arXiv subjects

Osvaldo Simeone

Publications and source records attributed to Osvaldo Simeone.

At least 361 records · Page 20Linked to original sources

arXiv2013

Multihop Backhaul Compression for the Uplink of Cloud Radio Access Networks

In cloud radio access networks (C-RANs), the baseband processing of the radio units (RUs) is migrated to remote control units (CUs). This is made possible by a network of backhaul links that connects RUs and CUs and that carries compressed baseband signals. While prior work has focused mostly on single-hop backhaul networks, this paper investigates efficient backhaul compression strategies for the uplink of C-RANs with a general multihop backhaul topology. A baseline multiplex-and-forward (MF) scheme is first studied in which each RU forwards the bit streams received from the connected RUs without any processing. It is observed that this strategy may cause significant performance degradation in the presence of a dense deployment of RUs with a well connected backhaul network. To obviate this problem, a scheme is proposed in which each RU decompresses the received bit streams and performs linear in-network processing of the decompressed signals. For both the MF and the decompress-process-and-recompress (DPR) backhaul schemes, the optimal design is addressed with the aim of maximizing the sum-rate under the backhaul capacity constraints. Recognizing the significant demands of the optimal solution of the DPR scheme in terms of channel state information (CSI) at the RUs, decentralized optimization algorithms are proposed under the assumption of limited CSI at the RUs. Numerical results are provided to compare the performance of the MF and DPR schemes, highlighting the potential advantage of in-network processing and the impact of CSI limitations.

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arXiv2013

Performance Evaluation of Multiterminal Backhaul Compression for Cloud Radio Access Networks

In cloud radio access networks (C-RANs), the baseband processing of the available macro- or pico/femto-base stations (BSs) is migrated to control units, each of which manages a subset of BS antennas. The centralized information processing at the control units enables effective interference management. The main roadblock to the implementation of C-RANs hinges on the effective integration of the radio units, i.e., the BSs, with the backhaul network. This work first reviews in a unified way recent results on the application of advanced multiterminal, as opposed to standard point-to-point, backhaul compression techniques. The gains provided by multiterminal backhaul compression are then confirmed via extensive simulations based on standard cellular models. As an example, it is observed that multiterminal compression strategies provide performance gains of more than 60% for both the uplink and the downlink in terms of the cell-edge throughput.

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arXiv2013

Constrained Codes for Joint Energy and Information Transfer

In various wireless systems, such as sensor RFID networks and body area networks with implantable devices, the transmitted signals are simultaneously used both for information transmission and for energy transfer. In order to satisfy the conflicting requirements on information and energy transfer, this paper proposes the use of constrained run-length limited (RLL) codes in lieu of conventional unconstrained (i.e., random-like) capacity-achieving codes. The receiver's energy utilization requirements are modeled stochastically, and constraints are imposed on the probabilities of battery underflow and overflow at the receiver. It is demonstrated that the codewords' structure afforded by the use of constrained codes enables the transmission strategy to be better adjusted to the receiver's energy utilization pattern, as compared to classical unstructured codes. As a result, constrained codes allow a wider range of trade-offs between the rate of information transmission and the performance of energy transfer to be achieved.

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arXiv2013

Joint Signal and Channel State Information Compression for the Backhaul of Uplink Network MIMO Systems

In network MIMO cellular systems, subsets of base stations (BSs), or remote radio heads, are connected via backhaul links to central units (CUs) that perform joint encoding in the downlink and joint decoding in the uplink. Focusing on the uplink, an effective solution for the communication between BSs and the corresponding CU on the backhaul links is based on compressing and forwarding the baseband received signal from each BS. In the presence of ergodic fading, communicating the channel state information (CSI) from the BSs to the CU may require a sizable part of the backhaul capacity. In a prior work, this aspect was studied by assuming a Compress-Forward-Estimate (CFE) approach, whereby the BSs compress the training signal and CSI estimation takes place at the CU. In this work, instead, an Estimate-Compress-Forward (ECF) approach is investigated, whereby the BSs perform CSI estimation and forward a compressed version of the CSI to the CU. This choice is motivated by the information theoretic optimality of separate estimation and compression. Various ECF strategies are proposed that perform either separate or joint compression of estimated CSI and received signal. Moreover, the proposed strategies are combined with distributed source coding when considering multiple BSs. "Semi-coherent" strategies are also proposed that do not convey any CSI or training information on the backhaul links. Via numerical results, it is shown that a proper design of ECF strategies based on joint received signal and estimated CSI compression or of semi-coherent schemes leads to substantial performance gains compared to more conventional approaches based on non-coherent transmission or the CFE approach.

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arXiv2013

Lossy Computing of Correlated Sources with Fractional Sampling

This paper considers the problem of lossy compression for the computation of a function of two correlated sources, both of which are observed at the encoder. Due to presence of observation costs, the encoder is allowed to observe only subsets of the samples from both sources, with a fraction of such sample pairs possibly overlapping. The rate-distortion function is characterized for memory-less sources, and then specialized to Gaussian and binary sources for selected functions and with quadratic and Hamming distortion metrics, respectively. The optimal measurement overlap fraction is shown to depend on the function to be computed by the decoder, on the source statistics, including the correlation, and on the link rate. Special cases are discussed in which the optimal overlap fraction is the maximum or minimum possible value given the sampling budget, illustrating non-trivial performance trade-offs in the design of the sampling strategy. Finally, the analysis is extended to the multi-hop set-up with jointly Gaussian sources, where each encoder can observe only one of the sources.

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arXiv2013

Multi-Layer Transmission and Hybrid Relaying for Relay Channels with Multiple Out-of-Band Relays

In this work, a relay channel is studied in which a source encoder communicates with a destination decoder through a number of out-of-band relays that are connected to the decoder through capacity-constrained digital backhaul links. This model is motivated by the uplink of cloud radio access networks. In this scenario, a novel transmission and relaying strategies are proposed in which multi-layer transmission is used, on the one hand, to adaptively leverage the different decoding capabilities of the relays and, on the other hand, to enable hybrid decode-and-forward (DF) and compress-and-forward (CF) relaying. The hybrid relaying strategy allows each relay to forward part of the decoded messages and a compressed version of the received signal to the decoder. The problem of optimizing the power allocation across the layers and the compression test channels is formulated. Albeit non-convex, the derived problem is found to belong to the class of so called complementary geometric programs (CGPs). Using this observation, an iterative algorithm based on the homotopy method is proposed that achieves a stationary point of the original problem by solving a sequence of geometric programming (GP), and thus convex, problems. Numerical results are provided that show the effectiveness of the proposed multi-layer hybrid scheme in achieving performance close to a theoretical (cutset) upper bound.

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arXiv2013

Joint Precoding and Multivariate Backhaul Compression for the Downlink of Cloud Radio Access Networks

This work studies the joint design of precoding and backhaul compression strategies for the downlink of cloud radio access networks. In these systems, a central encoder is connected to multiple multi-antenna base stations (BSs) via finite-capacity backhaul links. At the central encoder, precoding is followed by compression in order to produce the rate-limited bit streams delivered to each BS over the corresponding backhaul link. In current state-of-the-art approaches, the signals intended for different BSs are compressed independently. In contrast, this work proposes to leverage joint compression, also referred to as multivariate compression, of the signals of different BSs in order to better control the effect of the additive quantization noises at the mobile stations (MSs). The problem of maximizing the weighted sum-rate with respect to both the precoding matrix and the joint correlation matrix of the quantization noises is formulated subject to power and backhaul capacity constraints. An iterative algorithm is proposed that achieves a stationary point of the problem. Moreover, in order to enable the practical implementation of multivariate compression across BSs, a novel architecture is proposed based on successive steps of minimum mean-squared error (MMSE) estimation and per-BS compression. Robust design with respect to imperfect channel state information is also discussed. From numerical results, it is confirmed that the proposed joint precoding and compression strategy outperforms conventional approaches based on the separate design of precoding and compression or independent compression across the BSs.

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arXiv2013

Multi-Layer Hybrid-ARQ for an Out-of-Band Relay Channel

This paper addresses robust communication on a fading relay channel in which the relay is connected to the decoder via an out-of-band digital link of limited capacity. Both the source-to-relay and the source-to-destination links are subject to fading gains, which are generally unknown to the encoder prior to transmission. To overcome this impairment, a hybrid automatic retransmission request (HARQ) protocol is combined with multi-layer broadcast transmission, thus allowing for variable-rate decoding. Moreover, motivated by cloud radio access network applications, the relay operation is limited to compress-and-forward. The aim is maximizing the throughput performance as measured by the average number of successfully received bits per channel use, under either long-term static channel (LTSC) or short-term static channel (STSC) models. In order to opportunistically leverage better channel states based on the HARQ feedback from the decoder, an adaptive compression strategy at the relay is also proposed. Numerical results confirm the effectiveness of the proposed strategies.

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arXiv2013

Linear Precoding and Equalization for Network MIMO with Partial Cooperation

A cellular multiple-input multiple-output (MIMO) downlink system is studied in which each base station (BS) transmits to some of the users, so that each user receives its intended signal from a subset of the BSs. This scenario is referred to as network MIMO with partial cooperation, since only a subset of the BSs are able to coordinate their transmission towards any user. The focus of this paper is on the optimization of linear beamforming strategies at the BSs and at the users for network MIMO with partial cooperation. Individual power constraints at the BSs are enforced, along with constraints on the number of streams per user. It is first shown that the system is equivalent to a MIMO interference channel with generalized linear constraints (MIMO-IFC-GC). The problems of maximizing the sum-rate(SR) and minimizing the weighted sum mean square error (WSMSE) of the data estimates are non-convex, and suboptimal solutions with reasonable complexity need to be devised. Based on this, suboptimal techniques that aim at maximizing the sum-rate for the MIMO-IFC-GC are reviewed from recent literature and extended to the MIMO-IFC-GC where necessary. Novel designs that aim at minimizing the WSMSE are then proposed. Extensive numerical simulations are provided to compare the performance of the considered schemes for realistic cellular systems.

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arXiv2013

Distributed and Cascade Lossy Source Coding with a Side Information "Vending Machine"

Source coding with a side information "vending machine" is a recently proposed framework in which the statistical relationship between the side information and the source, instead of being given and fixed as in the classical Wyner-Ziv problem, can be controlled by the decoder. This control action is selected by the decoder based on the message encoded by the source node. Unlike conventional settings, the message can thus carry not only information about the source to be reproduced at the decoder, but also control information aimed at improving the quality of the side information. In this paper, the analysis of the trade-offs between rate, distortion and cost associated with the control actions is extended from the previously studied point-to-point set-up to two basic multiterminal models. First, a distributed source coding model is studied, in which two encoders communicate over rate-limited links to a decoder, whose side information can be controlled. The control actions are selected by the decoder based on the messages encoded by both source nodes. For this set-up, inner bounds are derived on the rate-distortion-cost region for both cases in which the side information is available causally and non-causally at the decoder. These bounds are shown to be tight under specific assumptions, including the scenario in which the sequence observed by one of the nodes is a function of the source observed by the other and the side information is available causally at the decoder. Then, a cascade scenario in which three nodes are connected in a cascade and the last node has controllable side information, is also investigated. For this model, the rate-distortion-cost region is derived for general distortion requirements and under the assumption of causal availability of side information at the last node.

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arXiv2013

Cognitive Access Policies under a Primary ARQ process via Forward-Backward Interference Cancellation

This paper introduces a novel technique for access by a cognitive Secondary User (SU) using best-effort transmission to a spectrum with an incumbent Primary User (PU), which uses Type-I Hybrid ARQ. The technique leverages the primary ARQ protocol to perform Interference Cancellation (IC) at the SU receiver (SUrx). Two IC mechanisms that work in concert are introduced: Forward IC, where SUrx, after decoding the PU message, cancels its interference in the (possible) following PU retransmissions of the same message, to improve the SU throughput; Backward IC, where SUrx performs IC on previous SU transmissions, whose decoding failed due to severe PU interference. Secondary access policies are designed that determine the secondary access probability in each state of the network so as to maximize the average long-term SU throughput by opportunistically leveraging IC, while causing bounded average long-term PU throughput degradation and SU power expenditure. It is proved that the optimal policy prescribes that the SU prioritizes its access in the states where SUrx knows the PU message, thus enabling IC. An algorithm is provided to optimally allocate additional secondary access opportunities in the states where the PU message is unknown. Numerical results are shown to assess the throughput gain provided by the proposed techniques.

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arXiv2013

Robust Uplink Communications over Fading Channels with Variable Backhaul Connectivity

Two mobile users communicate with a central decoder via two base stations. Communication between the mobile users and the base stations takes place over a Gaussian interference channel with constant channel gains or quasi-static fading. Instead, the base stations are connected to the central decoder through orthogonal finite-capacity links, whose connectivity is subject to random fluctuations. There is only receive-side channel state information, and hence the mobile users are unaware of the channel state and of the backhaul connectivity state, while the base stations know the fading coefficients but are uncertain about the backhaul links' state. The base stations are oblivious to the mobile users' codebooks and employ compress-and-forward to relay information to the central decoder. Upper and lower bounds are derived on average achievable throughput with respect to the prior distribution of the fading coefficients and of the backhaul links' states. The lower bounds are obtained by proposing strategies that combine the broadcast coding approach and layered distributed compression techniques. The upper bound is obtained by assuming that all the nodes know the channel state. Numerical results confirm the advantages of the proposed approach with respect to conventional non-robust strategies in both scenarios with and without fading.

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arXiv2013

Blahut-Arimoto Algorithm and Code Design for Action-Dependent Source Coding Problems

The source coding problem with action-dependent side information at the decoder has recently been introduced to model data acquisition in resource-constrained systems. In this paper, an efficient algorithm for numerical computation of the rate-distortion-cost function for this problem is proposed, and a convergence proof is provided. Moreover, a two-stage code design based on multiplexing is put forth, whereby the first stage encodes the actions and the second stage is composed of an array of classical Wyner-Ziv codes, one for each action. Specific coding/decoding strategies are designed based on LDGM codes and message passing. Through numerical examples, the proposed code design is shown to achieve performance close to the lower bound dictated by the rate-distortion-cost function.

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arXiv2013

Source Coding with in-Block Memory and Causally Controllable Side Information

The recently proposed set-up of source coding with a side information "vending machine" allows the decoder to select actions in order to control the quality of the side information. The actions can depend on the message received from the encoder and on the previously measured samples of the side information, and are cost constrained. Moreover, the final estimate of the source by the decoder is a function of the encoder's message and depends causally on the side information sequence. Previous work by Permuter and Weissman has characterized the rate-distortion-cost function in the special case in which the source and the "vending machine" are memoryless. In this work, motivated by the related channel coding model introduced by Kramer, the rate-distortion-cost function characterization is extended to a model with in-block memory. Various special cases are studied including block-feedforward and side information repeat request models.

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arXiv2012

Multiple Access Channels with States Causally Known at Transmitters

It has been recently shown by Lapidoth and Steinberg that strictly causal state information can be beneficial in multiple access channels (MACs). Specifically, it was proved that the capacity region of a two-user MAC with independent states, each known strictly causally to one encoder, can be enlarged by letting the encoders send compressed past state information to the decoder. In this work, a generalization of the said strategy is proposed whereby the encoders compress also the past transmitted codewords along with the past state sequences. The proposed scheme uses a combination of long-message encoding, compression of the past state sequences and codewords without binning, and joint decoding over all transmission blocks. The proposed strategy has been recently shown by Lapidoth and Steinberg to strictly improve upon the original one. Capacity results are then derived for a class of channels that include two-user modulo-additive state-dependent MACs. Moreover, the proposed scheme is extended to state-dependent MACs with an arbitrary number of users. Finally, output feedback is introduced and an example is provided to illustrate the interplay between feedback and availability of strictly causal state information in enlarging the capacity region.

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arXiv2012

Heegard-Berger and Cascade Source Coding Problems with Common Reconstruction Constraints

For the HB problem with the CR constraint, the rate-distortion function is derived under the assumption that the side information sequences are (stochastically) degraded. The rate-distortion function is also calculated explicitly for three examples, namely Gaussian source and side information with quadratic distortion metric, and binary source and side information with erasure and Hamming distortion metrics. The rate-distortion function is then characterized for the HB problem with cooperating decoders and (physically) degraded side information. For the cascade problem with the CR constraint, the rate-distortion region is obtained under the assumption that side information at the final node is physically degraded with respect to that at the intermediate node. For the latter two cases, it is worth emphasizing that the corresponding problem without the CR constraint is still open. Outer and inner bounds on the rate-distortion region are also obtained for the cascade problem under the assumption that the side information at the intermediate node is physically degraded with respect to that at the final node. For the three examples mentioned above, the bounds are shown to coincide. Finally, for the HB problem, the rate-distortion function is obtained under the more general requirement of constrained reconstruction, whereby the decoder's estimate must be recovered at the encoder only within some distortion.

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arXiv2012

On the Transfer of Information and Energy in Multi-User Systems

The problem of joint transfer of information and energy for wireless links has been recently investigated in light of emerging applications such as RFID and body area networks. Specifically, recent work has shown that the additional requirements of providing sufficient energy to the receiver significantly affects the design of the optimal communication strategy. In contrast to most previous works, this letter focuses on baseline multi-user systems, namely multiple access and multi-hop channels, and demonstrates that energy transfer constraints call for additional coordination among distributed nodes of a wireless network. The analysis is carried out using information theoretic tools, and specific examples are worked out to illustrate the main conclusions.

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arXiv2012

Two-way Communication with Adaptive Data Acquisition

Motivated by computer networks and machine-to-machine communication applications, a bidirectional link is studied in which two nodes, Node 1 and Node 2, communicate to fulfill generally conflicting informational requirements. Node 2 is able to acquire information from the environment, e.g., via access to a remote data base or via sensing. Information acquisition is expensive in terms of system resources, e.g., time, bandwidth and energy and thus should be done efficiently by adapting the acquisition process to the needs of the application. As a result of the forward communication from Node 1 to Node 2, the latter wishes to compute some function, such as a suitable average, of the data available at Node 1 and of the data obtained from the environment. The forward link is also used by Node 1 to query Node 2 with the aim of retrieving suitable information from the environment on the backward link. The problem is formulated in the context of multi-terminal rate-distortion theory and the optimal trade-off between communication rates, distortions of the information produced at the two nodes and costs for information acquisition at Node 2 is derived. The issue of robustness to possible malfunctioning of the data acquisition process at Node 2 is also investigated. The results are illustrated via an example that demonstrates the different roles played by the forward communication, namely data exchange, query and control.

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