Changyang She

Energy-Efficient Resource Allocation for MIMO-OFDM Systems Serving Random Sources With Statistical QoS Requirement

This paper optimizes resource allocation that maximizes the energy efficiency (EE) of wireless systems with statistical quality of service (QoS) requirement, where a delay bound and its violation probability need to be guaranteed. To avoid wasting energy when serving random sources over wireless channels, we convert the QoS exponent, a key parameter to characterize statistical QoS guarantee under the framework of effective bandwidth and effective capacity, into multi-state QoS exponents dependent on the queue length. To illustrate how to optimize resource allocation, we consider multi-input-multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. A general method to optimize the queue length based bandwidth and power allocation (QRA) policy is proposed, which maximizes the EE under the statistical QoS constraint. A closed-form optimal QRA policy is derived for massive MIMO-OFDM system with infinite antennas serving the first order autoregressive source. The EE limit obtained from infinite delay bound and the achieved EEs of different policies under finite delay bounds are analyzed. Simulation and numerical results show that the EE achieved by the QRA policy approaches the EE limit when the delay bound is large, and is much higher than those achieved by existing policies considering statistical QoS provision when the delay bound is stringent.

Ensuring the Quality-of-Service of Tactile Internet

Tactile internet requires ultra-low latency and ultrahigh reliability, which bring new challenges to the design of mobile systems. In this paper, we study how much resources are required to ensure the short end-to-end (E2E) delay and high reliability by taking a vehicle communication system as an example, where the E2E delay includes both queueing delay and transmission delay, and the reliability is captured by the packet loss and packet error caused by finite blocklength channel codes, queueing delay violation and packets dropping during deep channel fading periods. To this end, we optimize the bandwidth allocation among multiple users to minimize the average transmit power required to ensure the queueing delay and its violation probability of each packet, and analyze the maximal transmit power required to guarantee the E2E delay and the reliability. Simulation and numerical results validate our analysis and show the required maximal transmit power, bandwidth, and number of antennas to ensure the extremely stringent quality of service.

Cross-Layer Transmission Design for Tactile Internet

To ensure the low end-to-end (E2E) delay for tactile internet, short frame structures will be used in 5G systems. As such, transmission errors with finite blocklength channel codes should be considered to guarantee the high reliability requirement. In this paper, we study cross-layer transmission optimization for tactile internet, where both queueing delay and transmission delay are accounted for in the E2E delay, and different packet loss/error probabilities are considered to characterize the reliability. We show that the required transmit power becomes unbounded when the allowed maximal queueing delay is shorter than the channel coherence time. To satisfy quality-of-service requirement with finite transmit power, we introduce a proactive packet dropping mechanism, and optimize a queue state information and channel state information dependent transmission policy. Since the resource and policy for transmission and the packet dropping policy are related to the packet error probability, queueing delay violation probability, and packet dropping probability, we optimize the three probabilities and obtain the policies related to these probabilities. We start from single-user scenario and then extend our framework to the multi-user scenario. Simulation results show that the optimized three probabilities are in the same order of magnitude. Therefore, we have to take into account all these factors when we design systems for tactile internet applications.

Radio Resource Management for Ultra-Reliable and Low-Latency Communications

Supporting ultra-reliable and low-latency communications (URLLC) is one of the major goals in 5G communication systems. Previous studies focus on ensuring end-to-end delay requirement by reducing transmission delay and coding delay, and only consider reliability in data transmission. However, the reliability reflected by overall packet loss also includes other components such as queueing delay violation. Moreover, which tools are appropriate to design radio resource allocation under constraints on delay, reliability, and availability is not well understood. As a result, how to optimize resource allocation for URLLC is still unclear. In this article, we first discuss the delay and packet loss components in URLLC and the network availability for supporting the quality of service of users. Then we present tools for resource optimization in URLLC. Last, we summarize the major challenges related to resource management for URLLC, and perform a case study.

Uplink Transmission Design with Massive Machine Type Devices in Tactile Internet

In this work, we study how to design uplink transmission with massive machine type devices in tactile internet, where ultra-short delay and ultra- high reliability are required. To characterize the transmission reliability constraint, we employ a two- state transmission model based on the achievable rate with finite blocklength channel codes. If the channel gain exceeds a threshold, a short packet can be transmitted with a small error probability; otherwise there is a packet loss. To exploit frequency diversity, we assign multiple subchannels to each active device, from which the device selects a subchannel with channel gain exceeding the threshold for transmission. To show the total bandwidth required to ensure the reliability, we optimize the number of subchannels and bandwidth of each subchannel and the threshold for each device to minimize the total bandwidth of the system with a given number of antennas at the base station. Numerical results show that with 1000 devices in one cell, the required bandwidth of the optimized policy is acceptable even for prevalent cellular systems. Furthermore, we show that by increasing antennas at the BS, frequency diversity becomes unnecessary, and the required bandwidth is reduced.

Context aware energy efficient optimization for video on-demand service over wireless networks

Video on-demand (VOD) service is widely requested, and is becoming a dominant application in wireless networks, where energy efficiency (EE) is a major design goal. Reducing the energy consumption of VOD service with given quality of service (QoS) requirement can improve the EE of wireless systems. Recent finding shows that user mobility is highly predictable, and hence future location information is possible to know. In this paper, we study EE-optimal transmit power and bandwidth allocation for VOD service in orthogonal frequency division multiplexing (OFDM) system by exploiting context information. We consider two kinds of context information, i.e., the predictive average channel gains and the QoS of VOD service. The optimal resource allocation policy that minimizes the average energy consumption for VOD service is proposed. At the beginning of the service, the average transmit power and number of used subcarriers are allocated with future average channel gains. During the procedure of the service, the instantaneous transmit power is allocated to different subcarriers after the instantaneous channel gains becomes available. Simulation results show that the energy consumed for VOD service with the proposed policy is around half of that with an existing policy.

Energy efficient design for tactile internet

Ensuring the ultra-low end-to-end latency and ultrahigh reliability required by tactile internet is challenging. This is especially true when the stringent Quality-of-Service (QoS) requirement is expected to be satisfied not at the cost of significantly reducing spectral efficiency and energy efficiency (EE). In this paper, we study how to maximize the EE for tactile internet under the stringent QoS constraint, where both queueing delay and transmission delay are taken into account. We first validate that the upper bound of queueing delay violation probability derived from the effective bandwidth can be used to characterize the queueing delay violation probability in the short delay regime for Poisson arrival process. However, the upper bound is not tight for short delay, which leads to conservative designs and hence leads to wasting energy. To avoid this, we optimize resource allocation that depends on the queue state information and channel state information. Analytical results show that with a large number of transmit antennas the EE achieved by the proposed policy approaches to the EE limit achieved for infinite delay bound, which implies that the policy does not lead to any EE loss. Simulation and numerical results show that even for not-so-large number of antennas, the EE achieved by the proposed policy is still close to the EE limit.

Energy Efficiency and Delay in Wireless Systems: Is Their Relation Always a Tradeoff?

It is well known that the average transmit power can be traded off by average delay. This paper strives to study the relation between the maximal energy efficiency (EE) and the delay bound with a given violation probability for wireless systems serving random arrivals. We show that if the minimal average transmit and circuit powers consumed at a base station linearly increase with the required average service rate, i.e., the power-rate relation is linear, then a non-tradeoff region will appear in the EE-delay relation. By taking multi-input-multi-output system as an example, we show that the power-rate relation will be linear if transmit power and bandwidth are jointly allocated, and bandwidth constraint is inactive to support a required delay bound. The impacts of bandwidth constraint on the power-rate and EE-delay relations are then analyzed. To study fundamental EE-delay relation, aqueue length-dependent two-state policy is optimized. By further considering a compound Poisson arrival process in large number of transmit antennas asymptotics, we find the boundary of the tradeoff and non-tradeoff regions,and provide a lower bound of the Pareto optimal EE-delay relation in the tradeoff region, all with closed-form expressions. Our results show that the non-tradeoff region increases with the maximal bandwidth and the number of transmit antennas.

Optimal EE-delay relation in wireless systems

It is widely accepted that a tradeoff exists between transmit power and average delay. In this paper, we consider wireless systems transmitting randomly arrived traffic over fading channels with statistical quality-of-service requirement, characterized by a delay bound and a delay bound violation probability. We study the relation between the maximal energy efficiency (EE) and the delay bound with given delay violation probability. We prove that the EE-delay tradeoff vanishes if the average total power consumption, including transmit and circuit powers of the base station, linearly increases with the average service/transmission rate. By taking massive multi-input-multi-output (MIMO) system as an example, we show that if the required total power consumption is a linear function of the service rate, the maximal EE is independent of the delay bound. If the required total power is strictly convex in the service rate, then the EE can be improved by extending the delay.

Joint Uplink and Downlink Resource Configuration for Ultra-Reliable and Low-Latency Communications

Supporting ultra-reliable and low-latency communications (URLLC) is one of the major goals for the fifth-generation cellular networks. Since spectrum usage efficiency is always a concern, and large bandwidth is required for ensuring stringent quality-of-service (QoS), we minimize the total bandwidth under the QoS constraints of URLLC. We first propose a packet delivery mechanism for URLLC. To reduce the required bandwidth for ensuring queueing delay, we consider a statistical multiplexing queueing mode, where the packets to be sent to different devices are waiting in one queue at the base station, and broadcast mode is adopted in downlink transmission. In this way, downlink bandwidth is shared among packets of multiple devices. In uplink transmission, orthogonal subchannels are allocated to different devices to avoid strong interference. Then, we jointly optimize uplink and downlink bandwidth configuration and delay components to minimize the total bandwidth required to guarantee the overall packet loss and end-to-end delay, which includes uplink and downlink transmission delays, queueing delay, and backhaul delay. We propose a two-step method to find the optimal solution. Simulation and numerical results validate our analysis and show remarkable performance gain by jointly optimizing uplink and downlink configuration.