1,442 research outputs found

    Efficient Systematic Encoding of Non-binary VT Codes

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    Varshamov-Tenengolts (VT) codes are a class of codes which can correct a single deletion or insertion with a linear-time decoder. This paper addresses the problem of efficient encoding of non-binary VT codes, defined over an alphabet of size q>2q >2. We propose a simple linear-time encoding method to systematically map binary message sequences onto VT codewords. The method provides a new lower bound on the size of qq-ary VT codes of length nn.Comment: This paper will appear in the proceedings of ISIT 201

    Capacity Bounds and Concatenated Codes Over Segmented Deletion Channels

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    Cataloged from PDF version of article.We develop an information theoretic characterization and a practical coding approach for segmented deletion channels. Compared to channels with independent and identically distributed (i.i.d.) deletions, where each bit is independently deleted with an equal probability, the segmentation assumption imposes certain constraints, i.e., in a block of bits of a certain length, only a limited number of deletions are allowed to occur. This channel model has recently been proposed and motivated by the fact that for practical systems, when a deletion error occurs, it is more likely that the next one will not appear very soon. We first argue that such channels are information stable, hence their channel capacity exists. Then, we introduce several upper and lower bounds with two different methods in an attempt to understand the channel capacity behavior. The first scheme utilizes certain information provided to the transmitter and/or receiver while the second one explores the asymptotic behavior of the bounds when the average bit deletion rate is small. In the second part of the paper, we consider a practical channel coding approach over a segmented deletion channel. Specifically, we utilize outer LDPC codes concatenated with inner marker codes, and develop suitable channel detection algorithms for this scenario. Different maximum-a-posteriori (MAP) based channel synchronization algorithms operating at the bit and symbol levels are introduced, and specific LDPC code designs are explored. Simulation results clearly indicate the advantages of the proposed approach. In particular, for the entire range of deletion probabilities less than unity, our scheme offers a significantly larger transmission rate compared to the other existing solutions in the literature

    Error correction for asynchronous communication and probabilistic burst deletion channels

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    Short-range wireless communication with low-power small-size sensors has been broadly applied in many areas such as in environmental observation, and biomedical and health care monitoring. However, such applications require a wireless sensor operating in always-on mode, which increases the power consumption of sensors significantly. Asynchronous communication is an emerging low-power approach for these applications because it provides a larger potential of significant power savings for recording sparse continuous-time signals, a smaller hardware footprint, and a lower circuit complexity compared to Nyquist-based synchronous signal processing. In this dissertation, the classical Nyquist-based synchronous signal sampling is replaced by asynchronous sampling strategies, i.e., sampling via level crossing (LC) sampling and time encoding. Novel forward error correction schemes for sensor communication based on these sampling strategies are proposed, where the dominant errors consist of pulse deletions and insertions, and where encoding is required to take place in an instantaneous fashion. For LC sampling the presented scheme consists of a combination of an outer systematic convolutional code, an embedded inner marker code, and power-efficient frequency-shift keying modulation at the sensor node. Decoding is first obtained via a maximum a-posteriori (MAP) decoder for the inner marker code, which achieves synchronization for the insertion and deletion channel, followed by MAP decoding for the outer convolutional code. By iteratively decoding marker and convolutional codes along with interleaving, a significant reduction in terms of the expected end-to-end distortion between original and reconstructed signals can be obtained compared to non-iterative processing. Besides investigating the rate trade-off between marker and convolutional codes, it is shown that residual redundancy in the asynchronously sampled source signal can be successfully exploited in combination with redundancy only from a marker code. This provides a new low complexity alternative for deletion and insertion error correction compared to using explicit redundancy. For time encoding, only the pulse timing is of relevance at the receiver, and the outer channel code is replaced by a quantizer to represent the relative position of the pulse timing. Numerical simulations show that LC sampling outperforms time encoding in the low to moderate signal-to-noise ratio regime by a large margin. In the second part of this dissertation, a new burst deletion correction scheme tailored to low-latency applications such as high-read/write-speed non-volatile memory is proposed. An exemplary version is given by racetrack memory, where the element of information is stored in a cell, and data reading is performed by many read ports or heads. In order to read the information, multiple cells shift to its closest head in the same direction and at the same speed, which means a block of bits (i.e., a non-binary symbol) are read by multiple heads in parallel during a shift of the cells. If the cells shift more than by one single cell location, it causes consecutive (burst) non-binary symbol deletions. In practical systems, the maximal length of consecutive non-binary deletions is limited. Existing schemes for this scenario leverage non-binary de Bruijn sequences to perfectly locate deletions. In contrast, in this work binary marker patterns in combination with a new soft-decision decoder scheme is proposed. In this scheme, deletions are soft located by assigning a posteriori probabilities for the location of every burst deletion event and are replaced by erasures. Then, the resulting errors are further corrected by an outer channel code. Such a scheme has an advantage over using non-binary de Bruijn sequences that it in general increases the communication rate

    Capacity bounds and concatenated codes over segmented deletion channels

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    We develop an information theoretic characterization and a practical coding approach for segmented deletion channels. Compared to channels with independent and identically distributed (i.i.d.) deletions, where each bit is independently deleted with an equal probability, the segmentation assumption imposes certain constraints, i.e., in a block of bits of a certain length, only a limited number of deletions are allowed to occur. This channel model has recently been proposed and motivated by the fact that for practical systems, when a deletion error occurs, it is more likely that the next one will not appear very soon. We first argue that such channels are information stable, hence their channel capacity exists. Then, we introduce several upper and lower bounds with two different methods in an attempt to understand the channel capacity behavior. The first scheme utilizes certain information provided to the transmitter and/or receiver while the second one explores the asymptotic behavior of the bounds when the average bit deletion rate is small. In the second part of the paper, we consider a practical channel coding approach over a segmented deletion channel. Specifically, we utilize outer LDPC codes concatenated with inner marker codes, and develop suitable channel detection algorithms for this scenario. Different maximum-a-posteriori (MAP) based channel synchronization algorithms operating at the bit and symbol levels are introduced, and specific LDPC code designs are explored. Simulation results clearly indicate the advantages of the proposed approach. In particular, for the entire range of deletion probabilities less than unity, our scheme offers a significantly larger transmission rate compared to the other existing solutions in the literature. © 1972-2012 IEEE

    On Asynchronous Communication Systems: Capacity Bounds and Relaying Schemes

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    abstract: Practical communication systems are subject to errors due to imperfect time alignment among the communicating nodes. Timing errors can occur in different forms depending on the underlying communication scenario. This doctoral study considers two different classes of asynchronous systems; point-to-point (P2P) communication systems with synchronization errors, and asynchronous cooperative systems. In particular, the focus is on an information theoretic analysis for P2P systems with synchronization errors and developing new signaling solutions for several asynchronous cooperative communication systems. The first part of the dissertation presents several bounds on the capacity of the P2P systems with synchronization errors. First, binary insertion and deletion channels are considered where lower bounds on the mutual information between the input and output sequences are computed for independent uniformly distributed (i.u.d.) inputs. Then, a channel suffering from both synchronization errors and additive noise is considered as a serial concatenation of a synchronization error-only channel and an additive noise channel. It is proved that the capacity of the original channel is lower bounded in terms of the synchronization error-only channel capacity and the parameters of both channels. On a different front, to better characterize the deletion channel capacity, the capacity of three independent deletion channels with different deletion probabilities are related through an inequality resulting in the tightest upper bound on the deletion channel capacity for deletion probabilities larger than 0.65. Furthermore, the first non-trivial upper bound on the 2K-ary input deletion channel capacity is provided by relating the 2K-ary input deletion channel capacity with the binary deletion channel capacity through an inequality. The second part of the dissertation develops two new relaying schemes to alleviate asynchronism issues in cooperative communications. The first one is a single carrier (SC)-based scheme providing a spectrally efficient Alamouti code structure at the receiver under flat fading channel conditions by reducing the overhead needed to overcome the asynchronism and obtain spatial diversity. The second one is an orthogonal frequency division multiplexing (OFDM)-based approach useful for asynchronous cooperative systems experiencing excessive relative delays among the relays under frequency-selective channel conditions to achieve a delay diversity structure at the receiver and extract spatial diversity.Dissertation/ThesisPh.D. Electrical Engineering 201

    On capacity and coding for segmented deletion channels

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    We consider binary deletion channels with a segmentation assumption which appears to be suited for more practical scenarios. Unlike the binary independent and identically distributed (i.i.d.) deletion channel where each bit is independently deleted with an equal probability, the segmentation assumption prohibits certain transmitted bits to be deleted, i.e., in a block of bits of a certain length, only a limited number of deletions can occur. We first propose several upper and lower capacity bounds for the segmented deletion channel. Then we focus on an interleaved concatenation of an outer low-density parity check (LDPC) code with error-correction capabilities and an inner marker code with synchronization capabilities over these channels. With the help of a specifically designed maximum-a-posteriori (MAP) detector, we demonstrate reliable transmission at higher code rates than the existing ones reported in the literature. © 2011 IEEE
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