Shichao Li

Delay-Aware Dynamic Resource Management for High-Speed Railway Wireless Communications

In this paper, we investigate the delay-aware dynamic resource management problem for multi- service transmission in high-speed railway wireless communications, with a focus on resource allocation among the services and power control along the time. By taking account of average delay requirements and power constraints, the considered problem is formulated into a stochastic optimization problem, rather than pursuing the traditional convex optimization means. Inspired by Lyapunov optimization theory, the intractable stochastic optimization problem is transformed into a tractable deterministic optimization problem, which is a mixed-integer resource management problem. By exploiting the specific problem structure, the mixed-integer resource management problem is equivalently transformed into a single variable problem, which can be effectively solved by the golden section search method with guaranteed global optimality. Finally, we propose a dynamic resource management algorithm to solve the original stochastic optimization problem. Simulation results show the advantage of the proposed dynamic algorithm and reveal that there exists a fundamental tradeoff between delay requirements and power consumption.

Robust QoS-Aware Cross-layer Design of Adaptive Modulation Transmission on OFDM Systems in High-Speed Railway

In this paper, we consider an orthogonal frequency division multiplexing communication system that adopts frame-by-frame transmission in high-speed railway (HSR) scenario. Due to the increase in demand for the QoS sensitive services, an efficient QoS-aware transmission strategy that improves the system performance is required urgently. Many efforts have been devoted to addressing this problem with the assumption of block fading channel in a frame duration. However, due to the frequent channel quality variation in a frame duration and serious inter channel interference in HSR scenario, the throughput of the QoS sensitive services degrades severely. Hence, a robust cross-layer transmission strategy that combines adaptive modulation (AM) scheme with truncated automatic repeat request protocol is proposed. In this cross-layer formulation, the normalized average throughput is optimized subject to the average power and the packet loss rate (PLR) requirements. First, we derive the closed form average bit error rate that represents the PLR requirement at the physical layer. Second, we obtain the solution of robust AM scheme and power allocation policy in the case of continuous rate. Third, we present the adaptive bits and power allocation scheme in the case of discrete rate, which can be implemented in practice. Finally, the performance of the proposed transmission strategy is evaluated by extensive simulations. Comparing with the constant transmit power AM scheme, the throughput increases by 20%, which demonstrates that the proposed robust cross-layer design is suitable for the HSR communication systems.

Adaptive modulation transmission in high speed railway environment with QoS provisioning

Robust adaptive modulation (AM) is a promising technique to improve the spectrum efficiency (SE) of high speed railway (HSR) communication system. Although robust AM transmission schemes with assumption of block fading channel have been extensively investigated, which are no longer valid in the fast time-varying channel due to the channel variation in frame duration. This paper investigates the optimum of AM transmission schemes design with different bit-error rate (BER) criteria for maximizing SE in HSR communication system. We propose a variable rate and variable power modulation scheme in a normal HSR environment, in which the closed-form expression of the power allocation policy is derived. Furthermore, considering the extract coverage requirements in a higher mobility scenario and different BER requirements, we propose two constant power and variable rate transmission schemes with probability BER constraint and average BER constraint. The effectiveness of the proposed AM transmission schemes are validated by extensive simulations. The effects of channel quality and Doppler shift on the performance of the proposed AM transmission schemes are evaluated.

Resource Allocation with Multiple QoS Constraints in OFDMA-Based Cloud Radio Access Network

Due to the spread of mobile Internet and development of many new multimedia applications, there are much different quality-of-service (QoS) requirements of users in fifth generation (5G) communication system. In this paper, we consider two types of users with different QoS requirements in OFDMA based cloud radio access network (C-RAN). One type QoS requirements of users are joint bit error rate (BER) and data rate (type I users), and the other type is the data rate (type II users). We formulate the resource allocation problem in OFDMA-based C-RAN, the problem is maximal weighted sum rate for type II users subject to the QoS requirements of type I users and the fronthaul capacity constraint. Since the formulated problem is a non-convex problem, two subproblems are reformulated firstly, and then based on the CPLEX package, time-sharing and alternating methods, we proposed an iterative algorithm. Simulation results confirm that the proposed algorithm can achieve good performance.

Robust QoS-Aware Multi-Service Transmission with Hierarchical Modulation in High-Speed Railway

Adaptive hierarchical modulation is an effective technique to improve the spectral efficiency for multi-service transmission in high-speed railway (HSR) communication systems. Many efforts have been devoted to studying this technique with the perfect channel state information (CSI) assumption. However, the fast time-varying fading channels and feedback delay lead that the perfect CSI cannot be obtained in HSR scenario. Therefore, the performance of the existing non-robust hierarchical modulation schemes degrades severely. This paper proposes a robust adaptive hierarchical modulation scheme, which can bear multiple services in one symbol with different QoS requirements. The closed form bit error rate (BER) expressions of the robust hierarchical modulation scheme are derived, then the adaptive transmission strategy of the HSR communication system is designed. Finally, the performance of the robust hierarchical modulation scheme is evaluated by extensive simulations. Comparing with the uniform modulation scheme, the overall spectral efficiency increases by 15% when the train is at 500 km/h.

Energy Efficiency and Capacity Tradeoff in Cloud Radio Access Network of High-Speed Railways

To meet the increasing demand of high-data-rate services of high-speed railway (HSR) passengers, cloud radio access network (C-RAN) is proposed. This paper investigates the tradeoff between energy efficiency (EE) performance and capacity in C-RAN of HSR. Considering that the train location can be predicted, we propose a predictable path loss based time domain power allocation method (PPTPA) to improve EE performance of HSR communication system. First, we consider that the communication system of HSR only bears the passenger information services (PISs). The energy-efficient power allocation problem with delay constraint is studied. The formulated problem is nonconvex. To deal with it, an equivalent convex problem is reformulated. Based on PPTPA, we propose an iterative algorithm to improve the EE performance. Second, we consider that the PISs and the train control services (TCSs) are all bore. A capacity optimization problem with joint EE and services transmission delay constraints is formulated. Based on PPTPA, we propose a hybrid power allocation scheme to improve the capacity of the system. Finally, we analyze the effect of small-scale fading on EE performance. The effectiveness of the proposed power allocation algorithm is validated by HSR channel measurement trace based emulation results and extensive simulation results.

Energy-Efficient Power Allocation in Cloud Radio Access Network of High-Speed Railway

To meet the increasing demand of high-data-rate services of high-speed railway (HSR) passengers, cloud radio access network (C-RAN) is a promising technique in mobile communication system of HSR. In this paper, we focus on the energy-efficient power allocation problem for providing the high- data- rate services in HSR scenario. Based on the predicted path loss characteristic of HSR, the power allocation is formulated as a non-linear fractional programming problem. The service pro- cessing delay of baseband unit (BBU) pool and radio transmission delay at radio remote units (RRUs) are considered in the services transmission delay constraint. The formulated problem is a non- convex problem, an equivalent convex problem is reformulated firstly, and then propose an iterative algorithm to obtain the optimal power allocation solution. Furthermore, we analyze the effect of small-scale fading on energy-efficiency (EE) performance of the proposed power allocation scheme. Simulation results confirm that the proposed energy-efficient power allocation policy can meet the QoS of passengers and obtain the optimal EE performance.

Cross-Layer Resource Management in Software Defined Ultra Dense Wireless Networks

This paper focuses on the energy management problem of ultra dense wireless networks. The work modes of small cells are controlled by the software defined approach to reduce the system energy consumption. Considering the quality of service (QoS) requirements of users and coverage ratio requirement, the energy minimization problem are formulated as a mixedinteger nonlinear programming (MINLP) problem. To deal with this problem, we utilize the sparse character of the beamforming vector and the method of reweighted l1 norm to approximate l0 norm. Because the coverage ratio requirement constraint is still non-convex, we proposed a heuristic iterative algorithm to obtain a practical solution. Simulation results show that the proposed heuristic algorithm can achieve good performance compared with the conventional sparsity (SP) based algorithm.