IoT devices, which possess limited battery capacity and computing capabilities, are unable to meet many applications’ demands. The integration of wireless power transfer and edge computing has emerged as a promising solution for this problem. Nevertheless, efficiently making offloading decisions and allocating resources pose significant challenges, particularly in the scenarios of multiple access points (APs). This paper focuses on optimizing the sum computation rate (SCR) in a wireless powered network having multiple APs. The devices work in binary offloading, operating under frequency-division multiple access (FDMA) and time-division multiple access (TDMA), respectively. To efficiently address these two mixed-integer nonlinear programming problems, a deep reinforcement learning based algorithm is employed to determine the near-optimal offloading decisions. Additionally, under the given offloading decision, we present an algorithm using the golden section search for FDMA to obtain the subsequent optimal time allocation, and apply convex optimization algorithm to obtain the optimal time allocation for TDMA. Our algorithms achieve over 95 percent of the maximum SCR with low complexity. In comparison to the baseline algorithms, our proposed algorithms exhibit advantages in terms of convergence speed and attained SCR.

Recently, network coding has been applied to reliable multicast in wireless networks for packet loss recovery, resulting in significant bandwidth savings. In network-coding-based multicast schemes, once a receiver receives one packet from the source it sends an ACK to acknowledge packet receipt. Such acknowledgment mechanism has the following limitation: when an ACK from one receiver is lost, the source considers the corresponding packet to be lost at this receiver and then conducts unnecessary retransmission. Motivated by this basic observation, we first propose a block-based acknowledgment mechanism, where an ACK now acknowledges all previously received packets in the current block such that the later received ACKs can offset the loss of previous ACKs. To reduce the total amount of feedback overhead, we further propose a more simple feedback mechanism, in which the receivers only start to send acknowledgments from the last two packets (not from the first one as in the first mechanism) of the current block. The first mechanism has the potential to achieve better performance over the latter one in wireless networks with long deep fades (i.e., continuous packet losses) due to its continuous transmissions of ACKs, while the second one is more promising for wireless networks with only random packet losses due to its smaller amount of feedback. Both theoretical and simulation results demonstrate that, compared to the current acknowledgment mechanism in network-coding-based reliable multicast schemes, these two mechanisms can achieve much higher bandwidth efficiency.

Recently, a promising packet forwarding architecture COPE was proposed to essentially improve the throughput of multihop wireless networks, where each network node can intelligently encode multiple packets together and forward them in a single transmission. However, COPE is still in its infancy and has the following limitations: (1) COPE adopts the FIFO packet scheduling and thus does not provide different priorities for different types of packets. (2) COPE simply classifies all packets destined to the same nexthop into small-size or large-size virtual queues and examines only the head packet of each virtual queue to find coding solutions. Such a queueing structure will lose some potential coding opportunities, because among packets destined to the same nexthop at most two packets (the head packets of small-size and large-size queues) will be examined in the coding process, regardless of the number of flows. (3) The coding algorithm adopted in COPE is fast but cannot always find good solutions. In order to address the above limitations, in this paper we first present a new queueing structure for COPE, which can provide more potential coding opportunities, and then propose a new packet scheduling algorithm for this queueing structure to assign different priorities to different types of packets. Finally, we propose an efficient coding algorithm to find appropriate packets for coding. Simulation results demonstrate that this new COPE architecture can further greatly improve the node transmission efficiency.

Recently, network coding has been applied to the loss recovery of reliable multicast in wireless networks, where multiple lost packets are XOR-ed together as one packet and forwarded via single retransmission, resulting in a significant reduction of bandwidth consumption. In this paper, we first prove that maximizing the number of lost packets for XOR-ing, which is the key part of the available network coding-based reliable multicast schemes, is actually a complex NP-complete problem. To address this limitation, we then propose an efficient heuristic algorithm for finding an approximately optimal solution of this optimization problem. Furthermore, we show that the packet coding principle of maximizing the number of lost packets for XOR-ing sometimes cannot fully exploit the potential coding opportunities, and we then further propose new heuristic-based schemes with a new coding principle. Simulation results demonstrate that the heuristic-based schemes have very low computational complexity and can achieve almost the same transmission efficiency as the current coding-based high-complexity schemes. Furthermore, the heuristic-based schemes with the new coding principle not only have very low complexity, but also slightly outperform the current high-complexity ones.

Many nodes in Internet of Things (IoT) rely on batteries for power. Additionally, the demand for executing compute-intensive and latency-sensitive tasks is increasing for IoT nodes. In some practical scenarios, the computation tasks of WDs have the non-separable characteristic, that is, binary offloading strategies should be used. In this paper, we focus on the design of an efficient binary offloading algorithm that minimizes system energy consumption (EC) for TDMA-based wireless-powered multi-access edge computing networks, where WDs either compute tasks locally or offload them to hybrid access points (H-APs). We formulate the EC minimization problem which is a non-convex problem and decompose it into a master problem optimizing binary offloading decision and a subproblem optimizing WPT duration and task offloading transmission durations. For the master problem, a DRL based method is applied to obtain the near-optimal offloading decision. For the subproblem, we firstly consider the scenario where the nodes do not have completion time constraints and obtain the optimal analytical solution. Then we consider the scenario with the constraints. By jointly using the Golden Section Method and bisection method, the optimal solution can be obtained due to the convexity of the constraint function. Simulation results show that the proposed offloading algorithm based on DRL can achieve the near-minimal EC.