1,721,020 research outputs found
Optimal packet scheduling for an energy harvesting transmitter with processing cost
No full textEnergy harvesting (EH) technology enables wireless nodes to operate in a self-powered fashion; however, the stochastic nature of the harvesting process and the limited amount of harvested energy require efficient management of the available resources. In this paper, an EH transmitter communicating over a fading channel is studied considering jointly the energy costs of transmission and processing. In particular, under the assumption of known energy and data arrival profiles and fading states, optimal transmission policies are studied, so that, the remaining energy in the battery of the transmitter is maximized by a given deadline while all the arriving data packets are delivered to the receiver. A 'directional glue pouring' interpretation is provided for the algorithm that computes the optimal offline transmission policy. The relation of this problem with the transmission completion time minimization problem is also discussed. Finally, a heuristic algorithm for online optimization, which performs close to the optimal offline transmission policy, is proposed. © 2013 IEEE
Source coding under secrecy constraints
No full textDistributed compression involves compressing multiple data sources by exploiting the underlying correlation structure of the sources at separate non-cooperating encoders, while decoding is done jointly at a single decoder. Recent years have witnessed an increasing amount of research on the theoretical and practical aspects of distributed source codes, which find applications in distributed video compression, peer-to-peer data distribution systems, and sensor networks [1-3]. In many practical scenarios, limited network resources such as power and bandwidth, or physical limitations of the devices as in the case of sensor networks, pose challenges in terms of network performance and security. Oftentimes, the data aggregated in distributed compression systems may have commercial value as in the case of warehouse inventory monitoring systems, may contain sensitive information as in the case of distributed video surveillance systems, or might infringe personal privacy concerns as in the case of human body sensors measuring various health indicators. In all these scenarios, it is essential to develop distributed compression and communication protocols which exploit the limited power and bandwidth resources efficiently as well as satisfying the security requirements. Our goal in this chapter is to review fundamental limitations and tradeoffs for the overall performance optimization taking into account the quality and the security considerations jointly. There are two fundamental approaches to guarantee security in wireless networks. In the approach based on computational complexity [4], on which most practical cryptographic applications are based, the security of the system depends on the intractability assumption for a problem such as prime factorization. On the other hand, in the approach based on information theoretic secrecy introduced by Shannon in [5], the emphasis is on unconditional secrecy, which requires that, an eavesdropper with unbounded time and computational resources, and the knowledge of the encryption algorithm, does not gain any additional information about the underlying secret message upon intercepting the encrypted cryptogram. For a general review of recent progress in information theoretic security, see [6]. Although the complexity based approach has been successful in satisfying the security concerns of many practical networking applications such as the Internet, wireless networks pose additional limitations and threats that cannot be solved solely through encryption. The broadcast nature of the wireless medium makes it particularly vulnerable to eavesdropping and authentication attacks, and the energy and bandwidth limitations of wireless devices restrict their computational power, hence rendering high complexity encryption techniques undesirable. Furthermore, especially in the sensor network scenario, where the sensor nodes are generally deployed in remote locations highly vulnerable to tampering, secure key management becomes impractical. Issues such as mobility and lack of infrastructure (e.g., in mobile ad hoc networks) also pose significant challenges to traditional approaches based on maintaining secret keys. In such applications information theoretic security can support and enhance the computational complexity based approach. In this chapter, we survey information theoretic security in distributed source compression, and in particular how compression and communication can be achieved in an information theoretically secure way. Consider, for example, a sensor network in which correlated sensor observations are to be reconstructed at an access point either in a lossless fashion or within a prescribed distortion requirement. While some sensors might have secure (possibly wired) connections to the access point, others might be transmitting over the wireless medium, which can be accessed by an adversary trying to obtain information about the underlying phenomenon. Furthermore, this adversary might have her own observation of the main source. Our goal is to explore the fundamental information theoretic limitations for secure distributed compression and communication in this kind of situation. In practical applications, encryption is considered to be a separate block in the protocol stack applied in concatenation with source compression and channel transmission. The information theoretic unconditional secrecy obtained through secure source and/or channel coding or joint source-channel coding hence can be used in parallel with the existing computational encryption schemes enhancing the overall level of security. In order to fully exploit this concept of information theoretic security practical secure source and channel codes need to be developed. While there are many recent developments in this direction for channel coding [7-9] little is known for secure compression. However, design of such secure source codes is beyond the scope of this chapter, and constitutes a potential research direction. The chapter is organized as follows. After reviewing Shannon's model and the preliminaries of information theoretic secrecy in Sect. 8.2, in Sect. 8.3 we analyze distributed lossless compression under security constraints and present related fundamental results. In Sect. 8.4, we focus on lossy reconstruction at the legitimate receiver, and analyze the achievable distortion for given secrecy and communication rate constraints. Section 8.5 focuses on secure joint source-channel coding followed by the Conclusions and the Appendix. © 2010 Springer Science+Business Media, LLC
Delay-constrained distortion minimization for energy harvesting transmission over a fading channel
No full textDistortion minimization for an energy harvesting sensor node communicating over a fading channel is studied. Slotted transmission is considered such that, new source samples and energy packets arrive at the beginning of each time slot (TS), and the fading channel state changes from one TS to the next. A delay constraint is imposed requiring each source sample to be reconstructed at the destination d TSs after its arrival. Assuming independent Gaussian samples with variances changing over TSs, total distortion is minimized under the offline optimization framework, i.e., energy arrivals, source variances and channel gains are assumed to be known non-causally. Optimal compression rates and transmission powers are found and some properties of the optimal strategy are discussed. A two-dimensional water-filling interpretation of the optimal solution is provided for a battery-run node with d = 1. © 2013 IEEE
Interference channel and compound MAC with correlated sources and receiver side information
No full textWe consider discrete memoryless compound multiple access and interference channels with correlated sources and correlated side information at the receivers, and investigate necessary and sufficient conditions for lossless transmission. We first give sufficient conditions for the most general setting, and then show that these conditions are also necessary for both channels under certain assumptions on the side information and the interference. In particular, we generalize the notion of strong interference to take into account the correlation among the sources and side information. We prove the optimality of 'informational' or 'operational' source-channel separation for certain special cases. While informational separation results in independent source and channel encoding and decoding; operational separation corresponds to separation at the encoder, while decoding is done jointly. To our knowledge, these results constitute the first source-channel separation results for interference and compound multiple access channels with correlated sources and side information. ©2007 IEEE
Dynamic resource allocation for the broadband relay channel
No full textWe consider a half-duplex broadband relay channel which is composed of L parallel, independent Rayleigh fading relay channels. Partial channel state information in the form of channel state amplitudes is available at the transmitters while the receivers have perfect channel state information. We assume a long term total average power constraint at the source and the relay. We dynamically allocate the power and the relay transmission time to improve the delay limited capacity or alternatively to decrease the outage probability. We analyze multi-hop (MH) and opportunistic decodeand-forward (ODF) protocols for the broadband relay channel and propose various subchannel resource allocation strategies. Simulation based performance comparisons also include the modified cut-set bound. © 2007 IEEE
Resource allocation for the parallel relay channel with multiple relays
No full textA cooperative network where transmission between two nodes that have no direct link, but assisted by many relays is considered. We assume a broadband system, such as OFDM, modeled by multiple parallel Gaussian subchannels between the source and each relay, and also between each relay and the destination. We formulate the optimization problem for joint power and subchannel allocation under a short term per-node power constraint to maximize the instantaneous total transmission rate between the source and the destination. To solve this optimization problem, first we find the optimal power allocation for a given subchannel allocation. Then we focus on a greedy algorithm that jointly allocates subchannels and power. Simulation results reveal that our proposed algorithm results in rates close to the optimum allocation
Joint Source-Channel Codes for MIMO Block Fading Channels
Full text linkWe consider transmission of a continuous amplitude source over an L-block
Rayleigh fading MIMO channel when the channel state
information is only available at the receiver. Since the channel is not
ergodic, Shannon's source-channel separation theorem becomes obsolete and the
optimal performance requires a joint source -channel approach. Our goal is to
minimize the expected end-to-end distortion, particularly in the high SNR
regime. The figure of merit is the distortion exponent, defined as the
exponential decay rate of the expected distortion with increasing SNR. We
provide an upper bound and lower bounds for the distortion exponent with
respect to the bandwidth ratio among the channel and source bandwidths. For the
lower bounds, we analyze three different strategies based on layered source
coding concatenated with progressive, superposition or hybrid digital/analog
transmission. In each case, by adjusting the system parameters we optimize the
distortion exponent as a function of the bandwidth ratio. We prove that the
distortion exponent upper bound can be achieved when the channel has only one
degree of freedom, that is L=1, and . When we have more
degrees of freedom, our achievable distortion exponents meet the upper bound
for only certain ranges of the bandwidth ratio. We demonstrate that our
results, which were derived for a complex Gaussian source, can be extended to
more general source distributions as well
Rate-memory trade-off for the two-user broadcast caching network with correlated sources
No full textRate-memory trade-off for caching and delivery of correlated sources
No full textThis paper studies the fundamental limits of content delivery in a cache-aided broadcast network for correlated content generated by a discrete memoryless source with arbitrary joint distribution. Each receiver is equipped with a cache of equal capacity, and the requested files are delivered over a shared error-free broadcast link. A class of achievable correlation-aware schemes based on a two-step source coding approach is proposed. Library files are first compressed, and then cached and delivered using a combination of multiple-request caching schemes that are agnostic to the content correlations. The first step uses Gray-Wyner source coding to represent the library via private descriptions and descriptions that are common to more than one file. The second step then becomes a multiple-request caching problem, where the demand structure is dictated by the configuration of the compressed library, and it is interesting in its own right. The performance of the proposed two-step scheme is evaluated by comparing its achievable rate with a lower bound on the optimal peak and average rate-memory trade-offs in a two-file multiple-receiver network, and in a three-file two-receiver network. Specifically, in a network with two files and two receivers, the achievable rate matches the lower bound for a significant memory regime and it is within half of the conditional entropy of files for all other memory values. In the three-file two-receiver network, the two-step strategy achieves the lower bound for large cache capacities, and it is within half of the joint entropy of two of the sources conditioned on the third one for all other cache sizes
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