Qing Bai

Throughput maximizing transmission strategy of energy harvesting nodes

We investigate the throughput maximizing data transmission strategy of an energy harvesting node which is able to harvest and store energy for communication. Solar cell and rechargeable battery technologies have made such nodes feasible. In addition to the energy arrival process and the battery capacity limitation, the energy consumption of the circuits of the node also plays an important role in the way how the harvested energy should be utilized. To this end, we assume for the transmitting node an active mode for which a constant circuit power is incurred, and a sleep mode for which no energy is consumed. The criteria that an optimal transmission strategy should satisfy are discussed, and based on them, a construction procedure of the optimal transmission strategy is proposed. Numerical simulations are performed to verify the theoretical results, and the impact of circuit power on the optimal transmission strategy and the maximal achievable throughput is studied.

Energy efficiency maximization for 5G multi-antenna receivers

In a digital communication system, the analog signal that the receiver receives with its radio frequency front end is converted into digital format by using the analog-to-digital converter A/D converter, ADC. Quantisation takes place during the conversion from continuous amplitude signal to discrete amplitude signal, leading inevitably to losses in information which are dependent on the number of bits that is used to represent each sample. Although employing a higher bit resolution reduces the quantisation error, a higher power dissipation of the ADC is incurred at the same time. This trade-off is essential to the energy efficiency of the receiver, which is commonly measured by the number of information bits conveyed per consumed Joule of energy. We investigate, in this work, the adaptation of ADC resolutions of a multi-antenna receiver based on instantaneous channel knowledge, with the goal of maximising receiver energy efficiency. The formulated optimisation is a combinatorial problem, and we propose several algorithms which yield near-optimal solutions. Results from numerical simulations are presented and analysed, which provide guidelines to operation and deployment of the system. Copyright

On the effects of carrier frequency offset on cyclic prefix based OFDM and filter bank based multicarrier systems

Being sensitive to carrier frequency offset (CFO) is known to be one of the main drawbacks of multicarrier systems. In this paper, the effects of CFO on a filter bank based multicarrier system (FBMC) in a multipath fading channel are discussed, where an ideal root-raised cosine (RRC) filter with roll-off factor 1 is used as the prototype filter which enables analytical derivations of the interference caused by the CFO. Based on these results, an approximation on the SNR degradation with very small CFO is also given. Numerical experiments as well as Monte Carlo simulations are done to verify the analysis and the accuracy of the approximation in FBMC systems. A comparison with the SNR degradations in cyclic prefix based orthogonal frequency division multiplexing (CP-OFDM) systems has indicated an advantage of FBMC systems as being more robust to frequency misalignments.

Average throughput maximization for energy harvesting transmitters with causal energy arrival information

We consider an energy harvesting node which transmits data using the energy it harvests from the environment. In the simple scenario of point-to-point communication, the performance of the node in terms of throughput is greatly influenced by the transmission strategy it employs and its knowledge about the energy arriving process. We assume in this work that the transmitting node does not have non-causal information about the energy to be harvested in future, but only has available the statistics of the energy arriving process which is stationary. The practical considerations that the energy storage capacity of the node is limited and there is additional energy consumption within the circuitry of the node are taken into account by our system model. Viewing the system as a finite-state Markov decision process, we optimize the transmission policy the node employs as a function of the energy storage state after an energy arrival, by using the policy-iteration algorithm. The asymptotic performance of the system in terms of average throughput is studied within the established theoretical and algorithmic framework, under the several transmission strategies we propose. Simulation results indicate the advantage of each strategy with respect to a certain range of values that the system parameters may take.

Modulation optimization for energy harvesting transmitters with compound Poisson energy arrivals

With the development of the energy harvesting technology, communication devices nowadays can be powered by the electrical energy obtained by converting different forms of energy from their ambience. The energy that becomes available to such transceivers varies both in time and amount, the exact information of which is usually unknown to the transceivers. We consider in this work the point-to-point communication between an energy harvesting transmitter and a receiver over a block-fading channel, where the transmitter has statistical and causal knowledge about the energy arrivals as well as the channel conditions. The stochastic energy arriving process is assumed compound Poisson, which provides both good mathematical tractability and enough physical generality. With the objective of maximizing the average throughput over a long operation time, we model the system as a Markov decision process and apply the policy-iteration algorithm to optimize the transmission policies with respect to all discretized system states. Several transmission strategies are proposed and compared from the aspects of ease of control, performance, and computational complexity.

Scheduling and resource allocation in OFDM and FBMC systems: An interactive approach and performance comparison

In modern wireless communication systems, scheduling and resource allocation are two closely related tasks of the medium access control (MAC) and physical (PHY) layers respectively. In this paper, we present a separate yet interactive design of the two functional modules, where the scheduler prioritizes data packets from different service flows according to their traffic characteristics and feedback from the resource allocator, while the resource allocator performs quality of service (QoS) constrained transmit power minimization given lists of prioritized packets from the scheduler. The simulation results of applying the model to both cyclic prefix based OFDM (CP-OFDM) and the filter bank based multicarrier (FBMC) systems demonstrate the superior performance of the latter.

On energy efficient cross-layer assisted resource allocation in multiuser multicarrier systems

In this paper the quality of service (QoS) constrained radio resource allocation problem at the downlink of a multiuser multicarrier system is investigated. We demonstrate and analyze the trade-off between energy consumption and transmit power within a cross physical and link layer system model, which jointly considers power allocation, adaptive modulation and coding and ARQ/HARQ retransmission protocols. A novel transmit power constrained energy minimization problem is formulated based on the competing nature of the two resources. Due to the combinatorial property of the problem, a suboptimal heuristic resource allocation algorithm is proposed, the accuracy of which is compared with the dual optimal value obtained as a byproduct of the algorithm. Simulation results also provide performance comparisons on ARQ and HARQ protocols, and their different impacts on the choice of the optimal modes of operations.

Minimizing the energy per bit for pilot-assisted data transmission over quantized channels

To communicate over a priori unknown channels, pilot sequences can be exploited to assist the receiver in obtaining the channel state information. The analog-to-digital converter (ADC) at the front end of the receiver samples and quantizes the input signal, including both pilot and data symbols. This results in a reduction of the receive signal-to-noise ratio (SNR) as well as deteriorated quality of channel estimation, which depends quantitatively on the bit resolution used by the ADC. In this work, we consider the point-to-point, training based communication between a single-antenna transmitter and a multi-antenna receiver over a Rayleigh block fading channel, and take into account the impact of the ADC for a joint optimization of the training length, the average receive SNR, the number of receive antennas, and the bit resolution of the ADC. Goal of the optimization is to minimize the energy per bit metric, where we include both transmit power and power dissipation of the ADC into the energy consumption model, and employ a capacity lower bound which depends on all aforementioned design parameters. Results from numerical simulations are demonstrated and analyzed, leading to a number of insightful observations and conclusions which are important for the energy efficient operation of the system.

QoS-constrained Energy Minimization in Multiuser Multicarrier Systems

In this paper the QoS-constrained resource allocation problem in multicarrier systems is considered. Within the established cross-layer framework, parameters for subchannel assignment, adaptive modulation and coding, and ARQ/HARQ protocols are jointly optimized. Instead of the conventional transmit power minimization, the total energy consumption for the successful transmissions of all information bits is set as the optimization goal. The nonconvex primal problem is solved by using Lagrange dual decomposition and the ellipsoid method. Numerical results indicate that the recovered primal solution is well acceptable in performance, and efficient in terms of computational effort.

Packet scheduling and resource allocation for downlink multicarrier systems with quality-of-service constraints

We consider the scheduling and resource allocation problem in the downlink of multicarrier systems where data is processed and transmitted in unit of packets. This involves the allocation of transmit power as well as time and frequency slots to packets generated by different service flows, which consequently have various lengths and allows for various latency time in delivery. An optimization to maximize system throughput under frequency division multiple access (FDMA) and available resources restrictions is formulated, and an interactive scheduling and resource allocation approach is proposed to solve this combinatorial-natured problem. The paper especially focuses on the design of packet scheduling algorithms and introduces the concept of virtual packet size and anxious scheduler, which allows for simple implementation and high flexibility. Simulation results show the efficient collaboration of the proposed scheduling algorithm with the resource allocation scheme, and the effectiveness of the system as a whole which favorably exhibits low complexity.