Low-Complexity Cooperative Coding for Sensor Networks using Rateless and LDGM Codes

Application of an unconventional thermal and mechanical energy storage coupled with the air conditioning and domestic hot water systems of a residential building

Recently, in multi-way relay systems employing physical-layer network coding (PNC), channel condition-based pair selection for pairwise information exchange has drawn increased attention as it provides improved performance over the alternative approaches such as round-robin scheduling of node pairs. With pairwise information exchange, there is additional time diversity available due to transmission of the same coded information block of most of the nodes twice in two adjacent time slots. This additional time diversity can be exploited to further enhance the system performance by means of joint channel decoding-network coding. To this end, a joint belief propagation (BP)-based channel decoding-network coding algorithm was proposed by us in [9] for the relay node of low density parity check (LDPC)-coded multi-way relay systems. Even though the algorithm of [9] offers much superior performance over separate channel decoding, it is highly computational expensive and may not be suitable for applications in wireless sensor networks. Alternatively, bit-flipping (BF)-based LDPC decoding can be adopted at much lower computational complexity. In this paper, we develop a low complexity joint bit-flipping (BF)-based channel decoding and network coding algorithm for LDPC-based multi-way relay systems. The BER performance of the proposed algorithm is investigated using computer simulation for two commonly used LDPC codes. The simulation results demonstrate that superior BER performance can be achieved using the proposed joint decoding algorithm over separate and independent bit-flipping-based LDPC channel decoding at the relay. The simulation results also verify that our proposed algorithm is capable of harnessing the aforesaid additional time diversity available. Though the performance of the proposed joint decoding algorithm is inferior to the BP-based algorithm of [9], due to its low computationally complexity, this algorithm may be appealing for applications in relay nodes with low computational capabilities and memory constraints.

Sensor nodes in Wireless Sensor Networks (WSNs) operate with limited power resources such as small batterieswhich are difficult to be either recharged or replaced in some environments when depleted. Power consumptionrepresents one of the most constraints impact the design of WSNs, leading to various protocols and algorithmsaimed at minimizing the power consumption and extending batteries' lifetime. Sensor nodes in WSNs transmittheir periodic packets continuously to central nodes (receivers) which are responsible for decoding packets andtransmitting them to other communication networks. In addition, sensors usually follow various MAC strategieswhich allow accessing to wireless communication channels. However, sensors may attempt to access thewireless channels at the same time, potentially, leading to collisions among multiple nodes. In fact, central nodesin WSNs most often consume a large amount of power due to the necessity to decode every received packetregardless of the fact that the transmission may suffer from packets collision which impede the networkperformance. Therefore, in the receiver side of WSNs current collision detection mechanisms have largely beenrevolving around direct demodulation and decoding of received packets and deciding on a collision based onsome form of parity bits in each packet for error control. From information theoretic prospective full decoding ofreceived packets with error control bits at central nodes can achieve an efficient usage of network capacity,however, such an approach represents a major burden on power-constrained sensors. This drawback comes fromthe need to expend a significant amount of energy and processing complexity at sink nodes in order tofully-decode a packet, only to discover the packet is illegible due to a collision. In this paper, we propose a morepractical power saving approaches which achieve a significant power saving with low-complexity at the expenseof low throughput losses. Based on studying the statistics of received packets, central nodes can make a fastdecision to detect a collision without the need for full-decoding of the whole received packets. Our novelapproaches not only reduces processing complexity and hence power consumption, but it also reduces the delayincurred to detect a collision since it operates on only a small number of IQ samples in the beginning of areceived packet. In such a paradigm, our approaches operate directly at the output of the receiver’sAnalog-to-Digital-Converter (ADC) and eliminate the need to pass the corrupted packets through the entiredemodulator/decoder line-up. The performance gain of our proposed approach is illustrated through thecomparison between the computational complexity of our Statistical Discrimination (SD) approaches and someexisting Full Decoding (FD) algorithms(note 1). Our results show that the SD approaches has significant powersavings and low computational complexities over existing FD algorithms with low False-Alarm and Missprobabilities, which qualify our SD approaches to be considered as reliable collision detection mechanisms inWSNs. We also show how to tune various design parameters in order to allow a system designer multipledegrees of freedom for design trade-offs and optimization.

Spatio-temporal equalization is a technique which utilizes both spatial and temporal information of the received signal to compensate for intersymbol interference due to multipath fading. Considering the application of a spatio-temporal equalizer to high speed wireless communications systems, such as wireless LANs, this paper proposes a new spatio-temporal equalization method using a cascade configuration of an adaptive array and a DFE (decision feedback equalizer), which can be realized with small number of weights, and hence, low computational complexity. However, it has to pay a price for the simplicity, namely, the error performance surface becomes a fourth-order function of the weights, and possibly has two minima. In order to avoid a wrong trap by a local minimum during the adaptation of the MMSE (minimum mean-squared error) based adaptation algorithm with any initial values, the proposed equalizer calculates the weights of the adaptive array and the DFE separately in two steps, and the adaptive array selects a path or paths to capture depending on channel conditions. Computer simulation results show that the proposed method can achieve good performance in various channel models, which are based on measurement reports, in low computational complexity.

Two‐way relaying tends to become a celebrated technique in communication networks because of its unique characteristic in establishing a two‐step bilateral information exchange mechanism between users' pairs, as well as, arranging a virtual spatial diversity scenario. In this paper, two‐way relaying under amplify‐and‐forward strategy, and fast Rayleigh fading environment is considered. We investigate two distinct cases in which the relay retransmits users' superposed signals, either directly or after complex conjugation in two‐ or three‐phase modalities. We derive the optimal detection rule which is inherently computational complex. Two closed‐form suboptimal structures are proposed to circumvent this formidable problem. In the first form, we incorporate the destination noise into the relay counterpart, and assume Gaussian conditional distribution for the received signal in the latter. The first detector is designed using less stringent approximation and consequently has a better performance, whereas the second one benefits from a very low computational complexity and simple implementation and is more suitable for applications with strict computational and energy constraints such as sensor networks. Furthermore, we consider the imperfect self‐channel information case and extend the corresponding results. Bit error rate analyses and accompanying computer simulations show an improvement of about 5 dB over existing methods.

On the basis of analyzing of some existing differential space-time coding (DSTC) schemes, we develop a differential space-time block coding scheme based on multiple levels quadrature amplitude modulation (MQAM) in this paper. By introducing MQAM, the developed scheme can avoid the performance loss of conventional DSTC schemes based on MPSK modulation due to the decrease of minimum distance between constellation symbols in high spectrum efficiency. Compared with the existing DSTC schemes, the developed scheme has lower computational complexity and simple decoder. Moreover, it can achieve higher code rate in the case of more than two transmitter antennas. Theoretic analysis shows that the scheme has higher coding gain than existing differential unitary space-time coding scheme and differential orthogonal space-time coding scheme, and corresponding simulation results also show that our scheme has lower bit error rate (BER) when compared with the above two schemes.

In this note, a hierarchical fusion estimation method is presented for clustered sensor networks with a very general setup where sensors (sensor nodes) and estimators (cluster heads) are allowed to work asynchronously with aperiodic sampling and estimation rates. A sequential measurement fusion (SMF) method is presented to design local estimators, and it is shown that the SMF estimator is equivalent to the measurement augmentation (MA) estimator in precision but with much lower computational complexity. Two types of sequential covariance intersection (CI) fusion estimators are presented for the fusion estimation. The proposed SCI fusion estimators provide a satisfactory estimation precision that is close to the centralized batch CI (BCI) estimator while requiring smaller computational burden as compared with the BCI estimator. Therefore, the proposed hierarchical fusion estimation method is suitable for real-time applications in asynchronous sensor networks with energy constraints. Moreover, the method is applicable to the case with packet delays and losses.

This paper presents an efficient data gathering framework of network coding (NC) coupled compressed sensing (CS) in wireless sensor networks (WSNs), called network compressed coding (NCC). We employ network coding to adapt to the dynamic nature of WSNs, such as moving obstacles and link failure. Measurements from sensor networks are often correlated because sensors nodes nearby observe the contiguous phenomenon, and the operation of the random linear network coding (RLNC) scheme is similar to that of the random projection in compressed sensing. Therefore, we introduce compressed sensing into the network coding (NC), to prevent all-or-nothing impact on NC. NCC simultaneously transmits and encodes specific packets of sensor measurements to form random projections for CS recovery. CS technology guarantees that the data gathered at all nodes are accurately recovered with a high probability from a small number of projections, which is less than the total number of source nodes in the network. Our simulation results show that, only less than half number of packets are required to reconstruct measurements with reasonable quality compared with the traditional network coding schemes. Also, NCC increases the data gathering efficiency by over 20% compared to the conventional NC scheme.

Currently, most of the researches in molecular communication (MC) domain focus on the static MC scenarios. However, some envisioned important MC applications require mobile MC system. The investigation on mobile MC, especially the signal detection of mobile MC is limited. This work considers the problem of signal detection for mobile MC scenarios where the receiver nano-machine performs random movement. Due to the random movement of the receiver, the channel impulse response (CIR) changes over time which makes the received signal stochastic and complicated. This further complicates the signal detection in mobile MC and leads to that the state-of-the-art signal detection schemes for static MC scenarios fail for the mobile MC scenarios. To solve this issue, an adaptive detection scheme has been proposed by our group previously, based on dynamic estimation of the stochastically varying distance between the transmitter and receiver and the reconstruction of CIR in each interval. However, its computational complexity is high. Limited capability of current nano-machines desire low-complexity detection algorithm. In this work, we further propose an adaptive detection scheme for mobile MC with a low computational complexity by utilizing the local convex property of the CIR. With on-off keying (OOK) modulation, the signal of symbol "1" presents local convex property while that of symbol "0" presents local concave property. The convexity extent varies with the stochastic distance. A simple indicator, local maximum convexity is proposed which adapts to the stochastic distance. By comparing the adaptive indicator with an adaptive threshold within each symbol interval, the signal is detected without the need to estimate the stochastically changing distance or to reconstruct the CIR. Therefore, the computational load is effectively reduced. Numerical simulations are performed to evaluate the proposed scheme. The results show that the proposed scheme achieves good detection accuracy with low computational complexity and it could be a promising detection scheme for mobile MC scenarios.

Network coding provides the advantage of maximizing the usage of network resources, but the natural properties of network coding also make the pollution attack more threatening. Much work on resisting pollution attacks is through homomorphic MACs. But majority have same security parameter 1/q. In this paper, we present two ways to construct homomorphic MAC which improve the performance of previous schemes. The security parameters of our MACs are 1/ql1 and 1/ql2, respectively. Besides the higher security, our MAC schemes have lower computational complexity.

The Lifted MRD (Maximum Rank Distance) code was introduced by Silva et al. to correct link errors and erasures for network coding systems. It achieves the generalized asymptotic Singleton bound for network error correction codes, and was shown to be equivalent to the Koetter-Kschischang code. However, in wireless network coding, undetected link errors that occur early in the network may accumulate and propagate beyond the decoding capability of the Lifted MRD code at the destination node. In this paper, we address this problem by a few strategies: detect and track possible error packets as erasure packets as they propagate through the network, reverse the error propagation process at the destination node by exploiting knowledge of the erasure packet positions, and double the MRD decoding capability by using erasure-and-error decoding. Algorithms to implement the above strategies are designed for low network overhead and low computational complexity. Simulation results show that the proposed scheme significantly improves the reliability of network coding over unreliable wireless links.

Network coding allows intermediate nodes to encode data packets to improve network throughput and robustness. However, it increases the propagation speed of polluted data packets if a malicious node injects fake data packets into the network, which degrades the bandwidth efficiency greatly and leads to incorrect decoding at sinks. In this paper, insights on new mathematical relations in linear network coding are presented and a key predistribution-based tag encoding scheme KEPTE is proposed, which enables all intermediate nodes and sinks to detect the correctness of the received data packets. Furthermore, the security of KEPTE with regard to pollution attack and tag pollution attack is quantitatively analyzed. The performance of KEPTE is competitive in terms of: low computational complexity; the ability that all intermediate nodes and sinks detect pollution attack; the ability that all intermediate nodes and sinks detect tag pollution attack; and high fault-tolerance ability. To the best of our knowledge, the existing key predistribution-based schemes aiming at pollution detection can only achieve at most three points as described above. Finally, discussions on the application of KEPTE to practical network coding are also presented.

Instantly decodable network coding (IDNC) reduces the completion delay of packet retransmission for multicast services in wireless point-to-multipoint (PMP) networks. Compared with multicast services, multiple unicast services may be more common in PMP networks. Reducing completion delay using IDNC for multiple unicast services is still an open problem. According to the construction features of IDNC, we find that if some unicast retransmissions are combined as a retransmission group, IDNC benefits from network coding (NC) considerably, which increases retransmission efficiency. Based on this observation, we study the total completion delay of all these unicast transmissions with intersession NC. In this paper, we provide an intersession insight into the IDNC method. Specifically, we propose a framework that contains 1) a general solution to this minimum completion delay (MCD) problem, which is modeled as a bin-packing problem, and 2) a lower bound of completion delay for the MCD solution. Additionally, we provide a high-efficiency greedy algorithm to solve the MCD problem with low computational complexity. Simulation results demonstrate that the proposed method saves almost 43% retransmissions in PMP networks and makes 87.5% retransmission packets benefit from the NC transmission.

In this paper, we propose to generalize the coding schemes first proposed by Kozic & al to high spectral efficient modulation schemes. To obtain high performing coding schemes, we use a high dimensional modulo-MAP mapping process similar to the low-density generator-matrix codes (LDGM) introduced by Kozic & al. The main difference with their work is that we use an encoding and decoding process on GF(2m) which enables to obtain better performances while preserving a relative simple decoding algorithm when we use the Extended Min-Sum (EMS) algorithm of Declercq & Fossorier.

A low complexity Parallel Interference Cancellation (PIC) technique is proposed to suppress Multi-Access Interference (MAI) and minimize near-far effect for multi-user communication using Direct-Sequence Code Division Multiple Access (DS-CDMA). Interference signal is estimated using a relationship between cyclic correlation of the received signal and user's code of the interferer without requiring any knowledge of the channel condition. The user's codes for the multi-user DS-CDMA communication are constructed by using a set of m-sequences. The cyclic correlation is performed using Fast Walsh-Hadamard Transform (FWHT) which exhibits low computational complexity, i.e., it does not require any multiplication/division operations. In addition to low complexity, the proposed technique does not require complicated channel condition estimation and has no convergence issues. The uncoded Bit Error Rate (BER) performance of the proposed interference cancellation is calculated and compared with the conventional one over three different types of channels: AWGN, slow Rayleigh fading, and multipath channels.