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Cloud-RAN (C-RAN) is a promising network architecture to provide 5G broadband services. In C-RAN, the base stations (BSs) are separated as the computation entities (i.e., Baseband Units (BBUs) ) and the radio entities (i.e., Remote Radio Heads (RRHs) ), where the BBUs are put in a centralized cloud to realize centrally control and the RRH are left at cell sites for signal transmission. With C-RAN, multiple collaborative cells can transmit data to user equipments (UEs) by Joint Transmission (JT) technology to improve network efficiency. On the other hand, 3GPP standard has defined the Discontinuous Reception (DRX) mechanism, which allows UEs to turn off their radio interfaces periodically to save their energy. However, how to cooperate DRX with JT under the C-RAN architecture is still an open issue. Therefore, this letter studies how to optimize UEs’ DRX parameters while considering their quality-of-service (QoS) in C-RAN with JT. To solve this problem, we propose an energy-efficient JT scheduling scheme. The main idea of our scheme is to well pair UEs and BSs with the consideration of joint transmission quality and then optimizes DRX parameters to further save energy. Extensive simulation results show that our scheme can improve system throughput, well utilize resource and save UEs’ energy consumption.

Software defined network (SDN) provides flexible and scalable routing by separating control plane and data plane. With centralized control, SDN has been widely used in traffic engineering, link failure recovery, and load balancing. This work considers the flow update problem, where a set of flows need to be migrated or rearranged due to change of network status. During flow update, efficiency and consistency are two main challenges. Efficiency refers to how fast these updates are completed, while consistency refers to prevention of blackholes , loops , and network congestions during updates. This paper proposes a scheme that maintains all these properties. It works in four phases. The first phase partitions flows into shorter routing segments to increase update parallelism. The second phase generates a global dependency graph of these segments to be updated. The third phase conducts actual updates and then adjusts dependency graphs accordingly. The last phase deals with deadlocks, if any, and then loops back to phase three if necessary. Through simulations, we validate that our scheme not only ensures freedom of blackholes, loops, congestions, and deadlocks during flow updates, but is also faster than existing schemes.

For next-generation wireless communications, the 3GPP Long Term Evolution-Advanced (LTE-A) is the most promising technology which provides transmission rate up to 1 Gbps and supports various broadband multimedia services, such as IPTV and Voice/Video-over-IP services. To reduce the energy consumption of user equipments (UEs) , the LTE-A standard defines the Discontinuous Reception Mechanism (DRX) to allow UEs to turn off their radio interfaces and go to sleep when no data needs to be received. However, how to optimally configure DRX for UEs is still left as an open issue. In this paper, we address the DRX optimization problem for multicast services. This problem asks how to guarantee the quality of service (QoS) of the multicast streams under the Evolved Node B (eNB) while minimizing the UEs’ wake-up time. We prove this problem to be NP-complete and propose an energy-efficient heuristic. This heuristic consists of two phases. The first phase tries to aggregate the required bandwidth of the multicast streams for UEs to reduce their wake-up periods. The second phase further minimizes UEs’ unnecessary wake-up periods by optimizing their DRX configurations. Extensive simulation results show that our scheduling is close to the optimum in most cases.

With the design of data communications in mind, 3GPP LTE-advanced (LTE-A) is probably the most promising technology for Internet of Things (IoT). For IoT applications, continuous low-rate streaming data may be reported from devices over a long period of time, imposing stringent requirements on power saving. To manage power consumption, 3GPP LTE-A has defined the discontinuous reception/transmission (DRX/DTX) mechanism to allow devices to turn off their radio interfaces and go to sleep in various patterns. Existing literature has paid much attention to evaluate the performance of DRX/DTX; however, how to tune DRX/DTX parameters to optimize energy cost is still left open. This paper addresses the DRX/DTX optimization, by asking how to maximize the sleep periods of devices while guarantee their quality-of-service (QoS), especially on the aspects of traffic bit-rate, packet delay, and packet loss rate in IoT applications. Efficient schemes to optimize DRX/DTX parameters and schedule devices' packets with the base station are proposed. The key idea of our schemes is to balance the impacts between QoS parameters and DRX/DTX configurations. Simulation results show that our schemes can guarantee traffic bit-rate, packet delay, and packet loss rate while save energy of user equipments .

The Orthogonal Frequency Division Multiple Access (OFDMA) technique has been widely applied in broadband wireless networks, such as IEEE 802.16 (WiMAX) and 3GPP Long Term Evolution (LTE). Existing studies have targeted at improving network throughput by increasing the transmission rates of mobile stations (MSs). Nevertheless, this is at the cost of higher energy consumption of MSs. In the letter, we consider the tile-and-energy joint allocation problem for uplink transmissions in an OFDMA wireless network. We formulate this problem as a mixed integer programming, where the objective is to minimize MSs' energy consumption subject to satisfying their traffic demands. We show this to be NP-hard and develop a heuristic taking advantage of the water-filling technique. Simulation results show that the performance of our heuristic is close to the optimum, especially when the network is under non-saturated condition.