744 research outputs found
Blind Estimation of Multiple Carrier Frequency Offsets
Multiple carrier-frequency offsets (CFO) arise in a distributed antenna
system, where data are transmitted simultaneously from multiple antennas. In
such systems the received signal contains multiple CFOs due to mismatch between
the local oscillators of transmitters and receiver. This results in a
time-varying rotation of the data constellation, which needs to be compensated
for at the receiver before symbol recovery. This paper proposes a new approach
for blind CFO estimation and symbol recovery. The received base-band signal is
over-sampled, and its polyphase components are used to formulate a virtual
Multiple-Input Multiple-Output (MIMO) problem. By applying blind MIMO system
estimation techniques, the system response is estimated and used to
subsequently transform the multiple CFOs estimation problem into many
independent single CFO estimation problems. Furthermore, an initial estimate of
the CFO is obtained from the phase of the MIMO system response. The Cramer-Rao
Lower bound is also derived, and the large sample performance of the proposed
estimator is compared to the bound.Comment: To appear in the Proceedings of the 18th Annual IEEE International
Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC),
Athens, Greece, September 3-7, 200
On bounds and algorithms for frequency synchronization for collaborative communication systems
Cooperative diversity systems are wireless communication systems designed to
exploit cooperation among users to mitigate the effects of multipath fading. In
fairly general conditions, it has been shown that these systems can achieve the
diversity order of an equivalent MISO channel and, if the node geometry
permits, virtually the same outage probability can be achieved as that of the
equivalent MISO channel for a wide range of applicable SNR. However, much of
the prior analysis has been performed under the assumption of perfect timing
and frequency offset synchronization. In this paper, we derive the estimation
bounds and associated maximum likelihood estimators for frequency offset
estimation in a cooperative communication system. We show the benefit of
adaptively tuning the frequency of the relay node in order to reduce estimation
error at the destination. We also derive an efficient estimation algorithm,
based on the correlation sequence of the data, which has mean squared error
close to the Cramer-Rao Bound.Comment: Submitted to IEEE Transaction on Signal Processin
Channel Estimation for MIMO MC-CDMA Systems
The concepts of MIMO MC-CDMA are not new but the new technologies to improve
their functioning are an emerging area of research. In general, most mobile
communication systems transmit bits of information in the radio space to the
receiver. The radio channels in mobile radio systems are usually multipath
fading channels, which cause inter-symbol interference (ISI) in the received
signal. To remove ISI from the signal, there is a need of strong equalizer. In
this thesis we have focused on simulating the MIMO MC-CDMA systems in MATLAB
and designed the channel estimation for them
Random Access in Massive MIMO by Exploiting Timing Offsets and Excess Antennas
Massive MIMO systems, where base stations are equipped with hundreds of
antennas, are an attractive way to handle the rapid growth of data traffic. As
the number of user equipments (UEs) increases, the initial access and handover
in contemporary networks will be flooded by user collisions. In this paper, a
random access protocol is proposed that resolves collisions and performs timing
estimation by simply utilizing the large number of antennas envisioned in
Massive MIMO networks. UEs entering the network perform spreading in both time
and frequency domains, and their timing offsets are estimated at the base
station in closed-form using a subspace decomposition approach. This
information is used to compute channel estimates that are subsequently employed
by the base station to communicate with the detected UEs. The favorable
propagation conditions of Massive MIMO suppress interference among UEs whereas
the inherent timing misalignments improve the detection capabilities of the
protocol. Numerical results are used to validate the performance of the
proposed procedure in cellular networks under uncorrelated and correlated
fading channels. With UEs that may simultaneously become active
with probability 1\% and a total of frequency-time codes (in a given
random access block), it turns out that, with antennas, the proposed
procedure successfully detects a given UE with probability 75\% while providing
reliable timing estimates.Comment: 30 pages, 6 figures, 1 table, submitted to Transactions on
Communication
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