, we focus on online algorithm design. A stochastic dynamic programming approach is employed to obtain the optimal online resource allocation algorithm which requires a prohibitively high complexity. To strike a balance between system performance and computational complexity, we propose a low complexity suboptimal online iterative algorithm which is motivated by the offline optimization.

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Citations (2)

Cooperative Concatenated Coding for Wireless Systems

IEEE International Conference on Communications (2007)

Ernest S. Lo Khaled B. Letaief

Cooperative transmission has been of growing interest recently where users take advantage of each other's resources for better overall performance. In this paper, coded cooperation for wireless networks is considered and a novel cooperative concatenated coding strategy is proposed. In contrast to previous works, this scheme features additional coding benefits other than spatial diversity. Specifically, we show that remarkable error rate reduction can be achieved even when the receive SNR of all cooperating users is maintained at a specific level. The idea of interleaver gain of concatenated codes is exploited and it is shown that the error rate decreases dramatically with the number of cooperating nodes. Multiple cooperating users with unequal message sizes can also be supported easily and a reduced-complexity cooperative encoding structure is provided for good inter-user channels. Code design criteria are also investigated, as well as, the performance under various data-block sizes and number of cooperating users.

Coding gain

Cooperative Diversity

Forward error correction

10.1109/icc.2007.1010

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Citations (7)

Energy-Efficient Resource Allocation for Secure OFDMA Systems

IEEE Transactions on Vehicular Technology (2012)

Derrick Wing Kwan Ng Ernest S. Lo Robert Schober

In this paper, resource allocation for energy-efficient secure communication in an orthogonal frequency-division multiple-access (OFDMA) downlink network is studied. The considered problem is modeled as a nonconvex optimization problem that takes into account the sum-rate-dependent circuit power consumption, multiple-antenna eavesdropper, artificial noise generation, and different quality-of-service (QoS) requirements, including a minimum required secrecy sum rate and a maximum tolerable secrecy outage probability. The power, secrecy data rate, and subcarrier allocation policies are optimized for maximization of the energy efficiency of secure data transmission (bit/joule securely delivered to the users). The considered nonconvex optimization problem is transformed into a convex optimization problem by exploiting the properties of fractional programming, which results in an efficient iterative resource allocation algorithm. In each iteration, the transformed problem is solved by using dual decomposition. Simulation results illustrate that the proposed iterative resource allocation algorithm not only converges in a small number of iterations but maximizes the system energy efficiency and guarantees a nonzero secrecy data rate for the desired users as well. In addition, the obtained results unveil a tradeoff between energy efficiency and secure communication.

Fractional programming

Artificial Noise

Maximization

10.1109/tvt.2012.2199145

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Citations (242)

Energy-Efficient Resource Allocation in OFDMA Systems with Hybrid Energy Harvesting Base Station

arXiv (Cornell University) (2013)

Derrick Wing Kwan Ng Ernest S. Lo Robert Schober

10.48550/arxiv.1302.4721

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Citations (0)

Energy-efficient resource allocation in multi-cell OFDMA systems with limited backhaul capacity

2022 IEEE Wireless Communications and Networking Conference (WCNC) (2012)

Derrick Wing Kwan Ng Ernest S. Lo Robert Schober

In this paper, resource allocation for energy efficient communication in multi-cell orthogonal frequency division multiple access (OFDMA) downlink networks with cooperative base stations (BSs) is studied. The considered problem is formulated as a non-convex optimization problem which takes into account the circuit power consumption, the limited backhaul capacity, and the minimum required data rate for joint BS zero-forcing beamforming (ZFBF) transmission. By exploiting the properties of fractional programming, the considered non-convex optimization problem in fractional form is transformed into an equivalent optimization problem in subtractive form, which enables the derivation of an efficient iterative resource allocation algorithm. For each iteration, the optimal power allocation solution is derived with a low complexity suboptimal subcarrier allocation policy for maximization of the energy efficiency of data transmission (bit/Joule delivered to the users). Simulation results illustrate that the proposed iterative resource allocation algorithm converges in a small number of iterations, and unveil the trade-off between energy efficiency and network capacity.

Backhaul (telecommunications)

Fractional programming

10.1109/wcnc.2012.6213948

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Citations (46)

Adaptive Resource Allocation and Capacity Comparison of Downlink Multiuser MIMO-MC-CDMA and MIMO-OFDMA

IEEE Transactions on Wireless Communications (2007)

Ernest S. Lo Peter S. Chan Vincent K. N. Lau R.S. Cheng Khaled B. Letaief

In this paper, we examine and compare the potential maximum sum capacity of downlink multiple-input-multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) and multiple-input-multiple-output multicarrier code division multiple access (MIMO-MC-CDMA) in a single-cell multiuser environment with channel side information at the transmitter, with and without a fairness constraint. The resource allocation is formulated as a cross-layer optimization framework and optimal power allocation and user selection algorithms are proposed for both scenarios. We find that for delay-sensitive applications, where fairness is imposed, the performance gain of OFDMA over MC-CDMA is quite large at moderate path loss exponents and number of antennas. However, for delay-insensitive applications, the benefits of OFDMA over MC-CDMA are significantly reduced when the path loss exponent or the number of antennas is large

Frequency-division multiple access

10.1109/twc.2007.05510

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Citations (84)

Network Coding Versus Superposition Coding for Two-Way Wireless Communication

IEEE Wireless Communications and Networking Conference (2009)

Ernest S. Lo Khaled B. Letaief

Wireless network coding has attracted significant attention recently over relay channels. In this paper, we are interested in two-way wireless communication and explore the comparative advantages of two popular network coding strategies, binary network coding (NetC) and superposition coding (SupC), also named as analog network coding. In the literature, most works focused on NetC under a three-step framework and recently also SupC but under a two-step one. However, there is still little understanding on the truly optimal configuration. In addition, most works assumed channel knowledge at the transmitters while ignoring the presence of the direct link, which may not be valid in a fading environment. In this work, we focus on the outage performance instead and take into consideration also the time-varying nature of the direct link Outage regions of various schemes are theoretically characterized and their optimal operating conditions are identified, from which the best combined strategies are derived in terms of the maximum goodput and robustness to channel knowledge defects. Interesting new findings together with insightful discussions are provided.

Goodput

Linear network coding

10.1109/wcnc.2009.4917828

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Citations (20)

Dynamic Resource Allocation in MIMO-OFDMA Systems with Full-Duplex and Hybrid Relaying

IEEE Transactions on Communications (2012)

Derrick Wing Kwan Ng Ernest S. Lo Robert Schober

In this paper, we formulate a joint optimization problem for resource allocation and scheduling in full-duplex multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) relaying systems with amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols. Our problem formulation takes into account heterogeneous data rate requirements for delay sensitive and non-delay sensitive users. We also consider a theoretically optimal hybrid relaying scheme as a performance benchmark, which allows a dynamic selection between AF relaying and DF relaying protocols with full-duplex and half-duplex relays. We show that under some mild conditions the optimal transmitter precoding and receiver post-processing matrices jointly diagonalize the MIMO-OFDMA relay channels for all considered relaying protocols transforming the resource allocation and scheduling problem into a scalar optimization problem. Dual decomposition is employed to solve this optimization problem and a distributed iterative resource allocation and scheduling algorithm with closed-form power and subcarrier allocation is derived. Simulation results not only illustrate that the proposed distributed algorithm converges to the optimal solution in a small number of iterations, but also demonstrate the potential performance gains achievable with full-duplex relaying protocols.

Duplex (building)

Frequency-division multiple access

10.1109/tcomm.2012.031712.110233

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Citations (221)