3,245 research outputs found
Diversity techniques for blind channel equalization in mobile communications
A blind algorithm for channel distortion compensation is presented which can be employed in spatial or temporal diversity receivers. The proposed technique can be used in frequency selective and frequency flat fading mobile channels, using burst transmission schemes in the first case and OFDM modulation in the second one. The algorithm is base on a deterministic criteria and is suited for estimation when short sets of data are available.Peer ReviewedPostprint (published version
Turbo Packet Combining for Broadband Space-Time BICM Hybrid-ARQ Systems with Co-Channel Interference
In this paper, efficient turbo packet combining for single carrier (SC)
broadband multiple-input--multiple-output (MIMO) hybrid--automatic repeat
request (ARQ) transmission with unknown co-channel interference (CCI) is
studied. We propose a new frequency domain soft minimum mean square error
(MMSE)-based signal level combining technique where received signals and
channel frequency responses (CFR)s corresponding to all retransmissions are
used to decode the data packet. We provide a recursive implementation algorithm
for the introduced scheme, and show that both its computational complexity and
memory requirements are quite insensitive to the ARQ delay, i.e., maximum
number of ARQ rounds. Furthermore, we analyze the asymptotic performance, and
show that under a sum-rank condition on the CCI MIMO ARQ channel, the proposed
packet combining scheme is not interference-limited. Simulation results are
provided to demonstrate the gains offered by the proposed technique.Comment: 12 pages, 7 figures, and 2 table
SGD Frequency-Domain Space-Frequency Semiblind Multiuser Receiver with an Adaptive Optimal Mixing Parameter
A novel stochastic gradient descent frequency-domain (FD) space-frequency (SF) semiblind multiuser receiver with an adaptive optimal mixing parameter is proposed to improve performance of FD semiblind multiuser receivers with a fixed mixing parameters and reduces computational complexity of suboptimal FD semiblind multiuser receivers in SFBC downlink MIMO MC-CDMA systems where various numbers of users exist. The receiver exploits an adaptive mixing parameter to mix information ratio between the training-based mode and the blind-based mode. Analytical results prove that the optimal mixing parameter value relies on power and number of active loaded users existing in the system. Computer simulation results show that when the mixing parameter is adapted closely to the optimal mixing parameter value, the performance of the receiver outperforms existing FD SF adaptive step-size (AS) LMS semiblind based with a fixed mixing parameter and conventional FD SF AS-LMS training-based multiuser receivers in the MSE, SER and signal to interference plus noise ratio in both static and dynamic environments
A Two-Phase Maximum-Likelihood Sequence Estimation for Receivers with Partial CSI
The optimality of the conventional maximum likelihood sequence estimation
(MLSE), also known as the Viterbi Algorithm (VA), relies on the assumption that
the receiver has perfect knowledge of the channel coefficients or channel state
information (CSI). However, in practical situations that fail the assumption,
the MLSE method becomes suboptimal and then exhaustive checking is the only way
to obtain the ML sequence. At this background, considering directly the ML
criterion for partial CSI, we propose a two-phase low-complexity MLSE
algorithm, in which the first phase performs the conventional MLSE algorithm in
order to retain necessary information for the backward VA performed in the
second phase. Simulations show that when the training sequence is moderately
long in comparison with the entire data block such as 1/3 of the block, the
proposed two-phase MLSE can approach the performance of the optimal exhaustive
checking. In a normal case, where the training sequence consumes only 0.14 of
the bandwidth, our proposed method still outperforms evidently the conventional
MLSE.Comment: 5 pages and 4 figure
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