Daosen Zhai

RESP: A k-connected residual energy-aware topology control algorithm for ad hoc networks

Most of previous topology control algorithms that aim to extend the network lifetime focus only on the energy consumption of transmissions, and thus construct a static topology without adaptation to the varying energy consumption rates at different nodes. As a result, the network lifetime has not been prolonged to the most extent as expected. However, other topology control algorithms that consider the residual energy levels of nodes have not addressed the problem of fault tolerance. In this paper, we propose an adaptive topology control algorithm, Residual Energy-aware Shortest Path (RESP), which not only balances the energy consumption of different nodes but also provides fault tolerance. Particularly, RESP is able to ensure k-edge connectivity and preserve the minimum-weight path. Simulation results show that RESP extends the network lifetime and is superior to other existing localized fault-tolerant algorithms.

Achieving Bi-Channel-Connectivity with Topology Control in Cognitive Radio Networks

In cognitive radio networks (CRNs), secondary users (SUs) must vacate the spectrum when it is reclaimed by the primary users (PUs). As such, multiple SUs transmitting on the same channel will be affected when the channel is requested by the PUs, thereby resulting in a possible network partition of CRNs. Therefore, how to maintain the connectivity of CRNs considering the activity of PUs is a critical problem. In this paper, we propose a centralized and a distributed topology control algorithm respectively to address this problem. Particularly, we combine power control and channel assignment to construct a bi-channel-connected and conflict-free topology using the minimum number of channels. In the power control phase, we tailor the topology for the channel assignment in the second phase. In the channel assignment phase, we utilize the graph coloring algorithm to achieve conflict-free transmission by assigning a channel to each SU. Theoretical analysis and simulation study show that the derived topology can maintain connectivity in the event of any single channel interruption by PUs. Simulation results also demonstrate that the proposed algorithms can efficiently reduce the average number of required channels for achieving bi-channel-connectivity and conflict-free transmission and ensure that the minimum power paths in the original network preserved in the final topology.

Rate and Energy Maximization in SCMA Networks With Wireless Information and Power Transfer

In this letter, we investigate the fundamental tradeoff between rate and energy for sparse code multiple access (SCMA) networks with wireless power transfer. A weighted rate and energy maximization problem by jointly considering power allocation, codebook assignment, and power splitting, is formulated. To solve the hard problem, an iterative algorithm based on the univariate search technique is proposed, which has good performance with low complexity. Specifically, we analyze the special structure of the problem and exploit it to obtain the optimal power splitting ratio and resource allocation strategy when one of them is fixed. Simulation results indicate that our algorithm achieves a better rate-energy tradeoff compared to other schemes.

Leakage-Aware Dynamic Resource Allocation in Hybrid Energy Powered Cellular Networks

Energy harvesting is a promising technique to reduce conventional grid energy consumption, which caters for 5G visions on the green evolution of current cellular networks. To fully exploit the harvested energy, an inefficient factor caused by the battery leakage must be taken into account to tackle the energy dissipation problem, which triggers a new dimensional optimization related to the transmission time. However, most approaches are studied for perfect battery models and neglect the optimization for the transmission time. In this paper, we formulate the battery leakage process into our model to explore the grid energy conservation problem by jointly considering admission control, power allocation, subcarrier assignment, and transmission time determination in cellular networks powered by grid and renewable energy. To tackle this problem, we exploit the Lyapunov optimization technique to develop an online algorithm, referred to as leakage-aware dynamic resource allocation policy (LADRA). Specifically, the LADRA only needs to track the current system states (e.g., channel and energy conditions) but without requiring their prior-knowledge. Furthermore, we prove that the minimum grid energy consumption value can be achieved by our proposed algorithm asymptotically. Simulation results verify the correctness of the theoretical analysis, as well as exhibit the performance improvement against other algorithms in terms of grid energy consumption and queue backlog.

Intelligent Energy and Traffic Coordination for Green Cellular Networks With Hybrid Energy Supply

In energy-harvesting-enabled networks, the intermittent and randomly distributed renewable energy imposes severe challenges in reliably supplying the time-varying mobile traffic. To tackle this issue, we reshape the spatial renewable energy and mobile traffic by exploiting the approach of energy sharing and load shifting, with the objective of minimizing the grid energy expenditure of cellular networks powered by both grid and renewable energy. We formulate this problem as a mixed-integer nonlinear programming, which is proved to be NP-hard. For centralized networks, we first devise a cost-efficient centralized algorithm leveraging the univariate search technique, which can find the near-optimal solutions with the advantages of low complexity and fast convergence. Specifically, by jointly optimizing the spatial distribution of renewable energy and mobile traffic, the centralized algorithm achieves a good match between the renewable energy supply and the total energy demand at each base station (BS), such that the grid energy expenditure of the whole network is greatly reduced. For distributed networks, we further propose a three-phase distributed control policy in which BSs and mobile users adjust their strategies independently only with their local information. Finally, we present extensive simulations to investigate the convergence and effectiveness of our proposed algorithms and demonstrate the achieved energy conservation gain compared with the existing schemes.

Energy-Saving Resource Management for D2D and Cellular Coexisting Networks Enhanced by Hybrid Multiple Access Technologies

In this paper, we investigate the energy-saving resource management problem for a new device-to-device (D2D) and cellular coexisting network, where D2D users employ orthogonal frequency division multiple access (OFDMA) and cellular users employ sparse code multiple access (SCMA). This hybrid network can support massive connectivity by exploiting the degrees of freedom in code and space domains, however, the complicated spectrum sharing pattern also leads to serious interference, which further boosts the power consumption of mobile devices (MDs). To tackle this problem, we propose a unified resource management scheme to minimize the total transmit power of all MDs by jointly optimizing mode selection, resource allocation, and power control. First, we analytically get the optimal resource-sharing mode (dedicated mode or reuse mode) for cellular users and D2D users based on the mapping rule between SCMA codebooks and OFDMA resource blocks. For each resource-sharing mode, we reformulate the resource management problems as classical problems in graph theory, and then devise efficient algorithms leveraging the special structure of the constructed graphs. Finally, simulation studies indicate that the network capacity is upgraded with the hybrid multiple access technologies, and the energy efficiency performance is also enhanced through the unified resource management.

Joint Codebook Design and Assignment for Detection Complexity Minimization in Uplink SCMA Networks

To improve the spectrum efficiency (SE), sparse code multiple access (SCMA) has been proposed as an candidate for 5G wireless networks. Although SCMA has good SE performance, it suffers from high detection complexity, which may degrade its energy efficiency (EE) performance. To make up for this deficiency, we in this paper jointly consider codebook design (i.e., mapping matrix and constellation graph design) and codebook assignment to investigate the detection complexity minimization problem for uplink SCMA networks. To tackle this hard problem effectively, we first borrow the idea of dual coordinate search to devise a cost-efficient algorithm to determine the mapping matrix and codebook assignment. Based on the mapping matrix, we exploit the multi-dimensional modulation characteristic of SCMA to carefully design the constellations for each codebook to further reduce the detection complexity. Finally, we present some simulations to illustrate the performance gain of our proposed algorithm as compared with other schemes.

Cost-Efficient Codebook Assignment and Power Allocation for Energy Efficiency Maximization in SCMA Networks

In this paper, we investigate the energy-efficient transmission problem by resource allocation in SCMA networks. We formulate it as an optimization problem to maximize the network energy efficiency (EE) subject to quality-of-service (QoS) requirements, codebook assignment, power allocation, and subcarrier reuse constraints. Due to its mixed combinatory, we separate codebook assignment and power allocation to devise suboptimal but cost- efficient algorithms. With power equally distributed, we first propose a novel scheme to assign codebooks. We then develop a derivative- bisection based algorithm to optimally solve the resultant power allocation problem by exploiting its quasiconcave structure. Simulation results exhibit the superiority of the proposed algorithms against the existing classical schemes and of SCMA over OFDMA in terms of the network EE.

Resource management for D2D underlaying cellular network with hybrid multiple access technologies

This paper investigates the resource management problem for device-to-device (D2D) underlaying cellular network. In particular, cellular users employ sparse code multiple access (SCMA) while D2D users employ orthogonal frequency division multiple access (OFDMA). In this system, the cross-tier interference between cellular users and D2D users is highly coupled and if not properly handled, the potentials of the two 5G key enabling technologies (i.e., SCMA and D2D) cannot be fully exploited. To tackle this problem, we first construct an interference graph to depict the cross-tier interference, based on which an efficient resource allocation algorithm is devised to well coordinate the interference. Then, we propose an easily implemented iterative power control scheme to optimize the transmit power of all users. Finally, simulation results exhibit the performance gain of our algorithms as compared with other schemes.