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In millimeter-wave (mm-wave) cellular networks, directional antenna arrays are typically adopted to mitigate the severe propagation loss. However, the interference caused by such highly directional beams may, in turn, result in a significant number of transmission failures, especially for dense networks. To tackle this problem, we propose two inter-cell interference coordination (ICIC) schemes in mm-wave bands: one is merely based on the path loss incorporating the blockage effect (PL-ICIC); the other considers both path loss and directivity gain (PG-ICIC). To fully investigate both schemes, we first derive an exact expression for the success probability (reliability) of the typical (served) user. We further provide an asymptotic analysis for the success probability and propose an effective approximation based on the asymptotic signal-to-interference ratio (SIR) gain relative to no ICIC. Secondly, to incorporate the cost of ICIC schemes, we derive the approximate normalized throughput taking into account that some users cannot be served due to limited resources. Numerical results show that the two proposed schemes provide significant reliability improvements in the low-SIR regime, and the higher the number of antennas, the wider the SIR range for which there is an improvement. In addition, compared with PL-ICIC, PG-ICIC balances the available resources among all users well.

In this paper, we theoretically analyse the uplink (UL) and downlink (DL) performance of massive multiple-input and multiple-output (mMIMO) networks, in term of coverage probability, cell spectral efficiency and network area spectral efficiency, using stochastic geometry. A sophisticated but yet practical system model is considered, taking into account a path loss model differentiating line-of-sight and non-line-of-sight transmissions, an idle mode capability at the base stations and a finite user density. Our analysis pays particular attention to the existence of a finite number of UL pilots for channel estimation and the effect of pilot contamination. We study for the first time the joint impact of the number of UL pilot sequences, the user density, and the base-station density on the pilot contamination issue in a mMIMO network, which in turn characterizes the DL and UL network performance. Moreover, using the proposed framework, we investigate two different scheduling problems —UE and pilot scheduling—, to find the optimal simultaneously scheduled UE density per time-frequency resource as well as the optimal UL pilot number to maximise the spectral efficiency.

TeraHertz (THz) communications are envisioned as a promising technology, owing to its unprecedented multi-GHz bandwidth. One fundamental challenge when moving to new spectrum is to understand the science of radio propagation and develop an accurate channel model. In this paper, a wideband channel measurement campaign between 130 GHz and 143 GHz is investigated in a typical meeting room. Directional antennas are utilized and rotated for resolving the multi-path components (MPCs) in the angular domain. With careful system calibration that eliminates system errors and antenna effects, a realistic power delay profile is developed. Furthermore, a combined MPC clustering and matching procedure with ray-tracing techniques is proposed to investigate the cluster behavior and wave propagation of THz signals. In light of the measurement results, physical parameters and insights in the THz indoor channel are comprehensively analyzed, including the line-of-sight path loss, power distributions, temporal and spatial features, and correlations among THz multi-path characteristics. Finally, a hybrid channel model that combines ray-tracing and statistical methods is developed for THz indoor communications. Numerical results demonstrate that the proposed hybrid channel model shows good agreement with the measurement and outperforms the conventional statistical and geometric-based stochastic channel model in terms of the temporal-spatial characteristics., 30 pages

In application scenarios such as Internet of Things, a large number of energy receivers (ERs) exist and line-of-sight (LOS) propagation could be common. Considering this, we investigate wireless energy transfer (WET) in extra-large massive MIMO Rician channels. We derive analytical expressions of the received net energy for different schemes, including 1) training-based WET, where the ER sends beacon signal for channel training and the energy transmitter (ET) uses the channel estimate for energy beamforming, 2) LOS beamforming, where the ET transmits to the LOS direction of the ER, and 3) energy harvesting, which allows an ER to harvest the training energy from the other ERs. We derive a path loss threshold for switching between training and LOS beamforming-based WET. We further show that the WET scheme selection of one ER is not affected by the other ERs, and the energy harvested from training is minimal in practice. With these insights, we propose an algorithm for the multi-ER scenario, which minimizes the power consumption by iteratively updating the WET scheme selection and power allocation for all ERs. Simulations show that the proposed algorithm achieves near-optimal performance as compared to exhaustive searching, while with much lower implementation complexity.

International audience; Massive machine-type communications (mMTC) is one of the main services delivered by the fifth Generation (5G) mobile network. The traditional cellular architecture where all devices connect to the base station is not energy efficient. For this reason, the use of device-to-device (D2D) communications is considered to reduce the energy consumption of mMTC devices. The main idea is to use nearby user equipment (UE) as a relay and establish with it D2D communication. However, the relay selection process also consumes energy, and this consumption can be significant compared to the energy consumed during the data transmission phase. In this paper, we propose a distributed energy-efficient D2D relaying mechanism for mMTC applications. This mechanism favors the selection of the UEs with low path loss with the mMTC device. Through mathematical analysis and simulations, we show that our mechanism allows a reduction of the total energy consumption of mMTC devices (up to 75% compared to direct transmission) when they have an unfavorable link budget. Moreover, our mechanism achieves almost constant energy consumption for a large range of UE densities and distances between the mMTC device and the base station.

Ultra-dense network (UDN) is one of the most important techniques to support massive number of different types of user equipments (UEs). It is essential to understand the impact of densification on various system performance metrics in future cellular networks. Two contradictory conclusions were made from the existing research works. Some works indicated that the network densification has reached its upper limit and deploying more UEs may only reduce UDN performance; whereas the others claimed that more UEs can still be supported by deploying more small cell base stations (SBSs). The existence of above different conclusions is due mainly to the difficulties to find an effective means to take into account different path loss models in UDNs. In this paper, we aim to propose a unified analytical approach, which is effective to simplify UDN performance analysis based on different path loss models with a low computation complexity. Using the proposed approach with idle mode of SBSs enabled, we can identify the impact of the densities of SBSs and UEs on various performance metrics, i.e., coverage probability and average area spectral efficiency (ASE). The conclusions will be supported by the analytical and simulation results verifying the effectiveness of the proposed unified analytical approach.

Although millimeter wave (mmWave) communications can well support high-data-rate transmissions, the inherent shortcomings, e.g., high path loss and sensitivity to blockage, may cause severe outage problems if the network is not configured properly. This paper aims to minimize the long-term outage probability of an mmWave communication network by optimizing the base station (BS) deployment and user association. For the BS deployment problem, existing works usually assumed that the positions of users are fixed and formulated it as a deterministic optimization problem. With the time-varying nature of positions of user equipments (UEs) taken into account, we establish a stochastic optimization framework for BS deployment optimization. The objective is to maximize the average number of physically accessible BSs of each UE under an inaccessible probability constraint, and a cooperative stochastic approximation (CSA)-based algorithm is developed to effectively search the optimal positions of BSs. For user association, our focus is to properly associate UEs with BSs to minimize the outage probability with balanced workloads among BSs. Combined with the proposed user association scheme, the proposed BS deployment scheme can significantly improve the network outage probability in the long term, especially when the aggregation degree of UEs is large.

The Terahertz (THz) band is envisioned as a promising technique to support bandwidth-hungry and secure applications. Although the significant path loss and strong directivity make THz communications secure naturally, the information security is still imperfect at near regions along the beam propagation path. In this paper, a novel distance-adaptive absorption peak modulation (DA-APM) is developed for THz covert communications, by exploring the unique spectrum features of frequency-dependent molecular absorption. Although high-attenuation molecular absorption is unfavored for communications, the main principle to enhance covertness or equivalently, minimize the eavesdroppable distance, is dynamically modulating signals under the molecular absorption peaks in the THz spectrum, where the eavesdroppable distance is defined as the threshold distance within which an eavesdropper can wiretap the transmission. Furthermore, an optimization framework is proposed to minimize the eavesdroppable distance, to which the sub-optimal solutions are derived for the multi-wideband waveform by controlling carrier frequencies, power allocation, and rate distribution on each sub-band. Extensive numerical results show that the THz-spectrum-based DA-APM approach can reduce the eavesdroppable distance by 60% compared with random spectrum selection methods, which significantly reduce the insecure area and enhance the covertness of THz wireless transmission.

A reliable vehicle-to-vehicle (V2V) channel model is necessary for intelligent transportation systems (ITSs) design. Due to the high mobility of vehicles and the low heights of antennas, the line-of-sight (LOS) propagation paths in V2V communications are more likely to be obstructed by large vehicles such as buses. Therefore, it is worthwhile to conduct in-depth investigations on obstructed line-of sight (OLOS) propagation channels caused by vehicle obstructions. In this paper, actual V2V channel measurements with large vehicle obstructions at 5.9 GHz band are conducted. Based on the measured data, it can be found that the obstructions of large vehicles not only cause additional attenuation, but also significantly affect the angular distribution of multipath components (MPCs). In addition, a cluster-based dynamic V2V channel model is proposed for OLOS scenarios. In the proposed model, the influences of vehicle obstructions on path loss, delay and angle dispersion are intuitively embodied as changes in the statistical distribution of MPCs clusters. Finally, the rationality and accuracy of the proposed model is validated by comparing the measured and simulated channels. The results in the paper are useful for enriching the understanding of V2V channels and provide supports for vehicular communication systems design and performance evaluation.

Ultra-Wideband (UWB) technology has great potential for the cooperation and navigation among near ground mobile robots in GPS-denied environments. In this paper, an efficient two-segment UWB radio channel model is proposed with considering the multi-path condition in very near-ground environments and different surface roughness. We conducted field measurements to collect channel information, with both transmitter and receiver antennas placed at different heights above the ground: 0cm–20cm. Signal frequency was chosen at 4.3GHz with bandwidth of 1GHz. Three ground coverings were tested in common scenarios: brick, grass and robber fields. The proposed model has enhanced accuracy achieved by careful assessment of dominant propagation mechanisms in each segment, such as diffraction loss due to obstruction of the first Fresnel zone and higher-order waves produced by ground roughness. It is realized that antenna height and distance are the most influential geometric parameters to affect the path loss model. Once the antenna height is known, there exists a breakpoint distance in UWB propagation, which separates two segmentation using the different path-loss mechanism. Different surface types can cause different signal attenuation. Monte Carlo simulations are used to investigate the effects of antenna height, distance, ground surface type on mobile robots swarm communication to find out the antenna height is also a dominant factor on connectivity and the average number of neighbors. Within a certain range, the higher the antenna height and the closer the communication distance, the better the communication performance will usually be. Cramer-Rao lower bound(CRLB) of path loss estimator based on the proposed model is derived to show the relationship between CRLB with height and distance.

This paper proposes a two dimensional (2-D) statistical channel model for Terahertz (THz) chip-to-chip wireless communication in desktop size metal enclosures. This model differs from traditional statistical channel models as it models both traveling and resonant waves that exist inside metal enclosures. Based on the cavity environment and the statistical properties of the channel inside the metal cavity, the geometrical model which describes propagation in resonant cavity as a superposition of LoS, single bounced (SB), double bounced (DB), and multi-bounced (MB) rays is proposed. Based on the geometrical model, a parametric reference model is proposed. Furthermore, the path loss model that captures signal strength variation in a resonant cavity is proposed. Frequency correlation functions (FCF) and power delay profiles (PDP) for different possible chip-to-chip communication scenarios are derived and compared with the measured ones. The results show a good agreement between the simulated and measured statistics.

In this paper, we propose a superimposed training based two-phase robust channel estimation scheme for the unmanned aerial vehicle (UAV) assisted cellular communication system, in which various unitarily-invariant channel statistics errors are considered. Specifically, in the first phase, mobile station (MS) estimates the UAV-MS channel via the UAV training sequence, of which the robust design can be solved based on convex-concave theory. While in the second phase, the superimposed training scheme is considered at the ground base station (GBS) to improve spectrum efficiency. Then the robust GBS training sequence, the information signal power and the UAV amplifying factor are jointly optimized for the partially cascaded GBS-UAV-MS channel estimation subject to GBS and UAV transmit power constraints as well as the required information signal strength at the MS. To tackle this NP-hard problem, the optimal structures of involved variables are firstly derived, based on which the robust superimposed training design is simplified and proved to be quasi-convex in the UAV amplifying factor. Particularly, for Spectral norm and Nuclear norm bounded errors, the optimal training sequence can be obtained via convex-concave theory and Golden section searchWhile for Frobenius norm bounded error, a tractable upper-bounding scheme is proposed for the robust superimposed training design. Furthermore, we extend our work into the more general probabilistic path loss scenario of UAV-ground channels, and analyze the impacts of the probabilistic path loss and Rician $K$ -factor on channel estimation performance. Numerical results illustrate the excellent performance of the proposed superimposed training based two-phase channel estimation scheme.

openaire: EC/H2020/671650/EU//mmMAGIC In this paper, we parameterize an excess loss-based multipath component (MPC) cross-polarization ratio (XPR) model in indoor and outdoor environments for above-5-GHz frequency bands. The results are based on 35 measurement campaigns in several frequency bands ranging from 5 to 80 GHz. A conventional XPR model of an MPC assuming a constant mean value fits our measurements very poorly and moreover overestimates the depolarization effect. Our measurements revealed a clear trend that the MPC XPR is inversely proportional to the excess loss in reference to the free-space path loss. The model is physically sound as a higher loss is attributed to more lossy interactions or to a greater number of interactions with objects, leading to a greater chance of depolarization. The measurements furthermore showed that the MPC XPR is not strongly frequency or environment dependent. In our MPC XPR model, an MPC with zero-dB excess loss has a mean XPR of 27 dB. The mean XPR decreases half-a-dB as the excess loss increases by every dB and the standard deviation around the mean is 7 dB. The model is applicable to existing channel models to reproduce realistic MPC XPRs for the above 5-GHz radio links.

Millimeter-wave (mmWave) will be used for fifth-generation (5G) wireless systems. While many recent empirical studies have presented propagation characteristics at mmWave bands, macrodiversity and Coordinated Multipoint (CoMP) have not been carefully studied. This paper describes a large-scale mmWave base station diversity measurement campaign at 73 GHz in an urban microcell (UMi) in downtown, Brooklyn, NY, USA, and provides the first detailed analysis of CoMP and macrodiversity performance based on extensive measurements. The research employed nine different base station locations in a 200 m by 200 m area and considered 36 individual transmitter–receiver combinations for extensive co- and cross-polarized varying directional beam channel impulse response measurements. From the measured data, hypothesis testing with cross-validation shows that large-scale shadow fading of directional path loss at an RX from multiple base stations can be modeled as being independent. To consider life-like human blockage in CoMP and macrodiversity analysis, simulated human blockage traces are superimposed on the directional measurements to quantitatively show that a user that is served by multiple base stations undergoes dramatically less outage in the presence of rapid fading events, compared to a single serving base station. Moreover, the base station diversity measurements are used to determine the effectiveness of downlink precoding techniques for mmWave CoMP. While results show that the coordination can improve network performance by suppressing interference when it exists, nearly half of the 680 000 directional CoMP measurements (~43%) result in no interference for either user, meaning that macrodiversity alone may offer sufficient link and capacity improvement and that CoMP may not be necessary for interference coordination at mmWave when narrow directional beams are used.

Owing to severe path loss and unreliable transmission over a long distance at higher frequency bands, we investigate the problem of path selection and rate allocation for multi-hop self-backhaul millimeter wave (mmWave) networks. Enabling multi-hop mmWave transmissions raises a potential issue of increased latency, and thus, in this work we aim at addressing the fundamental questions: how to select the best multi-hop paths and how to allocate rates over these paths subject to latency constraints? In this regard, we propose a new system design, which exploits multiple antenna diversity, mmWave bandwidth, and traffic splitting techniques to improve the downlink transmission. The studied problem is cast as a network utility maximization, subject to an upper delay bound constraint, network stability, and network dynamics. By leveraging stochastic optimization, the problem is decoupled into: path selection and rate allocation sub-problems, whereby a framework which selects the best paths is proposed using reinforcement learning techniques. Moreover, the rate allocation is a nonconvex program, which is converted into a convex one by using the successive convex approximation method. Via mathematical analysis, we provide a comprehensive performance analysis and convergence proofs for the proposed solution. Numerical results show that our approach ensures reliable communication with a guaranteed probability of up to $99.9999\%$, and reduces latency by $50.64\%$ and $92.9\%$ as compared to baseline models. Furthermore, the results showcase the key trade-off between latency and network arrival rate., Comment: Keywords: URLLC, mmWave communications, latency, reliability, 5G, stochastic optimization, non-convex optimization, reinforcement learning. arXiv admin note: text overlap with arXiv:1802.02085

Outdoor to indoor penetration loss is one of the crucial challenges faced at millimeter-wave frequencies. This paper presents the results from 28-GHz channel sounding campaigns performed to investigate the impact of this phenomenon on the wireless propagation channel characteristics in small cell and fixed wireless access scenarios. The measurements are performed with a real-time channel sounder equipped with phased array antennas that allow beam-forming and electronic beam steering for directionally resolved measurements. Thanks to the short measurement time and the excellent phase stability of the system, we obtain both directional and omnidirectional channel power delay profiles without any delay uncertainty. We compare the measured path loss, delay spread, and angular spread for indoor and outdoor receiver locations for two different types of buildings. We find that the penetration loss strongly depends on the angle of incidence, and the scatterers on the outside of the building strongly impact how much power is coupled into the building. Based on the results, we provide statistical models for path loss, delay spread, and angular spread.

The terahertz (THz) communication utilizes the frequency spectrum above 300 GHz and is widely considered as a promising solution to the future high-speed short-range wireless communication beyond millimeter wave communication. While providing tens of gigahertz bandwidth, it is subjected to high-propagation path loss, inter-symbol, and inter-user interferences. The massive multiple-input-multiple-output (MIMO) can be applied to address these problems by cooperation between many access point antennas. However, the THz channel characteristics, including high-propagation path loss, frequency selectivity, and a big number of samples per channel impulse response, require carefully tailored algorithm for massive MIMO signal processing. In this paper, we propose a single carrier minimum mean square error precoding and detection algorithm for frequency selective THz channels. The MIMO signal transmission is described with the block matrices. A gain control heuristic is introduced to reduce the complexity. The sparsity property of the channel is utilized to construct sparse channel matrices and the least square QR algorithm is applied to efficiently solve the problems. Besides the uniform antenna array, the hybrid array consisting of several subarrays is considered as well. The simulation results show that the massive MIMO array can provide a satisfactory performance in terms of bit error rate.

In this paper, an analytical framework is provided to analyze the uplink performance of device-to-device (D2D)-enabled millimeter-wave (mm-wave) cellular networks with clustered D2D user equipments (UEs). The locations of cellular UEs are modeled as a Poisson point process, while the locations of potential D2D UEs are modeled as a Poisson cluster process. Signal-to-interference-plus-noise ratio outage probabilities are derived for both cellular and D2D links using tools from stochastic geometry. The distinguishing features of mm-wave communications such as directional beamforming and having different path loss laws for the line-of-sight and non-line-of-sight links are incorporated into the outage analysis by employing a flexible mode selection scheme and Nakagami fading. Also, the effect of beamforming alignment errors on the outage probability is investigated to get insight into the performance in practical scenarios. Moreover, area spectral efficiency of the cellular and D2D networks is determined for both underlay and overlay types of sharing. Optimal spectrum partition factor is determined for overlay sharing by considering the optimal weighted proportional fair spectrum partition.

In this paper, we characterize the wireless interference of a mobile ad hoc network, where the nodes move according to the random waypoint model. The interferers are assumed to be located within an interference region that is defined as a circular region centered in a fixed node located at a given point of the mobility scenario. The main contribution of this paper is the characterization of the aggregate interference caused to the fixed node by mobile interferers located within the interference region. The distribution of the interference is analyzed taking into account the stochastic nature of the path loss due to the mobility of the nodes, as well as fast fading and shadowing effects. The derivation of the characteristic function of the aggregate interference is used in two different estimators, which successfully characterize the interference using only a small set of samples. The theoretical approach is validated through simulations, which confirm its effectiveness. Finally, we assess the accuracy of the proposed estimators, demonstrating the practical value of this paper.

Angle of arrival (AoA) estimation is required by adaptive directive antennas in order to realize a high antenna gain, which is necessary for future indoor terahertz communications due to its extremely high path loss. This paper proposes an AoA estimation algorithm using belief propagation in a dynamic scenario, where the user equipment (UE) is moving during the data transmission, based on the space-time correlations of AoA change. The temporal correlation of AoA change is due to the limited moving speed and statistical movement pattern. Furthermore, if we have distributed antennas or hybrid massive multiple-input-multiple-output (MIMO) array, the AoA changes of different antennas reveal spatial correlation because all the AoA changes are caused by the same spatial displacement of UE. This spatial correlation is utilized in this paper to further improve the estimation accuracy by passing messages between antennas and combining the intrinsic estimate by each antenna and extrinsic information from other antennas. In order to demonstrate the algorithm performance, a distributed antenna system and a hybrid massive MIMO array (an array of multiple directive antenna arrays) are considered as application scenarios. The simulation results show that the cooperative estimation brings significant advantage in both scenarios in respect of mean effective antenna gain and level crossing rate.

We analyze the performance of a multiple-input multiple-output multiplexing system in a Poisson bipolar network under line-of-sight/non-line-of-sight (LOS/NLOS) path-loss model and zero-forcing beamforming at receivers. The capacity and outage performance of such a configuration, commonly under the standard path-loss model, have been broadly analyzed; yet little is known about its local transmission delay with considering the traits of LOS/NLOS model. As the effective fading power gain on each data stream is Nakagami-type, and due to the interference correlation across data streams of a link as well as the retransmission attempts, the evaluation of the mean delay is more involved than the capacity/coverage evaluation. Our rigorous analysis provides a lower bound and an approximate upper bound on the mean delay as the functions of density, multiplexing gain, transmission activity, and LOS/NLOS model, which sheds some light on the effect of the LOS component in circumventing the possible divergence of the mean delay. Simulations show the lower bound is very accurate and demonstrate several aspects of multiplexing, path-loss traits, and interference correlation on the mean delay. Exploiting the analysis, we further explore the optimization of effective spatial throughput of the network.

Massive Internet of Things (mIoT) is an important use case of 5G. The main challenge for mIoT is the huge amount of uplink traffic as it dramatically overloads the radio access network (RAN). To mitigate this shortcoming, a new RAN technology has been suggested, where small cells are used for interconnecting different devices to the network. The use of small cells will alleviate congestion at the RAN, reduce the end-to-end (E2E) delay, and increase the link capacity for communications. In this paper, we devise three solutions for deploying and interconnecting small cells that would handle mIoT traffic. A realistic physical model is considered in these solutions. The physical model is based on a composite fading channel that captures path loss, fast fading, shadowing, and interference to derive the signal-to-interference-plus-noise ratio. The three solutions consider two conflicting objectives, namely the cost and the E2E delay for deploying and backhauling small cells. The first solution minimizes the cost while the second reduces the E2E delay. The third solution uses bargaining game theory for reducing both the cost and the E2E delay. The proposed solutions are evaluated through simulations. The obtained results demonstrate the efficiency of each solution in achieving its design goals.

This paper evaluates the energy efficiency of uplink transmission in heterogeneous cellular networks (HetNets), where fractional power control (FPC) is applied at user equipments (UEs) subject to a maximum transmit power constraint. We first consider an arbitrary deterministic HetNet and characterize the properties of energy efficiency for UEs in different path loss regimes, or different access regions. By introducing the notion of transfer path loss, we reveal that, for UE whose path loss is below the transfer path loss, its energy efficiency highly depends on the value of power control coefficient adopted by FPC. In contrast, for UE with path loss above the transfer path loss, the uplink energy efficiency asymptotically decreases inversely with path loss, independent of the adopted power control coefficient. Based on these properties, we characterize the optimal power control coefficients for maximizing the energy efficiency of FPC in different access regions. Next, we extend the analysis to stochastic HetNets where UEs and BSs are distributed as independent Poisson point processes, and investigate the distribution of transmit power for uplink UEs. Moreover, the probability of truncation outage due to constrained maximal transmit power, as well as the average energy efficiency of UEs are analytically derived as functions of the BS and UE densities, power control coefficient, and receiver threshold. Simulation results validate the analytical results, show the consistency between deterministic and stochastic analyses, and suggest suitable power control coefficient for achieving energy efficient uplink transmission by FPC in HetNets.

This paper explores the problem of localizing an emitter of radio frequency energy using a network of mobile receiver nodes, each taking measurements of the emitter’s received signal strength (RSS). In this paper, we drop the assumption of receiver calibration, leading to biased measurements for each node. We model these bias effects as additive random variables for each receiver in the log-distance path loss model. We propose two novel estimators to handle these effects as modifications of the nonlinear least squares and the Gaussian particle filter algorithms. The estimators are augmented using the principle of variance least squares, in which the biases’ effect on the data covariance is estimated online. These estimates inform subsequent iterations of the nonlinear algorithms. The path loss exponent and emitter power offset are likewise treated as unknowns. Our simulations show the performance improvement evident in various scenarios over the naive approaches, other contemporary algorithms, and with respect to the Cramer-Rao lower bound. We further show the efficacy of our approach through several experiments using real RSS data collected from a mobile network.

This paper considers a fundamental issue of path loss (PL) modeling in urban micro cell (UMi) environments, namely the spatial consistency of the model as the mobile station moves along a trajectory through street canyons. This paper is motivated by the observed non-stationarity of the PL. We show that the traditional model of power law PL plus log-normally distributed variations can provide misleading results that can have serious implications for system simulations. Rather, the PL parameters have to be modeled as random variables that change from street to street and also as a function of the street orientation. Variations of the PL, taken over the ensemble of the whole cell (or multiple cells), thus consist of the compound effect of these PL parameter variations together with the traditional shadowing variations along the trajectory of movement. Ray-tracing results demonstrate that ignoring this effect can lead to a severe overestimation of the local standard deviation in a given area. Then, a spatially consistent stochastic street-by-street PL model is established, and a parameterization for 28-GHz UMi cells is given. The model correctly describes the PL as a function of the street orientation as well as the large variance observed for all the PL model parameters.

Millimeter wave (mmWave) communication is expected to be widely deployed in fifth generation (5G) wireless networks due to the substantial bandwidth available at mmWave frequencies. To overcome the higher path loss observed at mmWave bands, most prior work focused on the design of directional beamforming using analog and/or hybrid beamforming techniques in largescale multiple-input multiple-output (MIMO) systems. Obtaining potential gains from highly directional beamforming in practical systems hinges on sufficient levels of channel estimation accuracy, where the problem of channel estimation becomes more challenging due to the substantial training overhead needed to sound all directions using a high-resolution narrow beam. In this work, we consider the design of multi-resolution beamforming sequences to enable the system to quickly search out the dominant channel direction for single-path channels. The resulting design generates a multilevel beamforming sequence that strikes a balance between minimizing the training overhead and maximizing beamforming gain, where a subset of multilevel beamforming vectors is chosen adaptively to provide an improved average data rate within a constrained time. We propose an efficient method to design a hierarchical multiresolution codebook utilizing a Butler matrix, a generalized discrete Fourier transform (DFT) matrix implemented using analog RF circuitry. Numerical results show the effectiveness of the proposed algorithm.

In this paper, we propose a carrier sensing-based medium access control (MAC) protocol for wireless local area networks (WLANs) for exploiting successive interference cancellation (SIC). We then develop an analytical model to compute the total throughput of a WLAN under the proposed MAC protocol in the presence of path loss, Rayleigh fading, and log-normal shadowing and validate the model via simulation. By means of the analytical model and simulation results, we compare the performance of a carrier sense multiple access (CSMA) MAC protocol and the proposed MAC protocol in utilizing the opportunities from SIC. We find that the proposed MAC protocol effectively utilizes the opportunities of SIC and significantly improves throughput compared with the CSMA MAC protocol. We also investigate the effect of some of the parameters of network and wireless channel on the performance of SIC.

In this paper, we propose a novel transmission approach, namely, analog precoding-aided virtual space modulation (APAVSM), and its corresponding multimode hybrid precoder designs in the multiple-input multiple-output system. We consider the system equipped with a single radio frequency chain and a phase shift network. Our proposed designs can attain benefits of both beamforming and spatial modulation, and therefore enable the significant signal-to-noise power ratio enhancement with efficient degrees of freedom utilization and low cost. We elaborate APAVSM and formulate the multimode hybrid precoder design problem. To solve the problem, we impose restrictions on the number of candidate modes for selection, and propose the hybrid precoder design approach in which two non-convex max-min problems are solved sequentially by iterative approaches. To trade off between error rate and complexity, we propose alternative designs by reducing the dimensionality and/or relaxing constraints. Moreover, by the concept of beamspace, heuristic algorithms are proposed with extremely low complexities. We offer complexity analyses for proposed design approaches. Simulations in Ralyigh fading and millimeter-wave (mmWave) channels are used to evaluate the proposed designs. Results show that our designs can outperform the existing SM-MIMO systems, and provide the feasible operation in mmWave channels with severe path loss. Moreover, the superiority of proposed designs to the conventional precoding-aided MIMO systems is numerically demonstrated.

This paper tackles the challenge of optimally placing relay nodes (RNs) in wireless sensor networks given a limited set of positions. The proposed solution consists of: 1) the usage of a realistic physical layer model based on a Rayleigh block-fading channel; 2) the calculation of the signal-to-interference-plus-noise ratio (SINR) considering the path loss, fast fading, and interference; and 3) the usage of a weighted communication graph drawn based on outage probabilities determined from the calculated SINR for every communication link. Overall, the proposed solution aims for minimizing the outage probabilities when constructing the routing tree, by adding a minimum number of RNs that guarantee connectivity. In comparison to the state-of-the art solutions, the conducted simulations reveal that the proposed solution exhibits highly encouraging results at a reasonable cost in terms of the number of added RNs. The gain is proved high in terms of extending the network lifetime, reducing the end-to-end- delay, and increasing the goodput.

Ultraviolet (UV) communication enables non-line-of-sight (NLOS) outdoor wireless connectivity and is particularly desirable to relax or eliminate pointing and tracking requirements of infrared links. In comparison to infrared counterparts, UV links are subject to relatively higher path loss as well as intersymbol interference resulting from frequency selective nature of the channel. In this paper, we propose the powerful combination of relay-assisted transmission and multi-carrier architecture based on orthogonal frequency division multiplexing (OFDM). Specifically, we consider a cooperative diversity system with orthogonal cooperation protocol and use DC-biased optical OFDM as the underlying physical layer. We consider both amplify-and-forward (AF) and detect-and-forward (DF) relaying. We investigate the error rate performance of the proposed relay-assisted OFDM UV system under consideration and demonstrate performance gains over point-to-point OFDM UV systems. We further determine optimal power allocation schemes to improve the performance. We also propose a variable-rate UV OFDM system and improve system throughput via bit loading.

This paper considers the problem of tomographic area mapping using radio frequency measurements gathered by a network of mobile nodes. Termed radio tomographic imaging, the technique has shown potential for object tracking, imaging static obstacles, and even through-wall imaging. Our approach addresses substantial issues for the practical implementation of such a system, namely, the mitigation of multipath signal effects and the characterization of a large number of uncalibrated network links. We propose a system that utilizes ultrawideband direct path signal strength measurements as a means of reducing the effects of the multipath fading. Furthermore, we address the estimation of unknown path loss and link bias parameters online through the framework of a linear mixed effects model. This permits the estimation of a static area map without a prohibitive calibration of these parameters prior to deployment, which is crucial in a network that may contain hundreds of links. Our model is posed as a convex optimization problem using the elastic net for regularization. Bayesian performance bounds are derived and our method shows positive results in simulation. We then demonstrate the efficacy of our solution on real tomographic data gathered from our cognitive spectrum operations testbed.

This paper introduces a model to study both single tier and multitier wireless communication systems consisting of a multitude of wireless access points (AP), and operating according to the classical opportunistic beamforming framework. The AP locations in the proposed network model are determined by using planar Poisson point processes. The extreme value distribution of signal-to-interference-plus-noise-ratio ( ${\rm{ SINR}}$ ) on a beam is of fundamental importance for obtaining performance bounds for such an opportunistic communication system. Two tight distribution approximation results are provided for the distribution of maximum ${\rm{ SINR}}$ on a beam, which is hard to obtain due to correlation structure of the underlying inter-AP interference field, using key tools from stochastic geometry. These approximations hold for general path loss models that satisfy some mild conditions. Simulations and numerical evaluations are presented to validate the results, to provide further insights into the derived approximate maximum beam ${\rm{ SINR}}$ distributions, and to illustrate the utility of these approximations in obtaining performance bounds for opportunistic communication systems having multiple interfering APs. In particular, key performance measures such as beam outage probability and ergodic aggregate data rate of an AP are derived by utilizing the approximated distributions.