Pengxiang Li

Stochastic network calculus analysis of energy harvesting rate in wireless networks with delay and energy storage constraints

Energy evaluation of wireless transmission for data service under different QoS (quality of service) constraints is a hot topic in green communications. In this paper, we employ the theory of the stochastic network calculus to investigate the relationship between the traffic arrival rate and energy harvesting rate under the delay and energy storage constraints. We first construct a wireless system model which works only by consuming the harvested renewable energy. Also, stochastic traffic arrivals, packet size as well as a two-state Markov chain interference on energy harvesting are jointly considered to ensure the accuracy of the analysis. We derive the minimum energy harvesting rate needed to satisfy the delay and energy storage constraints under a given average arrival rate. The efficiency of the harvested energy is also studied and shown to be convex in the numerical simulation. Numerical results illustrate that while the minimum energy harvesting rate is positively correlated with the packet size, it is negatively related to the delay requirement, under a given arrival rate. Additionally, the probabilistic bound of energy insufficiency is shown to be positively correlated with the transition cycle of the interference.

A Pilot Assignment Scheme for Single-Cell Massive MIMO Circumstances

—In Time-Division Duplex (TDD) massive MultipleInput Multiple-Output (MIMO) systems, pilot contamination becomes the performance bottleneck when the number of terminals is larger than that of available pilot sequences. In this paper, we first deduce the general formulas for uplink Signal-toInterference Ratio (SIR) and channel capacity in single-cell massive MIMO circumstances with insufficient pilot sequences. Then, in order to enhance the Quality of Service (QoS) for the terminals who suffer from severe pilot contamination, an optimization problem is formulated to maximize the minimum uplink capacity of all terminals. Next, because the complexity of finding the optimal pilot assignment is too high, a suboptimal two-step assignment approach with low complexity is proposed to solve the optimization problem. Compared with the random pilot assignment scheme in single-cell massive MIMO systems, simulation results prove the effectiveness of this two-step scheme in obtaining better minimum uplink SIR and minimum channel capacity when the number of BS antennas is great but finite. Meanwhile, the average capacity of all terminals can also be improved.

Throughput Analysis of an Energy Harvesting Multichannel System Under Delay and Energy Storage Constraints

High power to guarantee strict performance requirement and low power to avoid energy depletion result in an inevitable conflict for a renewable energy harvesting communication system with finite energy storage. This paper proposes a generic approach to study the per-flow performance in such a multichannel system multiplexed by multiple flows. The queueing delay constraint and energy storage constraint are constructed to express the probabilistic bound of queuing delay and that of energy depletion, respectively. We study these constraints with the statistical information of the processes, including traffic arrivals and service, energy harvesting, and consumption. The lower bound of the long-term maximum per-flow throughput is then derived to meet the constraints under a specific system. The accuracy of the proposed approach is validated by simulation experiments. The analysis reveals how the sustained throughput is affected by various factors, such as the queueing delay and energy storage constraints, the packet size, the energy block size, the traffic scheduling schemes, the bandwidth allocation schemes as well as the interdependence among the channel service processes. Particularly, the analysis also provides valuable insight into traffic admission control from the viewpoint of small queueing delay and finite energy storage.

Delay and Delay-Constrained Throughput Performance of a Wireless-Powered Communication System

In this paper, the delay and delay-constrained throughput performance of a point-to-point wireless-powered communication system is investigated. In this system, the wireless-powered node, e.g., a user equipment (UE), receives data at the same time when powered from the other node, e.g., an access point (AP), and uses the harvested wireless energy to send data to the other node. The investigation focuses on the delay performance of sending data in the downlink (DL) from the AP node to the UE node and that in the uplink (UL) from the UE node to the AP node, based on which the throughput performance on both directions when delay constraints are enforced is also studied. To this aim, the cumulative service capacity of the service process is first analyzed for both DL and UL, taking into consideration the delay caused by the nontransmission phase for the AP or UE in each charging cycle. Thereafter, a general upper bound on the delay distribution for stochastic traffic arrivals is obtained for both DL and UL, based on which the delay-constrained throughput performance is further studied. In addition, to ensure the delay performance, the required energy storage capacity and wireless charging rate are investigated. The obtained results are exemplified with two specific traffic types, and the accuracy of the analysis is validated by comparison with extensive simulation results. The analysis and results shed new light on the performance of wireless-powered communication systems.

Enhanced multi-resolution hierarchical codebook design for adaptive compressed sensing based millimeter wave channel estimation

Perfect channel state information (CSI) is essential for precoding and combining in millimeter wave (mmWave) systems. The CSI estimation algorithm based on adaptive compressed sensing (CS) is an efficient method. However, the imperfect multi-resolution hierarchical codebook design possibly leads to wrong detections of angle of arrival (AoA) and angle of departure (AoD), which has a negative effect on the spectral efficiency. In this paper, an enhanced multi-resolution hierarchical codebook design is proposed to realize precise AoD/AoA estimation. First, the necessary number of sampling angles for generating the codebook is given. Then, the algorithm of iterative adjustment (IA) is developed to improve the codebook design. Simulation results show that using the proposed codebook design, the beams can precisely divide the AoA/AoD intervals as the requirements of the adaptive CS based algorithm. Thus, the average angle estimation error is reduced effectively.

Uplink signal structure design for multi-cell TDD massive MIMO systems

For multi-cell time-division duplex (TDD) massive multiple-input multiple-output (MIMO) systems, pilot contamination originates from limited pilot resources has been proved to be the ultimate limiting factor when the base station (BS) antennas are increased without bound. In this paper, a modified uplink signal structure is proposed to reduce the negative effects of pilot contamination. Specifically, we add a certain amount of identification information for distinguishing the terminals in different cells at the beginning of uplink signals. With this improved uplink signal structure, the BS obtains better channel estimates. Then uplink signal-to-interference ratio (SIR) and available capacity are obviously increased. Further, we also analyze the performance of actual situation when errors occur during the transmission of identification information. Simulation results prove the effectiveness of this signal structure in obtaining better available capacity when the coherence interval is high.

Packet delay analysis in wireless multi-channel networks: A network calculus perspective

In this work, we propose a stochastic network calculus based approach to study the packet delay in a multichannel network comprising one control channel and multiple parallel data channels. A node should compete with other nodes on the control channel before it is allowed to transmit packets on the data channels. The packet delay is the sum of packet (or node) competition delay, queueing delay and transmission delay. We derive an upper bound of the CCDF (complementary cumulative distribution function) of the packet delay, which is also called the probabilistic delay bound, in a general multi-channel network where not only the stochastic traffic can be any type, but also the above three types of delay can either be independent or correlated. Moreover, for further understanding and applying the proposed approach, we also employed Poisson traffic as a specific case to investigate the impact factors on the packet delay through traffic characteristics and network configurations.

Performance analysis for MISO wireless communication systems using stochastic network calculus

In this paper, a slow fading MISO (Multiple-Input Single-Output) wireless communication system with N transmit antennas is established. The transmission channel is considered as a complex Additive White Gaussian Noise (AWGN) term. Then the distribution of channel capacity is deduced based on probability theory and mathematical statistics. After that, stochastic service curve of the system is derived by combining channel capacity and stochastic network calculus. Further, performance analysis is presented for periodic traffic. Finally, numerical results and simulation results under different parameters are demonstrated and discussed.

A network calculus approach to throughput analysis of stochastic multi-channel networks

In this paper, two types of throughput, which are transient throughput and delay-constraint throughput, are investigated in a Gilbert-Elliott multi-channel network by using the stochastic network calculus. We propose a multi-channel model and derive an equivalent stochastic service curve guaranteed by the whole network. With the stochastic service curve, we obtain the lower bound of the network transient throughput. The throughput is non-asymptotic in that it holds for any number of channels and also fully accounts for transient regime. After, we derive the probabilistic delay bound of the multi-channel network, with which we further ascertain the delay-constraint throughput. Finally, numerical results are presented to show the impacts of the channel memory and number of channel on the transient throughput and that of the delay constraint on the maximum arrival rate sustained by the network.

Performance analysis for multi-carrier system based on stochastic network calculus

In this paper, probabilistic backlog and delay bound of multi-carrier systems are studied using stochastic network calculus. Firstly, a typical multi-carrier model is established. We assume that the transmitted signals will suffer equal flat Rayleigh fading on each subcarrier. Thereafter, the distribution of system capacity can be derived based on the central limit theorem. According to stochastic network calculus, probabilistic backlog and delay bound are demonstrated under periodic traffic source. Finally, numerical results and simulation results are presented and discussed.