322 research outputs found
Green Communication via Power-optimized HARQ Protocols
Recently, efficient use of energy has become an essential research topic for
green communication. This paper studies the effect of optimal power controllers
on the performance of delay-sensitive communication setups utilizing hybrid
automatic repeat request (HARQ). The results are obtained for repetition time
diversity (RTD) and incremental redundancy (INR) HARQ protocols. In all cases,
the optimal power allocation, minimizing the outage-limited average
transmission power, is obtained under both continuous and bursting
communication models. Also, we investigate the system throughput in different
conditions. The results indicate that the power efficiency is increased
substantially, if adaptive power allocation is utilized. For instance, assume
Rayleigh-fading channel, a maximum of two (re)transmission rounds with rates
nats-per-channel-use and an outage probability constraint
. Then, compared to uniform power allocation, optimal power
allocation in RTD reduces the average power by 9 and 11 dB in the bursting and
continuous communication models, respectively. In INR, these values are
obtained to be 8 and 9 dB, respectively.Comment: Accepted for publication on IEEE Transactions on Vehicular Technolog
Using Channel Output Feedback to Increase Throughput in Hybrid-ARQ
Hybrid-ARQ protocols have become common in many packet transmission systems
due to their incorporation in various standards. Hybrid-ARQ combines the normal
automatic repeat request (ARQ) method with error correction codes to increase
reliability and throughput. In this paper, we look at improving upon this
performance using feedback information from the receiver, in particular, using
a powerful forward error correction (FEC) code in conjunction with a proposed
linear feedback code for the Rayleigh block fading channels. The new hybrid-ARQ
scheme is initially developed for full received packet feedback in a
point-to-point link. It is then extended to various different multiple-antenna
scenarios (MISO/MIMO) with varying amounts of packet feedback information.
Simulations illustrate gains in throughput.Comment: 30 page
Hybrid ARQ with parallel and serial concatenated convolutional codes for next generation wireless communications
This research focuses on evaluating the currently used FEC encoding-decoding schemes and improving the performance of error control systems by incorporating these schemes in a hybrid FEC-ARQ environment. Beginning with an overview of wireless communications and the various ARQ protocols, the thesis provides an in-depth explanation of convolutional encoding and Viterbi decoding, turbo (PCCC) and serial concatenated convolutional (SCCC) encoding with their respective MAP decoding strategies.;A type-II hybrid ARQ scheme with SCCCs is proposed for the first time and is a major contribution of this thesis. A vast improvement is seen in the BER performance of the successive individual FEC schemes discussed above. Also, very high throughputs can be achieved when these schemes are incorporated in an adaptive type-II hybrid ARQ system.;Finally, the thesis discusses the equivalence of the PCCCs and the SCCCs and proposes a technique to generate a hybrid code using both schemes
DMT Optimality of LR-Aided Linear Decoders for a General Class of Channels, Lattice Designs, and System Models
The work identifies the first general, explicit, and non-random MIMO
encoder-decoder structures that guarantee optimality with respect to the
diversity-multiplexing tradeoff (DMT), without employing a computationally
expensive maximum-likelihood (ML) receiver. Specifically, the work establishes
the DMT optimality of a class of regularized lattice decoders, and more
importantly the DMT optimality of their lattice-reduction (LR)-aided linear
counterparts. The results hold for all channel statistics, for all channel
dimensions, and most interestingly, irrespective of the particular lattice-code
applied. As a special case, it is established that the LLL-based LR-aided
linear implementation of the MMSE-GDFE lattice decoder facilitates DMT optimal
decoding of any lattice code at a worst-case complexity that grows at most
linearly in the data rate. This represents a fundamental reduction in the
decoding complexity when compared to ML decoding whose complexity is generally
exponential in rate.
The results' generality lends them applicable to a plethora of pertinent
communication scenarios such as quasi-static MIMO, MIMO-OFDM, ISI,
cooperative-relaying, and MIMO-ARQ channels, in all of which the DMT optimality
of the LR-aided linear decoder is guaranteed. The adopted approach yields
insight, and motivates further study, into joint transceiver designs with an
improved SNR gap to ML decoding.Comment: 16 pages, 1 figure (3 subfigures), submitted to the IEEE Transactions
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