Abstract

A femtocell is a small cellular base station (BS), typically used for serving approved users within a small coverage. In this paper, we investigate the problem of data multicast in femtocell networks that incorporates superposition coding (SC) and successive interference cancellation (SIC). The problem is to decide the transmission schedule for each BS, as well as the power allocation for the SC layers, to achieve a sufficiently large SNR for each layer to be decodable with SIC. The objective is to minimize the total BS power consumption. We formulate a Mixed Integer Nonlinear Programming (MINLP) problem, which is NP-hard in general. We then reformulate the problem into a simpler form, and derive upper and lower performance bounds. Finally, we consider three typical connection scenarios in the femtocell network, and develop optimal and near-optimal algorithms for the three scenarios. The proposed algorithms have low computational complexity, and outperform a heuristic scheme with considerable gains in our simulation study.

Highlights

  • A femtocell is a small cellular base station (BS), typically used for serving approved users within a small coverage

  • We investigate the problem of multicasting data in femtocell networks

  • We focus on a multicast scenario, where the macro base station (MBS) and femto base stations (FBS)’s multicast a data file to the K users

Read more

Summary

Introduction

A femtocell is a small cellular base station (BS), typically used for serving approved users within a small coverage (e.g., a house). We investigate the problem of multicasting data in femtocell networks. We adopt superposition coding (SC) and successive interference cancellation (SIC), two wellknown physical layer (PHY) techniques, for data multicast in femtocell networks [10]. We adopt SC and SIC for the unique femtocell network environment, and investigate how to enable efficient data multicast from the femtocells to multiple users. Each user connects to either the MBS or an FBS and uses SIC to decode the received compound signal. The problem is to decide the transmission schedule for each BS, as well as the power allocation for the SC layers, such that a sufficiently large SNR is achieved for each layer to be decodable with SIC at each user.

System Model
Problem Statement
Reformulation and Power Allocation
Problem Reformulation
Performance Bounds
A Simple Heuristic Scheme
Power Allocation Algorithms
Related Work
Findings
Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call