Panos N. Alevizos

Coherent Detection and Channel Coding for Bistatic Scatter Radio Sensor Networking

With rapid advances of scatter radio systems, the principle of reflection rather than active transmission employed by backscatter sensor networks, has emerged as a potential key enabler for low-cost, large-scale and dense ubiquitous sensor networks. Despite the presence of three different unknown channel links due to the bistatic setup (i.e., carrier emitter and receiver are dislocated), as well as multiple unknown scatter radio-related parameters, this work offers a novel coherent receiver of frequency-shift keying (FSK) modulation for the bistatic scatter radio channel. Furthermore, with the objective of range maximization, specific short block-length cyclic channel codes are utilized. The proposed approach requires minimum encoding complexity, ideal for resource-constrained, ultra-low power (e.g. microcontroller unit-based), low-bit rate scatter radio tags, adheres to simple low-complexity decoding at the receiver and achieves high-order signal diversity. Analysis is followed by experimental validation with a commodity software-defined radio (SDR) reader and a custom scatter radio tag; tag-to-reader ranges up to 150 meters are demonstrated with as little as 20 milliWatt transmission power, increasing sensing ranges by approximately 10 additional meters, compared to state-of-the-art bistatic scatter radio receivers. With the imminent emergence of backscatter sensor networks, this work serves as a small step forward towards the realization of low-cost, low-power, increased-range, wireless sensing applications.

Noncoherent composite hypothesis testing receivers for extended range bistatic scatter radio WSNs

Scatter radio, i.e., communication by means of reflection, has emerged as a potential key-enabling technology for ultra low-cost, large-scale, ubiquitous sensor networking. This work studies bistatic scatter radio, where carrier emitter is dislocated from the software defined radio receiver. The ultimate goal of this work is to extend the communication range. Towards that goal, noncoherent channel coding is incorporated in bistatic scatter radio. Short block length channel codes are proposed with ultra low-complexity encoding, ideal for resource-constraint scatter radio tags. A novel composite hypothesis testing decoding rule is designed, that achieves high diversity order through interleaving. Simulation results corroborate the efficiency of the proposed noncoherent schemes over Rician fading and demonstrate that noncoherent setups offer comparable bit error rate (BER) performance with respect to coherent counterparts.

Channel coding for increased range bistatic backscatter radio: Experimental results

This work offers concrete, low-complexity (small codeword length) channel coding for the bistatic scatter radio channel, complementing the uncoded setup of recent work. The theoretical design is experimentally validated with a commodity software-defined radio (SDR) reader; tag-to-reader ranges up to 134 meters are demonstrated with 13 dBm emitter power, while bit error rate (BER) is reduced or range is increased, on the order of 10 additional meters (or more) compared to the uncoded case, with linear encoding at the tag/sensor and simple decoding at the reader. Even though designing low-complexity channel coding schemes is a challenging problem, this work offers a concrete solution that could accelerate the adoption of scatter radio for large-scale wireless sensor networks, i.e. backscatter sensor networks.

Log-Linear-Complexity GLRT-Optimal Noncoherent Sequence Detection for Orthogonal and RFID-Oriented Modulations

Orthogonal modulation, for example, frequency-shift keying (FSK) or pulse-position modulation (PPM), is primarily used in relatively-low-rate communication systems that operate in the power-limited regime. Optimal noncoherent detection of orthogonally modulated signals takes the form of sequence detection and has exponential (in the sequence length) complexity when implemented through an exhaustive search among all possible sequences. In this work, for the first time in the literature, we present an algorithm that performs generalized-likelihood-ratio-test (GLRT) optimal noncoherent sequence detection of orthogonally modulated signals in flat fading with log-linear (in the sequence length) complexity. Moreover, for Rayleigh fading channels, the proposed algorithm is equivalent to the maximum-likelihood (ML) noncoherent sequence detector. Simulation studies indicate that the optimal noncoherent FSK detector attains coherent-detection performance when the sequence length is on the order of 100, offering a 3-5 dB gain over the typical energy (single-symbol) detector. While the conventional exhaustive-search approach becomes infeasible for such sequence lengths, the proposed implementation requires a log-linear only number of operations, opening new avenues for practical deployments. Finally, we show that our algorithm also solves efficiently the optimal noncoherent sequence detection problem in contemporary radio frequency identification (RFID) systems.

Non-uniform directional dictionary-based limited feedback for massive MIMO systems

This work proposes a new limited feedback channel estimation framework. The proposed approach exploits a sparse representation of the double directional wireless channel model involving an over complete dictionary that accounts for the antenna directivity patterns at both base station (BS) and user equipment (UE). Under this sparse representation, a computationally efficient limited feedback algorithm that is based on single-bit compressive sensing is proposed to effectively estimate the downlink channel. The algorithm is lightweight in terms of computation, and suitable for real-time implementation in practical systems. More importantly, under our design, using a small number of feedback bits, very satisfactory channel estimation accuracy is achieved even when the number of BS antennas is very large, which makes the proposed scheme ideal for massive MIMO 5G cellular networks. Judiciously designed simulations reveal that the proposed algorithm outperforms a number of popular feedback schemes in terms of beam forming gain for subsequent downlink transmission, and reduces feedback overhead substantially when the BS has a large number of antennas.

Noncoherent Short Packet Detection and Decoding for Scatter Radio Sensor Networking

Scatter radio, i.e., communication by means of reflection, has been recently proposed as a promising technology for low-power wireless sensor networks (WSNs). Specifically, this paper offers noncoherent receivers in scatter radio frequency-shift keying, for either channel-coded or uncoded scatter radio reception, in order to eliminate the need for training bits of coherent schemes (for channel estimation) at the packet preamble. Noncoherent symbol-by-symbol and sequence detectors based on hybrid composite hypothesis test (HCHT) and generalized likelihood-ratio test, for the uncoded case and noncoherent decoders based on HCHT, for small block-length channel codes, are derived. Performance comparison under Rician, Rayleigh, or no fading, taking into account fixed energy budget per packet is presented. It is shown that the performance gap between coherent and noncoherent reception depends on whether channel codes are employed, the fading conditions (e.g., Rayleigh versus Rician versus no fading), as well as the utilized coding interleaving depth; the choice of one coding scheme over the other depends on the wireless fading parameters and the design choice for extra diversity versus extra power gain. Finally, experimental outdoor results at 13-dBm transmission power corroborate the practicality of the proposed noncoherent detection and decoding techniques for scatter radio WSNs.

Coherent detection and channel coding for bistatic scatter radio sensor networking

With rapid advances of scatter radio systems, the principle of reflection rather than active transmission employed by backscatter sensor networks, has emerged as a potential key enabler for low-cost, large-scale and dense ubiquitous sensor networks. Despite the presence of three different unknown channel links due to the bistatic setup (i.e., carrier emitter and receiver are dislocated), as well as multiple unknown scatter radio-related parameters, this work offers a novel coherent receiver of frequency-shift keying (FSK) modulation for the bistatic scatter radio channel. Furthermore, with the objective of range maximization, specific short block-length cyclic channel codes are utilized. The proposed approach requires minimum encoding complexity, ideal for resource-constrained, ultra-low power (e.g. microcontroller unit-based), low-bit rate scatter radio tags, adheres to simple low-complexity decoding at the receiver and achieves high-order signal diversity. Analysis is followed by experimental validation with a commodity software-defined radio (SDR) reader and a custom scatter radio tag; tag-to-reader ranges up to 150 meters are demonstrated with as little as 20 milliWatt transmission power, increasing sensing ranges by approximately 10 additional meters, compared to state-of-the-art bistatic scatter radio receivers. With the imminent emergence of backscatter sensor networks, this work serves as a small step forward towards the realization of low-cost, low-power, increased-range, wireless sensing applications.

Bistatic architecture provides extended coverage and system reliability in scatter sensor networks

Scatter radio is a promising enabling technology for ultra-low power consumption and low monetary cost, largescale wireless sensor networks. The two most prominent scatter radio architectures, namely the monostatic and the bistatic, are compared. Comparison metrics include bit error probability under maximum-likelihood detection for the single-user case and outage probability for the multi-user case (including tight bounds). This work concretely shows that the bistatic architecture improves coverage and system reliability. Utilizing this fact, a bistatic, digital scatter radio sensor network, perhaps the first of its kind, using frequency-shift keying (FSK) modulation and access, is implemented and demonstrated.

Factor graph-based distributed frequency allocation in wireless sensor networks

As wireless sensor networks (WSNs) become denser, simultaneous transmissions (on the same time slot and frequency channel of two or more terminals) may cause severe interference. Appropriate interference-aware allocation is a complex problem and distributed frequency allocation is even harder. This work studies the problem of assigning frequency channels for a given WSN routing tree, such that: a) time scheduling and frequency allocation are performed in a distributed way, i.e. information exchange is only performed among neighboring terminals, and b) detection of potential interfering terminals is simplified. The algorithm imprints space, time and frequency constraints, assuming half-duplex, single-antenna radios into a loopy factor graph (FG) and performs iterative message passing. Convergence to a valid solution is addressed based on appropriate modifications of the resulting message passing inference algorithm. The proposed algorithm is compared with two distributed frequency allocation algorithms, based on game-theory or min-max interference control. It is shown that the proposed distributed algorithm offers comparable performance with state-of-the-art, even though it utilizes simplified interfering terminals set detection.

Cooperative localization in wireless networks under bandwidth constraints

This work studies algorithms that require minimum size of exchanged messages between cooperating (for localization purposes) nodes. It is motivated by long-baseline (LBL) acoustic positioning in underwater systems, where acoustic modems are narrow-band and thus, exchanging large amounts of data among network nodes is prohibitive. Bandwidth-limited versions of cooperative localization algorithms are proposed that achieve two- to three-orders of magnitude reduction of total exchanged numbers, for the studied scenario. Despite the size reduction of the exchanged messages, localization accuracy is not compromised, compared to state-of-the-art wide-band cooperative localization. Furthermore, new bandwidth- and computation-efficient versions are proposed and tested for given topology. The algorithms have been evaluated with Gaussian, as well as non-Gaussian unimodal ranging error models.