In this paper, amplify-and-forward beamforming (AFB) is considered to establish a communication, through wireless sensor networks (WSNs) of K sensor nodes, from a source to a receiver in the presence of both scattering and interference. All sources send their data to the WSN during the first time slot, while the nodes forward a properly weighted version of their received signals during the second slot. These weights are properly selected to maximize the desired power while completely canceling the interference signals. We show, however, that they depend on information locally unavailable at each node, making the zero-forcing beamformer (ZFB) unsuitable for WSNs, due to the prohibitive data exchange overhead and the power depletion it would require. To address this issue, we exploit the asymptotic expression at large K of the ZFB weights that is locally computable at every node and, further, well-approximates their original counterparts. The performance of the resulting new distributed ZFB (DZFB) version is analyzed and compared with the conventional ZFB and two other distributed AFB benchmarks: the monochromatic (i.e., single-ray) AFB whose design neglects the presence of scattering and the bichromatic AFB which relies on an efficient two-ray channel approximation valid only for low angular spread (AS). We show that the proposed DZFB outperforms its monochromatic and bichromate counterparts while incurring much less overhead and power depletion than ZFB. We show also that it is able to provide optimal performance even in highly scattered environments as in the latter.

User-centric wireless access virtualization (WAV) allows each user to be served by a set of carefully selected transmission points (TPs) forming a user-specific virtual base station (uVBS) adapted to its environment and quality-of-service (QoS) requirement. In this way, this new concept breaks away from the conventional cell-centric architecture to provide boundaryless communications in future fifth-generation (5G) networks. This fundamental structural 5G evolution and the ultra-dense multi-tier heterogeneous context foreseen in such networks require an inevitable rethinking of efficient scalable TP clustering. As such, this paper proposes three innovative low-cost clustering approaches that enable the user-centric WAV and provide dynamic, adaptive, and overlapping TP clusters while requiring not only negligible overhead cost but also minimum signaling changes at both network and user sides. Contrary to existing clustering techniques, the new ones we propose better leverage the 5G features such as extreme densification and massive connectivity as well as new concepts such as millimeter wave (mmWave) spectrum and massive multiple-input-multiple-output (MIMO). The simulations show that they may achieve until 154% and 282% of throughput and coverage gains, respectively. Furthermore, these approaches are flexible enough to be adapted to different network dimensions (i.e., space and time), thereby paving the way for achieving the dramatic performance improvements required by the 5G networks to cope with the upcoming mobile data deluge.

We propose a new collaborative beamforming (CB) solution robust against major implementation impairments over dual-hop transmissions from a source to a destination communicating through a wireless sensor network (WSN) of K nodes. In the first time slot, the source sends its signal to the WSN while, in the second, each node forwards its received signal after multiplying it by a properly selected beamforming weight. The latter aims to minimize the received noise power while maintaining the desired power equal to unity. These weights depend a priori on some channel state information (CSI) parameters. Hence, the latter have to be estimated locally at each node thereby resulting in implementation errors that could severely hinder CB performance. Exploiting an efficient asymptotic approximation at large K, we develop alternative CB solutions that not only account for estimation errors, but also adapt to different implementation scenarios and wireless propagation environments ranging from monochromatic (i.e., scattering-free) to polychromatic (i.e., P-DCB) ones. Besides, in contrast to existing techniques, our new CB solutions are distributed (i.e., DCB) in that they do not require any information exchange among nodes, thereby dramatically improving both WSN spectral and power efficiencies. Simulation results confirm that the proposed DCB techniques are much more robust against implementations errors than their benchmarks at much lower complexity.

This paper develops an innovative scalable and low-cost QoS-based user equipment (UE) virtualization (UEV) scheme that capitalizes on the massive connectivity and the enhanced resources of the new UE generation in terms of connectivity, computing, battery/power, etc. Exploiting the need/excess duality and the heterogeneity in such resources at the UE plan, we form virtual UEs (VUE)s, dynamically, owing to a carefully-designed time-adjusting scheme for the selection of the proper cooperative UE sets. The new UEV scheme is able to adapt to each target UE (TUE) environment, meet its demands, and scale with its needs, offers a reliable and efficient yet low-cost inter-UE cooperation, reduces the overhead and power consumption with respect to conventional approaches, and substantially reduces the number of communication links and, hence, incurs much less interference. System-level simulation results show that the proposed QoS-based UEV scheme largely outperforms the “dummy UEs” approach.

In this paper, we develop a new dynamic utility for wireless access virtualization (WAV) optimization embodying highly-dimensional time-varying multi-criteria metrics (i.e., CAPEX and OPEX costs, QoS or QoE, multi-tier and/or multi-RAT HetNets, etc.) that gauge the best deployment and viability scenarios of cloud (C)- and fog (F)-RANs within legacy networks. Exploiting the powerful tool of graph theory, we devise a progressive greyfield WAV strategy that optimizes our dynamic utility through an efficient combination of C- and F-RANs. This strategy is able to readjust very quickly to any changes in existing or new constraints as they evolve or occur in time, respectively. The resulting optimized hybrid RAN deployment outperforms both the greenfield and the pre-planed greyfield “turnkey” WAV strategies.

We propose a novel range-free localization algorithm for wireless sensor networks (WSN)s that is robust against the anisotropic signal attenuation induced by fading, shadowing, and interference, etc., present in any wireless channel, and hereby develop a new distance estimation (DE) approach able to efficiently derive distances' estimates in closed form. Exploiting artificial neural networks (ANN)s, we also develop a power-efficient DE correction mechanism that properly accounts for anisotropic signal attenuation. Simulation results show that the proposed algorithm significantly outperforms most representative range-free localization algorithms, not only in accuracy, but also in robustness against anisotropic attenuation.

In this paper, we develop a new dynamic utility for wireless access virtualization (WAV) optimization embodying highly-dimensional time-varying multi-criteria metrics (i.e., CaPeX and OPEX costs, QoS or QoE, multitier and/or multi-RAT HetNets, etc.) that gauge the best deployment and viability scenarios of cloud (C)- and fog (F)-RANs within legacy networks. Exploiting the powerful tool of graph theory, we devise a progressive greyfield WAV strategy that optimizes our dynamic utility through an efficient combination of C- and F-RANs. This strategy is able to readjust very quickly to any changes in existing or new constraints as they evolve or occur in time, respectively. The resulting optimized hybrid RAN deployment outperforms both the greenfield and the pre-planed greyfield ”turnkey” WAV strategies.

In this paper, amplify-and-forward beamforming (AFB) is considered to establish a reliable communication between devices in networked smart cities. All sources send their data during the first time slot while the cooperative terminals forward a properly weighted version of their received signals during the second. These zero-forcing AFB (ZFB) weights are properly selected to maximize the desired power while completely canceling the interference signals. We show, however, that their implementation requires a huge terminals' information exchange, making ZFB unsuitable for smart cities where the overhead and power restrictions are very stringent. To address this issue, we exploit the asymptotic expression at large K of the ZFB weights whose computation requires much less information exchange and, further, well-approximate their original counterparts. The performance of the proposed beamforming is analyzed and compared to ZFB and monochromatic (i.e., single-ray) AFB (MB) whose design neglects the presence of scattering.

In this paper, we develop a novel optimal anchors placement strategy tailored for anisotropic WSNs. By resorting to the well-known particle swarm optimization (PSO), we derive the optimal anchors' positions that minimize the average location estimation error (LEE). We show that our placement strategy provides substantial accuracy gains if used instead of the conventional ones and that it is able to reduce not only the average LEE but also the LEE itself and, hence, guarantees high accuracy for any WSN configuration.

In this paper, we propose a novel range-free localization algorithm tailored for mobile ad hoc networks (MANET)s. In contrast to most existing range-free techniques, we take into account the nodes mobility and hence enable the nodes to estimate their positions using solely their locally-available information, thereby avoiding any unnecessary costs in overhead and power that would have been incurred if information exchange between nodes were required. Furthermore, we show that the proposed algorithm outperforms in accuracy the best representative range-free algorithms. In contrast to the latter, it is able to compensate the nodes mobility effects when the nodes' speeds are moderate.

To localize multi-hop wireless sensor networks (WSN) nodes, only the hop-based information (i.e., hops' number, average hop size, etc.) have been so far exploited by rangefree techniques, with poor-accuracy, however. In this paper, we show that localization accuracy may greatly benefit from joint exploitation, at no cost, of the information already provided by the forwarding nodes between each anchor (i.e., position-aware) and sensor nodes pair. As such, we develop a novel rangefree localization algorithm, derive its average location estimation error (LEE) in closed-form, and compare it in LEE performance with the best representative algorithms in the literature. We show that the proposed algorithm outperforms in accuracy all its counterparts. In contrast to the latter, we further prove that it is able to achieve a LEE average and variance of about 0 when the number of sensors is large enough, thereby achieving an unprecedented accuracy performance among rangefree techniques.

In this paper, we consider a collaborative beam-former (CB) design that achieves a dual-hop communication from a source to a receiver in highly-scattered environments, through a wireless network comprised of K independent terminals. The weights of the considered CB design at these terminals, derived to maximize the received signal-to-noise ratio (SNR) subject to constraint over the terminals' total transmit power, have expressions that inevitably depend on some form of the channel state information (CSI). Only those requiring the local CSI (LCSI) available at their respective terminals lend themselves to a truly distributed implementation. The latter has the colossal advantage of significantly minimizing the huge overhead resulting otherwise from non-local CSI (NLCSI) exchange required between terminals, which becomes prohibitive for large K and/or high Doppler. We derive the closed-form expression of the SNR-optimal CB (OCB) and verify that it is a NLCSI-based design. Exploiting, however, the polychromatic (i.e., multi-ray) structure of scattered channels as a superposition of L impinging rays or chromatics, we propose a novel LCSI-based distributed CB (DCB) design that requires a minimum overhead cost and, further, performs nearly as well as its NLCSI-based OCB counterpart. Furthermore, we prove that the proposed LCSI-based DCB outperforms two other DCB benchmarks: the monochromatic (i.e., single-ray) DCB (M-DCB) whose design ignores the presence of scattering and the bichromatic (i.e., two-ray) DCB (B-DCB) which relies on an efficient polychromatic-channel approximation by two rays when the angular spread is relatively small.

To localize the wireless sensor networks nodes, only the hop-based information (i.e., hops' number, average hop size, and so on) has been, so far, exploited by range-free techniques, with poor-accuracy, however. In this paper, we show that localization accuracy may greatly benefit from joint exploitation, at no cost, of the information already provided by the forwarding nodes (i.e., relays) between each anchor (i.e., position aware) and sensor nodes pair. As such, we develop a novel range-free localization algorithm, derive its average location estimation error (LEE) in closed-form, and compare it in LEE performance with the best representative algorithms in the literature. We show that the proposed algorithm outperforms them in accuracy. In contrast to the latter, we further prove that it is able to achieve an LEE average and variance of about 0 when the number of sensors is large enough, thereby achieving an unprecedented accuracy performance among range-free techniques.

In this paper, we propose a novel low-cost localization algorithm tailored for multihop heterogeneous wireless sensor networks (HWSNs) where nodes' transmission capabilities are different. This characteristic, if not taken into account when designing the localization algorithm, may severely hinder its accuracy. Assuming different nodes' transmission capabilities, we develop two different approaches to derive the expected hop progress (EHP). Exploiting the latter, we propose a localization algorithm that is able to accurately locate the sensor nodes owing to a new low-cost implementation. Furthermore, we develop a correction mechanism, which complies with the heterogeneous nature of wireless sensor networks (WSNs) to further improve localization accuracy without incurring any additional costs. Simulations results show that the proposed algorithm, whether applied with or without correction, outperforms in accuracy the most representative WSN localization algorithms.

In this paper, we consider a collaborative beamforming (CB) technique to achieve a dual-hop communication from a source surrounded by MIinterferences to a receiver, through a wireless network comprised of K independent terminals. The CB weights are designed so as to minimize the interferences plus noises' powers while maintaining the received power from the source to a constant level. We show, however, that they are intractable in closed-form due to the complexity of the polychromatic channels arising from the presence of scattering in real-world environments. By recurring to a two-ray channel approximation proved valid at relatively low angular spread (AS) values, we are able to derive the new optimum weights and prove that they could be locally computed at each terminal, thereby complying with the distributed feature of the network of interest. The so-obtained bichromatic distributed collaborative beamforming (B-DCB) is then analyzed and compared in performance to the monochromatic CB (MCB), whose design does not account for scattering, and the optimal CSI-based CB (OCB). It is shown that the proposed B-DCB outperforms its counterparts in real-world environments.

In this paper, we propose a novel low-cost localization algorithm tailored for multi-hop heterogeneous wireless sensor networks (HWSNs) where nodes' transmission capabilities are different. This characteristic, if not taken into account when designing the localization algorithm, may severely hinder its accuracy. Assuming different nodes' transmission capabilities, we develop a novel approach to derive the expected hop progress (EHP). Exploiting the latter, we propose a localization algorithm that is able to accurately locate the sensor nodes owing to a new low-cost implementation. Furthermore, we develop a correction mechanism which complies with the heterogeneous nature of WSNs to further improve localization accuracy without incurring any additional costs. Simulations results show that the proposed algorithm, whether applied with or without correction, outper-forms in accuracy the most representative WSN localization algorithms.

In this paper, we consider a dual-hop communication from a source surrounded by MIinterferences to a receiver, through a wireless network comprised of K independent terminals. In the first time slot, all sources send their signals to the network, whereas in the second time slot, the terminals multiply the received signal by their respective beamforming weights and forward the resulting signals to the receiver. We design these weights so as to minimize the interferences plus noises' powers while maintaining the received power from the source to a constant level. We show, however, that they are intractable in closed form due to the complexity of the polychromatic channels arising from the presence of scattering. By resorting to a two-ray channel approximation proved valid at relatively low angular spread (AS) values, we are able to derive the new optimum weights and prove that they could be locally computed at each terminal, thereby complying with the distributed feature of the network of interest. The so-obtained bichromatic distributed collaborative beamforming (B-DCB) is then analyzed and compared in performance to the monochromatic CB (MCB), whose design does not account for scattering, and the optimal CSI-based CB (OCB). Comparisons are made under both ideal and real-world conditions where we account for implementation errors and the overhead incurred by each CB solution. They reveal that the proposed B-DCB always outperforms MCB in practice; and that it approaches OCB in lightly to moderately scattered environments under ideal conditions and outperforms it under real-world conditions even in highly scattered environments. In such conditions, indeed, the B-DCB operational regions in terms of AS values over, which it is favored against OCB could reach until 50° and hence cover about the entire span of AS values.

In this paper, we propose a novel range-free localization algorithm tailored for anisotropic wireless sensors networks (WSN)s. Using the proposed algorithm, each regular or positionunaware node estimates its distances only to reliable anchors or position-aware nodes. The latter are properly chosen following a new reliable anchor selection strategy that ensures an accurate distance estimation making thereby our localization algorithm more precise. Indeed, simulations suggest that it outperforms the best representative range- free localization algorithms currently available in the literature in terms of accuracy.

In this paper, we propose a novel range-free localization algorithm tailored for heterogeneous wireless sensor networks (WSNs), where nodes have different transmission capabilities. Two different approaches are developed to accurately derive the expected hop progress (EHP). It is shown that the obtained EHP depends solely on the information locally available at each node and, hence, can be computed in a localized manner. Furthermore, a localization correction mechanism which accounts for the heterogeneous nature of WSNs is developed. Simulations results show that the proposed algorithm, whether with or without correction, outperforms in accuracy the most representative range-free localization algorithms in the literature.

In this paper, a collaborative beamformer (CB) is considered to achieve a dual-hop communication from a source to a receiver, through a wireless network comprised of K independent terminals. Whereas previous works neglect the scattering effect to assume a plane-wave single-ray propagation channel termed here as monochromatic (with reference to its angular distribution), a multi-ray channel termed as polychromatic due to the presence of scattering is considered, thereby broadening the range of applications in real-world environments. Taking into account the scattering effects, the weights of the so-called polychromatic CB (P-CB) are designed so as to minimize the received noise power while maintaining the desired power equal to unity. Unfortunately, their derivation in closed-form is analytically intractable due to the complex nature of polychromatic channels. However, when the angular spread (AS) is relatively small to moderate, it is proven that a polychromatic channel may be properly approximated by two rays and hence considered as bichromatic. Exploiting this fact, we introduce a new bichromatic CB (B-CB) whose weights can be derived in closed-form and, further, accurately approximate the P-CB's weights. Yet these weights, which turn out to be locally uncomputable at every terminal, are unsuitable for a distributed implementation. In order to circumvent this shortcoming, we exploit the asymptotic expression at large K of the B-CB whose weights could be locally computed at every terminal and, further, well-approximate their original counterparts. The performances of the so-obtained bichromatic distributed CB (B-DCB) and its advantages against the monochromatic DCB (M-DCB), which is designed without accounting for scattering, are analytically proved and further verified by simulations at practical values of K.

In this paper, we propose a novel range-free localization algorithm able to reduce errors due to mapping the hops into distance units. Using the proposed algorithm, the mean hop size h̅sis locally derived at each regular or position-unaware node, thereby avoiding its broadcast by anchors (i.e., a few nodes aware of their exact position) as usually required in current state-of-the-art solutions and, hence, resulting in less battery power depletion. The analytical expression of h̅sis derived for different node distributions. Furthermore, it is shown that it is possible to locally compute h̅sat each regular node with or even without prior knowledge of the node distribution. Simulations results show that the proposed scheme outperforms the most representative range-free localization schemes in terms of accuracy.

Three main collaborative beamforming (CB) designs based on different channel models could be applied in real-world environments where local scattering and implementation imperfections might exist: the optimal CSI-based CB (OCB), the conventional or monochromatic (i.e., single-ray) distributed CB (M-DCB), and the recently developed bichromatic (i.e., two-ray) distributed CB (B-DCB). In this paper, we perform an analytical comparison, under practical constraints, between these CB designs in terms of achieved signal-to-noise ratio (SNR) as well as achieved throughput. Assuming the presence of local scattering in the source vicinity and accounting for implementation errors incurred by each CB design, we derive for the first time closed-form expressions of their true achieved SNRs. At a low angular spread (AS) where both designs nominally achieve the same SNR in ideal conditions, we show that the B-DCB always outperforms OCB, more so and at larger regions of AS values when errors increase. Excluding exceptional circumstances of unrealistic low quantization levels (i.e., very large quantization errors) hard to justify in practice, we also show that the new B-DCB always outperforms the M-DCB as recently found nominally in ideal conditions. This work is also the first to push the performance analysis of CB to the throughput level by taking into account the feedback overhead cost incurred by each design. We prove both by concordant analysis and simulations that the B-DCB is able to outperform, even for high AS values, the OCB which is penalized by its prohibitive implementation overhead, especially for a large number of collaborating terminals and/or high Doppler frequencies.

In this paper, a minimum variance distortionless response (MVDR) collaborative beamformer (CB) is considered to achieve a dual-hop communication from a far-field source surrounded by several interfering transmitters to a receiver, through a wireless network comprised of K independent terminals. Whereas the previous works assumed a model of plane wavefronts, here, a local scattering in the source and interferences vicinities is considered, thereby broadening the range of applications in real-world environments. It is shown that the required bandwidth allocation to the MVDR CB implementation linearly increases with K and becomes prohibitive in some applications where the number of terminals is typically large. Aiming to improve the system's spectrum efficiency, a novel distributed collaborative beamformer (DCB) whose implementation does not require any bandwidth allocation and, further, that well-approximates its MVDR CB counterpart is then proposed. The performance of the proposed technique is analyzed and its net advantages against the scattering-free DCB technique, which is designed without taking into account the presence of local scattering in the source and interferences vicinities, are proved.

In this paper, transmit and receive collaborative beamforming (CB) techniques are considered to achieve a dualhop communication from a source to a receiver, through a wireless network comprised of K independent terminals. Whereas the previous works assumed a model of plane wavefronts, here, a local scattering in the source or receiver vicinity is considered, thereby broadening the range of applications in real-world environments. Taking into account the local scattering, these CB techniques aim to maintain the beamforming response in the desired direction equal to unity. It is shown that the so-obtained collaborative beamformers are not suitable for a distributed implementation. We hence propose a novel beamformer solution that can be implemented in a distributed fashion and, further, well-approximates both transmit and receive collaborative beam-formers. The performance of the proposed distributed CB (DCB) technique is analyzed and its advantages against the conventional DCB technique, which is designed without taking into account the presence of local scattering in the source or receiver vicinity, are analytically proved and further verified by simulations.

In this paper, transmit and receive collaborative beamforming (CB) techniques are considered to achieve a dualhop communication from a source to a receiver, through a wireless sensor network (WSN). Whereas the previous works assumed a model of plane wavefronts, here, a local scattering in the source or receiver vicinity is considered, thereby broadening the range of applications in real-world environments. Taking into account the local scattering, these beamformers aim to maintain the beamforming response in the desired direction equal to unity. It is shown that the so-obtained beamformers are not suitable for a distributed implementation in WSNs. We hence propose a novel distributed collaborative beamforming (DCB)technique that can be implemented in a distributed fashion and, further, well-approximates both transmit and receive CB techniques. The performance of the proposed DCB is analyzed and its advantages against the conventional DCB, which is designed without taking into account the presence of local scattering in the source or receiver vicinity, are analytically proved and are further verified by simulations.

ABSTRACT Three main collaborative beamforming (CB) solutions based on different channel models exist: the optimal CSI‐based CB (OCB), the conventional or monochromatic (i.e., single‐ray) distributed CB (M‐DCB), and the recently developed bichromatic (i.e., two‐ray) distributed CB (B‐DCB). In this paper, we perform an analytical comparison, under practical constraints, between these CB solutions in terms of achieved signal‐to‐noise ratio (SNR) as well as achieved throughput. Assuming the presence of local scattering in the source vicinity and accounting for implementation errors incurred by each CB solution, we derive for the first time closed‐form expressions of their true achieved SNRs. For low angular spread (AS), where both solutions nominally achieve the same SNR in ideal conditions, we show that the B‐DCB always outperforms OCB, more so and at larger regions of AS values when errors increase. Excluding exceptional circumstances of unrealistic low quantization levels (i.e., very large quantization errors) that are hard to justify in practice, we also show that the new B‐DCB always outperforms the M‐DCB as recently found nominally in ideal conditions. This work is also the first to push the performance analysis of CB to the throughput level by taking into account the feedback overhead cost incurred by each solution. We prove both by concordant analysis and simulations that the B‐DCB is able to outperform, even for high AS values, the OCB which is penalized by its prohibitive implementation overhead, especially for a large number of collaborating terminals and/or high Doppler frequencies. Indeed, it is shown that the operational regions in terms of AS values over which the new B‐DCB is favored against OCB in terms of achieved throughput can reach up to 40°. Copyright © 2012 John Wiley & Sons, Ltd.

A collaborative receive beamforming technique is proposed that lends itself to a distributed implementation in wireless sensor networks (WSNs). In the first time slot, the transmitter of interest along with several interfering terminals send their signals while in the second time slot K nodes multiply their received signals with properly selected beamforming weights and forward the resulting signals to the receiver. The beamforming weights are selected such that they depend only on the locally-available knowledge at the relaying nodes while aiming to maximize the signal-to-interference-plus-noise ratio (SINR) at the receiver. The beampattern expression is obtained and its analytical properties are studied.