Computation Offloading for IoT in C-RAN: Optimization and Deep Learning

by   Chandan Pradhan, et al.

We consider computation offloading for Internet-of-things (IoT) applications in multiple-input-multiple-output (MIMO) cloud-radio-access-network (C-RAN). Due to the limited battery life and computational capability in the IoT devices (IoTDs), the computational tasks of the IoTDs are offloaded to a MIMO C-RAN, where a MIMO radio resource head (RRH) is connected to a baseband unit (BBU) through a capacity-limited fronthaul link, facilitated by the spatial filtering and uniform scalar quantization. We formulate a computation offloading optimization problem to minimize the total transmit power of the IoTDs while satisfying the latency requirement of the computational tasks, and find that the problem is non-convex. To obtain a feasible solution, firstly the spatial filtering matrix is locally optimized at the MIMO RRH. Subsequently, we leverage the alternating optimization framework for joint optimization on the residual variables at the BBU, where the baseband combiner is obtained in a closed-form, the resource allocation sub-problem is solved through successive inner convexification, and the number of quantization bits is obtained by a line-search method. As a low-complexity approach, we deploy a supervised deep learning method, which is trained with the solutions to our optimization algorithm. Numerical results validate the effectiveness of the proposed algorithm and the deep learning method.


Power-Efficient Resource Allocation in Massive MIMO Aided Cloud RANs

This paper considers the power-efficient resource allocation problem in ...

Random Access-based Multiuser Computation Offloading for Devices in IoT Applications

In various Internet-of-Things (IoT) applications, a number of devices an...

Joint Computation Offloading and Resource Allocation in Cloud Based Wireless HetNets

In this paper, we study the joint computation offloading and resource al...

Joint Precoding Design and Resource Allocation for C-RAN Wireless Fronthaul Systems

This paper investigates the resource allocation problem combined with fr...

Secure and Multi-Step Computation Offloading and Resource Allocation in Ultra-Dense Multi-Task NOMA-Enabled IoT Networks

Ultra-dense networks are widely regarded as a promising solution to expl...

Optimizing Information Freshness in RIS-assisted NOMA-based IoT Networks

This paper investigates the benefits of integrating reconfigurable intel...

Timeliness of Information for Computation-intensive Status Updates in Task-oriented Communications

Moving beyond just interconnected devices, the increasing interplay betw...

Please sign up or login with your details

Forgot password? Click here to reset