6 research outputs found
On the capacity of rate adaptive modulation systems over fading channel
Ph.DDOCTOR OF PHILOSOPH
Selective AP-sequence Based Indoor Localization without Site Survey
In this paper, we propose an indoor localization system employing ordered
sequence of access points (APs) based on received signal strength (RSS). Unlike
existing indoor localization systems, our approach does not require any
time-consuming and laborious site survey phase to characterize the radio
signals in the environment. To be precise, we construct the fingerprint map by
cutting the layouts of the interested area into regions with only the knowledge
of positions of APs. This can be done offline within a second and has a
potential for practical use. The localization is then achieved by matching the
ordered AP-sequence to the ones in the fingerprint map. Different from
traditional fingerprinting that employing all APs information, we use only
selected APs to perform localization, due to the fact that, without site
survey, the possibility in obtaining the correct AP sequence is lower if it
involves more APs. Experimental results show that, the proposed system achieves
localization accuracy < 5m with an accumulative density function (CDF) of 50%
to 60% depending on the density of APs. Furthermore, we observe that, using all
APs for localization might not achieve the best localization accuracy, e.g. in
our case, 4 APs out of total 7 APs achieves the best performance. In practice,
the number of APs used to perform localization should be a design parameter
based on the placement of APs.Comment: VTC2016-Spring, 15-18 May 2016, Nanjing, Chin
Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning
Recently, the reconfigurable intelligent surface (RIS), benefited from the
breakthrough on the fabrication of programmable meta-material, has been
speculated as one of the key enabling technologies for the future six
generation (6G) wireless communication systems scaled up beyond massive
multiple input multiple output (Massive-MIMO) technology to achieve smart radio
environments. Employed as reflecting arrays, RIS is able to assist MIMO
transmissions without the need of radio frequency chains resulting in
considerable reduction in power consumption. In this paper, we investigate the
joint design of transmit beamforming matrix at the base station and the phase
shift matrix at the RIS, by leveraging recent advances in deep reinforcement
learning (DRL). We first develop a DRL based algorithm, in which the joint
design is obtained through trial-and-error interactions with the environment by
observing predefined rewards, in the context of continuous state and action.
Unlike the most reported works utilizing the alternating optimization
techniques to alternatively obtain the transmit beamforming and phase shifts,
the proposed DRL based algorithm obtains the joint design simultaneously as the
output of the DRL neural network. Simulation results show that the proposed
algorithm is not only able to learn from the environment and gradually improve
its behavior, but also obtains the comparable performance compared with two
state-of-the-art benchmarks. It is also observed that, appropriate neural
network parameter settings will improve significantly the performance and
convergence rate of the proposed algorithm.Comment: 12 pages. Accepted by IEEE JSAC special issue on Multiple Antenna
Technologies for Beyond 5
Subcarrier Sensing for Distributed OFDMA in Powerline Communication
Abstract—Powerline communication (PLC) is a preferred choice for smart home network. In this paper, a new system structure is proposed for PLC, which is based on distributed orthogonal frequency division multiple access (DOFDMA). Sub-carrier sensing, i.e., sensing every OFDM subcarrier to see if it is occupied or not, is proposed to replace the conventional carrier sensing multiple access (CSMA) for multi-user contention of a channel. This structure, borrowed from cognitive radio, allows multiple users to opportunistically share the same channel on different subcarriers and therefore increases the channel capacity. Two subcarrier sensing methods are proposed: one is based on information theory and the other is based on successive energy comparison. Simulations are provided to verify the methods. I
System throughput analysis of rate adaptive TDMA system supporting two class services
10.1007/s11276-005-3523-8Wireless Networks116687-695WINE