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This paper investigates distributed MIMO precoding design to maximize the weighted sum rate in a heterogeneous network where the multiple input multiple output full-duplex (MIMO-FD) small cells reuse the downlink spectrum of the macro base-station (BS) to exchange backhaul information. The multi-antenna BS transmits signals to the cellular users using the dirty paper coding technique and the MIMO-FD small cells apply FD precoding structures to effectively balance the received signal, the self-interference (SI), and the co-channel interference (CCI). Since the optimization problem is shown to be nonconvex, obtaining the global optimum is challenging. A low-complexity solution with distributed implementation is introduced with proved convergence. By applying the successive convex approximation technique and the duality between the broadcast channel and the multiple access channel, the original nonconvex problem is decomposed into a sequence of convex subproblems, which can be solved analytically and separately at each small cell and macro BS with limited channel state information exchange. Simulation results confirm the convergence and demonstrate the benefits of the introduced algorithm. It is shown that the SI and CCI can be suppressed effectively with sufficient cancellation power and number of transmit antennas at the FD small cells.

Most applications of underwater acoustic sensor networks (UASNs) rely upon reliable location information of sensor nodes. However, the harsh underwater environment makes localization more challenging as compared to terrestrial sensor networks. This paper is concerned with a localization issue for UASNs, subject to clock asynchronization and node mobility. A hybrid architecture including autonomous underwater vehicles (AUVs), active and passive sensor nodes is designed, where AUVs act as anchor nodes to provide localization information for sensor nodes. In order to eliminate the effect of asynchronous clocks and compensate the mobility of sensor nodes, an asynchronous localization algorithm with mobility prediction is provided for active and passive sensor nodes. Then, two localization optimization problems are formulated as minimizing the sum of all measurement errors. To solve the localization optimization problems, iterative least squares estimators are designed. In addition, the convergence analysis and Crame r–Rao lower bound for the localization errors are also provided. Finally, simulation results show that the proposed localization approach can reduce the localization time by comparing with the exhaustive search-based localization method. Meanwhile, the asynchronous algorithm in this paper can effectively eliminate the impact of the clock asynchronization and node mobility.

Increasing safety and automation in transportation systems has led to the proliferation of radar and IEEE 802.11pbased dedicated short-range communication (DSRC) in vehicles. However, current implementations of vehicular radar devices are expensive, use a substantial amount of bandwidth, and are susceptible to multiple security risks. In this paper, we use the IEEE 802.11 orthogonal frequency-division multiplexing communications waveform, as found in IEEE 802.11a/g/p, to perform radar functions. In this paper, we present an approach that determines the mean-normalized channel energy from frequencydomain channel estimates and models it as a direct sinusoidal function of target range, enabling closest target range estimation. In addition, we propose an alternative to vehicular forward collision detection by extending IEEE 802.11 DSRC and WiFi technology to radar, extending the foundation ofjoint communications and radar frameworks. Furthermore, we perform an experimental demonstration near DSRC spectrum using IEEE 802.11 standard compliant software defined radios with potentially minimal modification through algorithm processing on frequency-domain channel estimates. The results of this paper show that our solution delivers sufficient accuracy and reliability for vehicular RADAR if we use the largest bandwidth available to IEEE 802.11p (20 MHz). This indicates significant potential for industrial devices with joint vehicular communications and radar capabilities.

This paper focuses on the secure transmission of wireless-powered full-duplex (FD) relay systems, where a multiantenna source communicates with a single-antenna destination with the help of a FD relay in the presence of a single-antenna eavesdropper. It is assumed that the FD relay is wireless energy harvesting-enabled, adopting both transmit and receive antennas to harvest energy in a time switching (TS) mode. As the objective of this paper is to maximize the system secrecy rate through jointly designing the energy beamforming vector, the information beamforming vector and the TS coefficient, an optimization problem is formulated. The formulated problem is proved to be nonconvex and the challenge to solve which is to concurrently solve out the three variables. To cope with this difficulty, an iterative algorithm is proposed to convert the formulated optimization problem into three convex subproblems, based on which the closed form solutions for the beamforming vectors are derived and the TS coefficient is obtained. Convergence property of the iterative method is analyzed. Simulations are also done to verify the theoretical derivations in terms of the convergence speed and the secrecy rate. Results reveal that the secrecy rate performance of exploiting transmit antenna together with receive antenna for energy harvesting at the FD relay outperforms only receive antenna case. Moreover, although there exists loopback interference between antennas, the FD relaying can always substantially boost the secrecy rate compared with half-duplex relaying architecture.

With the emergence of in-vehicle applications, providing the required computational capabilities is becoming a crucial problem. This paper proposes a framework named autonomous vehicular edge (AVE) for edge computing on the road, with the aim of increasing the computational capabilities of vehicles in a decentralized manner. By managing the idle computational resources on vehicles and using them efficiently, the proposed AVE framework can provide computation services in dynamic vehicular environments without requiring particular infrastructures to be deployed. Specifically, this paper introduces a workflow to support the autonomous organization of vehicular edges. Efficient job caching is proposed to better schedule jobs based on the information collected on neighboring vehicles, including GPS information. A scheduling algorithm based on ant colony optimization is designed to solve this job assignment problem. Extensive simulations are conducted, and the simulation results demonstrate the superiority of this approach over competing schemes in typical urban and highway scenarios.

As the conventional spatial modulation (SM) system lacks an efficient downlink multiple access scheme, this paper proposes a novel downlink nonorthogonal multiple access aided multiple-input multiple-output SM system with finite alphabet inputs. Mutual information (MI) is used to characterize the system's achievable spectral efficiency (SE). Because the MI lacks a closed-form formulation, in this paper we propose a computational-efficient lower bound to provide an approximation to the simulated MI. Besides, preprocessing is also designed at the receiver to mitigate the detrimental effect of channel correlation, which leads to striking a higher SE performance. Simulation results not only confirm the accuracy of our SE analysis, but also substantiate the superior SE performance achieved by the proposed preprocessing.

Both caching and interference alignment (IA) are promising techniques for next-generation wireless networks. Nevertheless, most of the existing works on cache-enabled IA wireless networks assume that the channel is invariant, which is unrealistic considering the time-varying nature of practical wireless environments. In this paper, we consider realistic time-varying channels. Specifically, the channel is formulated as a finite-state Markov channel (FSMC). The complexity of the system is very high when we consider realistic FSMC models. Therefore, in this paper, we propose a novel deep reinforcement learning approach, which is an advanced reinforcement learning algorithm that uses a deep $Q$ network to approximate the $Q$ value-action function. We use Google TensorFlow to implement deep reinforcement learning in this paper to obtain the optimal IA user selection policy in cache-enabled opportunistic IA wireless networks. Simulation results are presented to show that the performance of cache-enabled opportunistic IA networks in terms of the network's sum rate and energy efficiency can be significantly improved by using the proposed approach.

This paper investigates the energy consumption of distributed large-scale MIMO systems made up of a set of remote radio heads (RRHs), each of which is powered by both an independent energy harvesting source and the grid. The grid energy source allows to compensate for the randomness and intermittency of the harvested energy. Hence, the problem of grid power consumption minimization has to be solved by efficiently managing the energy delivered from different sources while satisfying the system requirements in terms of users’ quality of service demands. First, this paper solves the optimal offline version of the problem using linear programming. In fact, the main problem is decomposed and heuristically solved in order to deal with the large number of constraints and variables. Since sometimes all the users cannot be served, an iterative link removal algorithm is devised ensuring the feasibility of the problem. Next, we investigate the online energy management problem. We first propose a dynamic programming approach to obtain the optimal online solution but with high complexity. Then, we develop and propose a low complexity heuristic solution based on using the maximal available energy at the batteries. Taking benefits of the characteristics of large-scale MIMO and the modeling of the harvested energy as Markov chains, we devise an efficient online energy management algorithm based on energy prediction. Finally, we propose a heuristic solution for RRH on/off operation with the objective of improving the system energy efficiency. The performance of the proposed algorithms is evaluated by simulations and it is shown that the proposed energy management approaches offer efficient use of nonrenewable energy to compensate the variability of renewable energy in large-scale MIMO systems.

Existing research on a simultaneous wireless information and power transfer (SWIPT) system is based on the assumption of Gaussian inputs. However, the optimal design on Gaussian inputs may lead to dramatic performance loss for practical systems with finite-alphabet inputs. This paper focuses on the precoder design for a SWIPT system with finite-alphabet inputs and instantaneous channel state information over a multiple-input multiple-output channel. We formulate the optimal precoder design as an optimization problem, in which the objective is to maximize the mutual information over the channel from the transmitter to the information receiver under the constraints of transmit power and harvested energy threshold. The formulated problem is NP-hard, so a global optimal solution cannot be found within the polynomial time. The main contributions of this paper are as follows: 1) By using its structure, the NP-hard problem is relaxed to a semidefinite programming problem. Then, a general solving framework for both co-located and separated receiver cases, based on the semidefinite relaxation (SDR) technique, is developed to achieve a near optimal precoder. 2) For the case of co-located receivers, we show that the optimal precoder design is a concave problem with respect to power allocation; then, a specific algorithm for co-located receivers is proposed. Compared with the general SDR-based method, the specific algorithm for co-located receivers exhibits almost the same performance but much lower complexity. 3) The performance of several practical co-located receiver designs is analyzed in SWIPT systems with finite-alphabet inputs. Finally, we provide simulation results to show the efficacy of the proposed algorithms.

This paper deals with the secure communication issues of wireless cooperative networks in the presence of multiple friendly but selfish intermediate nodes. On account of the broadcast nature of wireless communications, it is assailable to malicious eavesdropping. To tackle this challenge in the paper, we present a relay and jammer selection strategy that selects the jammer and relay nodes from intermediate nodes to improve the security of the eavesdropping attacks. The jammer is used to broadcast artificial interference noise on the eavesdropper. The relay acts as a traditional relay that retransmits source signal from the source to the intended destination. For achieving the maximum secrecy capacity by the selected nodes, we introduce a power allocation approach of intermediate nodes that is formulated as a Bertrand game based on price competition. We prove that an optimal pricing scheme can maximize the secrecy capacity and achieve the optimal profits for the selfish friendly nodes. Then, a new particle swarm with simulated anneal optimization algorithm is employed to obtain the solution of pricing and node selection. Finally, the simulation results verify our theoretical analysis.

Applications of unmanned aircraft systems (UAS) are expected to expand dramatically in the coming decades. In order to provide safe and reliable links for UAS, NASA Glenn Research Center sponsored a measurement campaign in 2013 to characterize air-ground (AG) channels. In the first three of our AG channel characterization series papers, path loss, small scale fading, stationarity distance, root mean square (RMS) delay spread, spatial correlations, and tapped delay line models were presented for a range of ground site environment. In this paper, we expand the results to a unique and little-studied characteristic of the AG channels—airframe shadowing—for a medium-sized aircraft. Airframe shadowing occurs when the line-of-sight signal is obstructed by the airplane itself in some specific maneuvers. Based on over 200 aircraft wing/engine shadowing events in both C-band (5060 MHz) and L-band (968 MHz) collected in the measurement campaign, shadowing depth, duration, multiple antenna diversity gain, and small scale fading results and their statistics are reported. Algorithms are proposed to simulate a random shadowing event based upon shadowing depth and duration cumulative density functions. Airframe shadowing characteristics are independent of the local ground site conditions and link distance. The shadowing loss is modeled as a function of aircraft roll angle, but shadowing loss and duration are essentially uncorrelated. The maximum shadowing loss measured was over 35 dB and the duration was up to 74 s. As expected, deployment of multiple aircraft antennas is shown helpful to mitigate this shadowing.

Diversity is used to combat fading and shadowing in narrowband spectrum sensing. In this paper, we propose two new detection algorithms for wideband spectrum sensing that use square law combining (SLC) diversity to improve the detection performance. We analyze the performance of these algorithms under Nakagami fading. The proposed schemes include channel by channel square law combining (CC-SLC) and ranked square law combining (R-SLC). We first provide the asymptotic analysis for decision statistic of received energy to simplify the analysis. The approximated probability density function (pdf) to decision statistic is used to derive the pdf of received energy for $P$ number of diversity branches. The performance of the proposed algorithms is measured in terms of probability of insufficient spectrum opportunity ( $P_{\text{ISO}}$ ) and probability of excessive interference opportunity ( $P_{\text{EIO}}$ ). The analysis provided in this paper is general and can be used with any fading model and diversity scheme. Experiments are carried out using theoretical analysis and also verified by using Monte-Carlo simulation. Our analysis shows that the proposed algorithms using diversity outperform the channel by channel and ranked channel detection algorithms used under no diversity. Our results also indicate that among the proposed detection algorithms R-SLC performs better.

The proposed solutions in the literature for integrating Device-to-Device (D2D) communication in cellular networks require added functionalities and consume valuable network resources, mainly in the discovery process. Unlike existing solutions, this paper mitigates the requirement of additional resources in the LTE-A network. This is achieved by proposing to offload a portion of the discovery traffic and processing of D2D communications that involve vehicular users (drivers and passengers) into Vehicular Ad-hoc Networks (VANETs) by using the inherent knowledge of the Road Side Units (RSUs) about users in their coverage areas. In addition, the paper develops an analytical model to analyze the duration of peer discovery in highway scenarios. The results are validated through simulation experiments using both the Network Simulator NS3 and Matlab. The analytical and numerical results demonstrate the effectiveness of the proposed scheme, and show that a low discovery latency is obtained.

Radio tomographic imaging systems use received signal strength measurements between static wireless sensors to image the changes in the radio propagation environment in the area of the sensors, which can be used to localize a person causing the change. To date, spatial models used for such systems are set a priori and do not change. Imaging and tracking performance suffers because of the mismatch between the model and the measurements. Collecting labeled training data requires intensive effort, and the data degrade quickly as the environment changes. This paper provides a means for a radio tomographic imaging system to bootstrap to improve its spatial models using unlabeled data, iteratively improving itself over time. A collection of tracking filters are presented to improve the accuracy of image and coordinate estimates. This paper presents an online method to use these estimates to instantaneously update spatial model parameters. Further, a smoothing method is presented to fine-tune the model with a given finite latency. The development efforts are evaluated using simulations and validated with real-world experiments conducted in three different environments. With respect to another state-of-the-art radio tomographic imaging system, the results suggest that the presented system increases the median tracking accuracy by twofold in the most challenging environment and by threefold when the model parameters are trained using the smoothing method.

This paper reconsiders the design of blind interference alignment (BIA) for $K$ -user MISO interference channel in which each receiver is equipped with a reconfigurable antenna of preset $M_k\geq 3$ modes. Beyond the degree of freedom (DoF)-oriented BIA (D-BIA) design proposed by Lu et al. , we further take into account the frequency of mode switching within one supersymbol frame. Even though every receiving antenna is reconfigurable with preset multiple modes, from an engineering perspective, it is of practical importance for each receiving antenna to make less number of mode switching in order to gain the benefits such as less switching power consumption and less signal distortion. To this end, we propose in this paper switching-oriented BIA (S-BIA) scheme, which preserves the same degree of freedom (DoF) gain as D-BIA while offering reduced mode switching frequency. Theoretical analysis and simulation results demonstrate that, compared to D-BIA, S-BIA can gain $100/(M-1)$ percent of switching saving when $M_k = M$ is odd for all transmitters. Remarkably, S-BIA offers 50% switching saving for multiuser $3\times 1$ interference channels.

With the ever-growing number of mobile users and the rapid growth of wireless data service requirement, quality of experience (QoE) has emerged as an essential indicator for users, service providers, and operators. Meanwhile, to improve coverage and serve users, a lot of small cell base stations (SBSs) must be installed, and a great amount of energy is consumed. However, as far as is known, there are few works that have studied the combinatorial problem of QoE and energy aware SBS management, which jointly implements power selection, load management (SU allocation), and channel allocation. This paper investigates the problem of QoE and energy aware SBS management, which consists of power selection, load management, and channel allocation. In this paper, we resort to cloud technologies to solve such a complicated combinatorial problem and employ an iterative approach in which two subproblems are alternatively assigned and optimized at each iteration, i.e., 1) transmission power and load joint management and 2) channel allocation. We propose a two-dimensional-action extended weakly acyclic game theoretical scheme to optimize the two subproblems distributedly and iteratively. We define a novel two-dimensional-action pure strategy Nash equilibrium (2D-NE) and prove that at least one 2D-NE exists in the proposed game. With the help of cloud, we propose two kinds of better response algorithms to achieve 2D-NE of the proposed game $G_w$ . Moreover, simulation results show that the proposed approach could achieve a good QoE-energy utility performance and a high QoE energy efficiency.

In cognitive radio (CR) networks, cooperative spectrum sensing is utilized to improve the sensing performance to avoid potential interference to primary users (PUs) and increase spectrum access opportunities for secondary users (SUs). A cooperative spectrum sensing process is divided into three phases: individual sensing/detection, reporting/fusion, and data transmission. In the reporting phase, one or more reporting channels are needed to transmit individual sensing results to a fusion center (FC), and global spectrum sensing results are determined at the FC. The number of required reporting channels depends on the number of spectrum sensors or SUs, which relates to reporting channel efficiency and channel scheduling complexity. That is to say, the reporting channel design can be a challenge, especially when fixed assignment scheduling is used. Therefore, in this paper, we design a reporting channel scheme based on random access protocols, including slotted Aloha and reservation-Aloha. Performance evaluations in terms of PU detection probabilities and false alarm probabilities considering the proposed reporting channels are presented. In addition, the impact of soft/unquantized spectrum sensors or detectors (SUs) and malicious SUs is considered in this paper. Analytical and simulation results illustrate the effectiveness of the proposed reporting channel scheduling methods in improving the cooperative spectrum sensing performance.

With the never-ending increase in the number of mobile connected devices and the need for higher data rates anywhere, anytime, higher frequency bands are being considered for communications. As millimeter-wave technology moves from research to commercial deployments, and motivated by the still limited bandwidth, the terahertz (THz) band is envisioned as the next frontier for communications. When it comes to vehicular networks, communication at much higher frequencies and, consequently, with much higher data rates brings many exciting opportunities as well as challenges. In this paper, an overview of the opportunities and challenges in THz communications for vehicular networks is provided. In addition, the papers in this Special Section which provide first-time solutions to some of these challenges, are introduced.

In this paper, we consider a heterogenous network in which low-power indoor femtocells are deployed in the coverage area of the existing macrobase station (MBS). This paper proposes a novel coordinated random beamforming and user-scheduling strategy to improve the throughput of users served by the femtocell access point (FAP) while satisfying the quality-of-service (QoS) requirements of users served by both MBS and FAP. The strategy, termed as QoS-aware coordinated scheduling (QACS), requires limited coordination between the MBS and FAP, i.e., only the indexes of the qualified beams are shared. Exact statistical analysis for the ergodic achievable rate of both FAP and MBS with the proposed strategy are presented. Scheduling fairness is also addressed for the proposed QACS.

The ever-increasing demand for mobile Internet and high-data-rate applications poses unique challenging requirements for 5G mobile networks, including spectrum limitations and massive connectivity. Cognitive radio and carrier aggregation (CA) have recently been proposed as promising technologies to overcome these challenges. In this paper, we investigate joint relay selection and optimal power allocation in an underlay cooperative cognitive radio with CA, taking into account the availability of multiple carrier components in two frequency bands, subject to outage probability requirements for primary users (PUs). The secondary user network employs relay selection, where the relay that maximizes the end-to-end sum rate is selected, assuming both decode-and-forward and amplify-and-forward relaying. The resulting optimization problems are optimally solved using convex optimization tools, i.e., dual decomposition and an efficient iterative method, allowing their application in practical implementations. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom efficiently to maximize the SU rate, while meeting the PU average outage probability constraints. 1 1967-2012 IEEE. Manuscript received May 27, 2016; revised October 2, 2016; accepted November 7, 2016. Date of publication December 2, 2016; date of current version July 14, 2017. The work of P. D. Diamantoulakis, G. K. Karagiannidis, and T. Khattab was supported by the NPRP under Grant NPRP 6-1326-2-532 from the Qatar National Research Fund (a member of Qatar Foundation). This work was presented in part at the IEEE Wireless Communications and Networking Conference (WCNC), Doha, Qatar, Apr. 2016. The review of this paper was coordinated by Prof. D. B. da Costa. Scopus

With the proliferation of sensors, such as accelerometers, in mobile devices, activity and motion tracking has become a viable technology to understand and create an engaging user experience. This paper proposes a fast adaptation and learning scheme of activity tracking policies when user statistics are unknown a priori, varying with time, and inconsistent for different users. In our stochastic optimization, user activities are required to be synchronized with a backend under a cellular data limit to avoid overcharges from cellular operators. The mobile device is charged intermittently using wireless or wired charging for receiving the required energy for transmission and sensing operations. Firstly, we propose an activity tracking policy by formulating a stochastic optimization as a constrained Markov decision process (CMDP). Secondly, we prove that the optimal policy of the CMDP has a threshold structure using a Lagrangian relaxation approach and the submodularity concept. We accordingly present a fast Q-learning algorithm by considering the policy structure to improve the convergence speed over that of conventional Q-learning. Finally, simulation examples are presented to support the theoretical findings of this paper., 14 pages, 10 figure

Fourth/Fifth Generation heterogeneous wireless networks (4G/5G HetNets) use or will use small cells (SCs) to extend network coverage and increase spectrum efficiency. However, the standard and technical specifications do not specify how to plan the locations of the SCs within the network. Several papers introduced strategies for planning the locations of SCs in the 4G HetNet architecture. However, SCs placement strategies to support the self-healing functionality of the 4G/5G self organizing networks framework has not been studied in the literature. The placement of SCs in 4G HetNets such that an SC failure will not interrupt service, hence making the network fault tolerant, is an important design and planning problem that is addressed in this paper. We present an integer linear program formulation for planning operators of managed SC locations with fault tolerance. We allow one SC to fail and by using self-healing, a fault-tolerance service is provided at designated fail-over levels (defined in terms of users throughput). We consider the problem of SC location planning by using offloading in both out-band and in-band modes, and an interference model is presented to consider the in-band mode and to address the effect of interference on SCs placement planning. A novel approach to provide a linear interference model by using an expanded state space to get rid of nonlinearity is introduced. We present numerical results that show how our model can be used to plan the positions of SCs. We also incorporate the existence of obstacles in the planning, such as large structures or natural formations, that might happen in real life. To the best of our knowledge, this is the first work that addresses the planning of SC locations in 4G/5G HetNets in a fault-tolerant manner.

In this paper, we present a novel Wi-Fi-based pedestrian collision avoidance (PCA) system: WiSafe. Compared to vision-based and radar-based PCA systems, WiSafe has a key advantage of Non-Line-of-Sight (NLOS). WiSafe can assist drivers in discovering pedestrians in NLOS and blind spots, where the views of drivers are blocked by buildings, vehicles, or other obstacles. In particular, it is very useful when driving in poor visibility conditions such as at night, in heavy rain, or thick fog. WiSafe can save split seconds, which can potentially save lives. Instead of using wireless access in vehicular environments/dedicated short-range communications to protect pedestrians, WiSafe provides a simple, effective, and low-cost solution. Without changing Wi-Fi standards, WiSafe is compatible with 802.11a/b/g/n and can be implemented by apps on smartphones or wearable devices. The complete analysis, implementation, and experiments are presented in this paper. The results show that WiSafe can achieve and even exceed the PCA requirements.

In this paper, a new cooperative two-way cognitive relaying scheme is proposed. In this model, a primary user (PU) network consisting of two PU sources communicate with each other via a single amplify-and-forward (AF) relay. In addition, a secondary user (SU) source transmits its data to an SU destination via the same PU relay node. To mitigate the SU interference caused to the PU network, the PU network considers the SU network pairs as two additional relay nodes helping the original PU relay node in improving the PU network performance. As a reward for its cooperation, the PU network allows the SU network to communicate simultaneously via the PU relay node by using the decode-and-forward protocol. The proposed system allows the transmission of four PU symbols and one SU symbol in four/three time slots resulting in a bandwidth efficiency of $1.25/1.67$ based on the cooperative scheme, respectively. Two power allocation optimization problems are formulated: the first problem minimizes the weighted sum of the average symbol error probability of both PU and SU systems, whereas the second problem maximizes the total achievable sum rate of the PU and SU networks. Lagrangian multiplier method is used to find the optimal solutions for both problems under the constraint of maximum allowable power budget. In addition, the paper investigates how the proposed model improves the PU physical layer security performance against a single passive eavesdropper. The results show that the error performance of the proposed relay selection model outperforms the conventional two-way relaying networks with AF protocol. Moreover, findings illustrate that the total achievable sum rate of the proposed relay elimination model is higher than the total achievable rate of the conventional two-way relaying model. From secrecy point of view, the proposed model is shown to achieve a nonzero secrecy rate that improves the PU system security against eavesdropping attacks.

In this paper, we propose a novel distributed cooperative sensing algorithm for connected vehicles. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this paper by using a computationally efficient numerical approach. The proposed optimization approach minimizes the probability of an incorrect detection as a function of both the probability of false alarm and the probability of missed detection. By considering both probabilities when computing the probability of incorrect detection, to the best of the authors' knowledge, the proposed approach is novel. During the energy detection process, large-scale fading, multipath fading, Doppler effect, and transmission errors affecting the control messaging process are accounted for in order to provide a practical solution for connected vehicles. Once the available channels have been detected, the vehicles share this information using broadcast control messages. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors, where the credibility of each neighbor is weighted during the voting process. An interdisciplinary approach referred to as entropy-based weighting is used to define the neighbor, as well as the vehicle's own credibility. The voting mechanism is switched between the proposed voting mechanism and the traditional voting approach obtained from the current state of the art in order to maintain a balance between the computational cost/latency and robust spectrum sensing. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero.

Contrary to the traditional theoretical analysis with perfect self-interference cancellation, this paper studies the outage performance of a full-duplex (FD) decode-and-forward two-way relay system with the consideration of the residual self-interference incurred by the FD mode. The exact closed-form outage probability expressions are derived in this paper. In addition, the asymptotic outage performance is investigated when the transmit powers increase to infinity, and the result demonstrates that the outage probabilities monotonically increase and finally converge to 1 as the transmit power exceeds a certain threshold. Furthermore, optimal power allocation schemes and optimal relay node placement strategies are then proposed to improve the outage performance. Finally, simulation results are conducted to verify the accuracy of the theoretical analysis.

This paper considers both nondistributed and distributed multilevel amplify-and-forward (AF) wireless relay networks. For a fair comparison, the nondistributed multilevel AF relay network consists of a one-source–one-destination pair and a relay at each level with multiple antennas, whereas the distributed network consists of a one-source–one-destination pair and multiple distributed relays at each level with a single antenna at each relay. In this paper, relay beamforming matrices are determined for both networks based on the minimum mean square error (MMSE) criterion. During data transmission, power is independently and individually constrained at the relays at each level. Finally, an iterative algorithm is proposed to solve the desired optimization problem.

Cellular heterogeneous networks (HetNets), which are realized through shared carrier deployments of macrocells and small cells, are widely seen as a potential solution to serve growing data capacity demands. While these networks pose significant challenges in interference management, much of the focus in earlier efforts has been limited only to small-cell range expansion in the downlink. In this paper, we provide a comprehensive analysis of interference management techniques applicable to the uplink of cellular HetNets, with the goal of characterizing and improving edge user (e.g., 5th percentile) performance. In particular, we propose and study virtual soft-handoff (VSHO), which offers a low-complexity and low-overhead solution that exploits the link asymmetry observed in the uplink geometry of HetNets. VSHO exploits the fact that, in the uplink, an edge macro user who suffers from very low throughput may be closer to a nearby small cell than its own macrocell. The intuition is that such macro users should have better decoding opportunity when their signals are processed at the nearby small cell with better channel conditions. We also study how interference cancelation (IC) and interference avoidance through resource blanking can be incorporated into our VSHO proposal for further throughput gains. In addition to the VSHO techniques outlined in this paper, we also analyze other candidate techniques available in the Third Generation Partnership Project Long-Term Evolution (3GPP-LTE), such as cell-range expansion (CRE) and joint processing, to present a unified view of interference management options available in HetNets.

In this paper, a spectrum-band selection scheme is developed for secondary users (SUs) in underlay spectrum-sharing networks to balance the performance between SUs and primary users (PUs) while guaranteeing PUs' priority. With the developed scheme, among multiple candidate spectrum bands, a given secondary transmitter (ST) is scheduled to access the spectrum band with minimum ratio of the ST–PU channel power gain to the SU link channel power gain. To evaluate this scheme, the SU's performance is investigated concerning its service delay. Under the constraint on average interference from the ST to PUs, the ST's optimal power allocation is obtained in a closed form to achieve the maximum effective capacity (EC) over SU links. Illustrative numerical results and asymptotic discussions substantiate the validity of our derivations and, moreover, demonstrate that, for the case of stringent delay requirements but loose average interference constraint, the band-selection scheme developed in this paper achieves better performance than both the selection of the band with maximum SU link channel power gain and that with minimum ST–PU channel power gain.

With the increasing demand of spectrum and emergence of mobile devices, a cloud radio access network (C-RAN) is a promising technology to improve network capacity and coverage. The key concept of the C-RAN is to separate the radio function unit in remote radio heads (RRHs) from the digital function unit in baseband units (BBUs). This separation facilitates efficient spectrum and infrastructure sharing in the C-RAN. This paper considers the cooperative interference management among RRHs in the C-RAN. The RRHs can form coalitions to mitigate intra-interference and jointly serve their subscribers. To characterize RRH performance under the coalition, this paper develops two signal-to-interference-plus-noise-ratio (SINR)-based downlink throughput models of RRH, where one adopts tools from stochastic geometry to capture the interference from vehicular users (VUs) belonging to noncooperative RRHs, and another ignores the VU interference. In this paper, a coalition formation game is formulated to model the situation in which RRHs of C-RAN can make an individual decision to cooperatively serve their VUs if the throughput of the RRH can be improved. To obtain the solution of the proposed game, we develop a distributed coalition formation algorithm and analyze the stability of the coalition structure using a Markov chain model. Simulation results show that, as compared with the noncoalition and grand coalition, our distributed coalition formation can improve the C-RAN throughput by at least 20% and 80%, respectively. Furthermore, according to extensive simulation, we can define the conditions needed for RRHs to form a coalition and obtain higher throughput.

In cognitive radio networks, secondary users (SUs) can use a frequency band when the primary user (PU) of the band is not transmitting. Spectrum sensing is one of the methods that SUs employ to know if the PU has stopped transmitting. Accurate spectrum sensing boosts the likelihood that an SU detects a spectrum opportunity. However, it will be challenging for affordable receivers to support accurate spectrum sensing due to receiver impairments, including IQ imbalance and aliasing. Several other papers have developed methods that can address the effects of IQ imbalance in spectrum sensing. This paper presents a technique that can address not only IQ imbalance but the effects of aliasing on multiband spectrum sensing as well. We use channelized spectrum-domain modeling of receivers to develop the technique. This paper presents the theoretical development of the receiver modeling technique and the proposed spectrum sensing mechanism. The performance of the proposed mechanism is evaluated using simulations and hardware-based measurements. The results demonstrate that the proposed mechanism significantly enhances the opportunity detection probability of affordable cognitive radios with high IQ imbalance and poor antialiasing filter selectivity performances.

This work considers the problem of reliability and secrecy enhancement for wireless content sharing between a content source node and a content requester. By exploiting the social characteristics of multiple nodes in the presence of multiple independent eavesdroppers, this paper first investigates the impact of mobility for source node selection for transmission reliability, within a cooperative wireless network. Furthermore, trustworthiness and social-tie-based jammer node selections are explored for cooperative jamming to provide secrecy, while allocating power appropriately to the source node and the cooperative jammer node to maximize the worst-case ergodic secrecy rate. Specifically, the source transmitter is selected by first narrowing the potential link set to provide the desired transmission success rate while considering the physical channel and social characteristics jointly. Moreover, the effect of jammer dependability based on its social interactive behavior is also investigated. Instead of focusing on full channel state information (CSI), this paper also investigates the more practical case in which only statistical CSI knowledge is known. Our optimization is based on the upper and lower bounds to the secrecy rate to simplify the power optimization problem without noticeable performance loss. Additional performance analysis for the impact of social characteristics is given. Finally, a one-dimensional search is proposed to further reduce the computational complexity of the power optimization.

The Internet Protocol (IP) Multimedia Subsystem (IMS) is a framework for delivering all-IP-based services. Voice via IMS has been defined as a possible solution from Third-Generation Partnership Project (3GPP) Release 5, prior to long-term evolution (LTE). However, the cost and immediate need for IMS services prevented operators from migration to IMS-based services, particularly with the wide presence of circuit-switched (CS) services offered in Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) networks. CS fallback (CSFB), which was introduced in 3GPP Release 8, enables the support of voice service without IMS. This is the common deployed scenario for many exiting LTE networks. Voice over LTE (VoLTE) is compulsory to offer rich communication services (RCS) via IMS, in addition to improving the performance of the already deployed CSFB voice solution. However, CSFB and VoLTE are still deployed concurrently, where operators can gradually roll out an LTE/IMS system, while still supporting 2G/3G fallback mechanism. It is, therefore, important to benchmark the performance of both solutions, highlight the deployment challenges, and study the impacts on the end-user experience. This paper provides performance analysis, deployment challenges, and comparisons between these voice solutions. This paper presents practical performance analysis, including end-to-end assessment of call setup delay under different radio conditions, main challenges impacting the in-call performance, as well as performance aspects of Single Radio Voice Call Continuity (SRVCC) and its evolution releases.

The use of unmanned aerial systems (UASs), which are also known as unmanned aerial vehicles, and by the term “drones” in the popular press, is growing rapidly. To ensure safety, UAS control and nonpayload communication (CNPC) links must operate very reliably in a variety of conditions. This requires an accurate quantitative characterization of the air–ground (AG) channel, and this channel characterization is the focus of this paper. After providing motivation and background, we describe our methods and modeling approach, followed by a description of our simultaneous dual-band (L-band ∼970 MHz, C-band ∼5 GHz) measurement campaign and the over-water (OW) measurement sites. Example results for path loss and root-mean-square delay spread are provided, as well as the results for channel stationarity distance (SD), used in calculating small-scale Rician $K$ - factor and correlations between the two receiver antennas that we employed in each frequency band. Two distinct SD measures—the power delay profile (PDP) correlation coefficient and the spatial autocorrelation matrix collinearity—were used and found to be of the same order. Path-loss exponents are near that of free space, but significant two-ray cancelation effects for these OW settings warrant more accurate models, which we provide. Delay spreads in the OW channels are also dominated by the two-ray components and are hence typically very small (∼10 ns) but can exceed 350 ns. A third intermittent multipath component (MPC) is also present a nonnegligible fraction of time; hence, we provide statistical wideband AG channel models to represent this. Future papers in this series will report results for the AG channel with ground sites in other types of environments.

This paper investigates the secrecy outage performance of transmit antenna selection (TAS)/maximal ratio combining (MRC) in multiple-input-multiple-output (MIMO) cognitive radio networks (CRNs) over Rayleigh fading channels. In the considered system, a secondary user (SU-TX) equipped with N A (N A ≥ 1) antennas uses TAS to transmit confidential messages to another secondary user (SU-RX), which is equipped with N B (N B ≥ 1) antennas and adopts the MRC scheme to process multiple received signals. Meanwhile, an eavesdropper equipped with N E (N E ≥ 1) antennas also adopts the MRC scheme to overhear the transmitted information between SU-TX and SU-RX. SU-TX adopts the underlay strategy to guarantee the quality of service (QoS) of the primary user (PU) without spectrum sensing. In this paper, we derive the exact and asymptotic closed-form expressions for the secrecy outage probability (SOP). Simulations are conducted to validate the accuracy of the analysis.

This paper investigates collaborative spectrum sharing (CSS) for which a cognitive secondary transmitter acts as a decode-and-forward (DF) relay for two primary users (PUs) occupying an interfering multiple-access channel. PUs are assumed to send their signals simultaneously; hence, interference between the primary signals exists due to the multiple-access nature. The secondary user (SU) selects and forwards one of the PU's signals to a desired destination, and at the same time, the SU also transmits its own signal only if it is not harmful to PUs. The selection of a primary signal to relay is investigated, depending on SU's knowledge of two primary source–destination channels, for which closed-form outage probabilities for PUs and SU are provided accordingly. With the help of the closed-form PU's outage probability, an optimal selection strategy between the primary signals and an optimal power allocation between the primary and secondary signals are also obtained in closed form, which minimizes SU's outage probability while keeping the PU's outage performance at an SU-free level. Numerical investigation is used to verify and illustrate the analysis given in this paper. Numerical results also show that the SU's performance can vary significantly according to the amount of channel knowledge that the SU can have.

Source localization based on time-difference-of-arrival (TDOA) measurements from spatially separated sensors is an important problem in sensor networks. In this paper, we study the optimal geometries of a team of networked sensors for the TDOA-based localization problem, taking into account the a priori uncertainty of the source location. Two types of TDOA sensor pairing methods, namely, centralized and decentralized , are considered. Analytic solutions to the optimal sensor geometries in the ideal case are derived in both static and movable source cases. In the movable source case, sensor geometry design is investigated under an extended Kalman filter (EKF) framework. Furthermore, under sensor motion and communication constraints, we extend this paper to an optimal sensor path planning problem. Simulations demonstrate its enhancement to the source localization and tracking performance.

In this paper, we address the problem of securing information transmission in very adverse environments, i.e., no eavesdropper channel state information (CSI) and imperfect legitimate channel CSI, by introducing a massive multiple-input–multiple-output (M-MIMO) relay. The relay is powered through wireless power transfer from the source, such that it can flexibly adjust its position according to the secrecy requirement. The benefits of a M-MIMO relay are fully exploited to enhance both power transfer efficiency and information transmission security. In particular, the challenging issues incurred by short interception distance and long transfer distance are well addressed simultaneously. The focus of this paper is on investigating the secrecy performance of two classical relaying protocols, namely amplify-and-forward (AF) and decode-and-forward (DF), and obtaining explicit expressions of secrecy outage capacity in terms of transmit power, channel condition, and antenna number. Furthermore, we propose two effective performance optimization schemes, i.e., power control at the source, and relaying protocol switch at the relay. Finally, our theoretical claims are validated by simulation results.

Traffic offloading among coexisting heterogeneous radio access technologies (RATs), i.e., inter-RAT offloading, is considered to be an effective strategy for enhancing the capacity of wireless networks and reducing the power consumption of both base stations (BSs) and mobile stations (MSs). To fully utilize inter-RAT offloading advantages, a mobility-aware evaluation is needed, which takes into account the combined effects of mobility and MS and BS spatial distributions on the performance gains. This paper proposes a novel analytical model that accurately describes MS mobility dynamics in heterogeneous wireless networks, while conveying detailed information on its location. In addition, this paper derives an analytical expression for calculating the packet loss probability for orthogonal-frequency-division-multiple-access (OFDMA)-based networks. Taking users' mobility and spatial distribution into account, this paper develops a Markovian-based framework for evaluating inter-RAT offloading performance. The accuracy of the proposed mobility model and the efficacy of the proposed performance evaluation framework are validated. Results show that MS mobility and vertical handover (VHO) cost significantly affect inter-RAT offloading performance, and ignoring their effects could lead to an inaccurate evaluation. When the effects of MS mobility and VHO cost on the performance are ignored, utilizing inter-RAT offloading decreases the packet loss probability by 9% and saves energy by 6%. However, accounting for these effects results in a 32% increase in the packet loss probability evaluation and a 64% increase in the energy consumption evaluation.

This paper studies the cooperative device-to-device (D2D) transmissions in cellular networks, where two D2D users communicate bidirectionally with each other and simultaneously serve as relays to assist the two-way transmissions between two cellular users. For this scenario, both cellular and D2D links share the same spectrum, thus creating mutual interference. In addition to that, a security problem also exists since the cellular users want to keep their messages secret from the D2D users and vice versa . To address these two issues, a security-embedded interference avoidance scheme is proposed in this paper. By exploiting the constellation rotation technique, the proposed scheme can create interference-free links for both D2D and cellular communications, thereby significantly improving the system error performance. Moreover, our scheme also provides an inherent secrecy protection at the physical layer, which makes the information exchange between cellular users and that between D2D users confidential from each other.

In this paper, secure communication aided by a multiantenna cooperative jammer is investigated. Under very practical but adverse assumptions, i.e., no instantaneous jammer–eavesdropper channel state information (CSI) and imperfect instantaneous jammer–receiver CSI, the residual interference from the jammer to the legitimate receiver appears, even with spatial beamforming. Then, this paper analyzes the impact of imperfect CSI on the function of cooperative jamming and derives closed-form expressions of multiple secrecy performance metrics, including ergodic secrecy rate, secrecy outage capacity, and interception probability. Interestingly, it is found that two antennas at the jammer is always optimal. Furthermore, some insights are obtained through asymptotic analysis, e.g., the secrecy performance is saturated as the source transmit power increases, the ergodic secrecy rate is a linear function of CSI feedback bits in the region of high transmit power at the source/jammer, and interception probability is independent of transmit power at the source and is a decreasing function of transmit power at the jammer. Finally, theoretical claims are validated by simulation results.

In this paper, we consider a cooperative simultaneous wireless information and power transfer (SWIPT) network with one source–destination pair and multiple energy harvesting relays. How to efficiently use these relays has been addressed in conventional cooperative networks, and this paper investigates the impact of SWIPT on the performance of such multirelay cooperative networks. In particular, the main contribution of this paper is that a closed-form expression of the outage probability achieved by the multirelay cooperative protocol is obtained, as well as its approximation at high SNR. In addition, the performance of the cooperative network with the SWIPT relays is compared with that in conventional systems with self-powered relays.

Wireless systems employing frequency-division duplexing (FDD) must use duplexing filters to isolate the sensitive receiver from its own strong transmission. The number of filters in the duplexer is equal to the total number of aggregated transmit and receive bands. These filters are nontunable; therefore, a separate duplexer is required for each combination of operating bands. This paper presents an adaptive duplexer architecture capable of handling more than one receiver channel and tunable over a wide frequency range. The structure uses a combination of a low-isolation device with multiple analog canceling loops controlled by a normalized least mean squares (N-LMS) algorithm to track changes in signal leakage. The control is a multiple-input–multiple-output (MIMO) problem. This paper shows that modeling the inverse plant can orthogonalize the problem and dramatically improve convergence times with reduced complexity over previous search algorithms. Low-power pseudonoise (PN) pilot signals are proposed to detect and cancel the transmitter noise. Simulations show that 50 dB of isolation is possible with 20-MHz Long-Term Evolution (LTE)-like channels. Convergence takes 80 iterations (10 ms) from cold or 15 iterations (1.5 ms) for changes in carrier frequency or antenna loading.

There is an ongoing debate in the research and industry communities as to whether IEEE 802.11p or Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) should be used for vehicular communications. In this paper, we argue that a hybrid vehicular network combining both technologies can increase the performance of the system. We first propose a mechanism to improve location-based routing in a hybrid vehicular network architecture by data and signaling traffic separation on independent wireless networks. We then develop analytical models to calculate the stochastic upper bound of the end-to-end delay (E2ED) for location-based routing in three different networking architecture alternatives based on a) short-range ad hoc only, b) cellular only, and c) the proposed hybrid ad hoc/cellular network. The analytical approach in this paper is based on the stochastic network calculus (SNC) theory, which provides a solid and uniform framework for analysis of the upper bound of the E2ED in communication networks. It is demonstrated that the proposed hybrid network provides a lower E2ED compared with the other two alternatives. Comparisons of realistic simulation results, carried out in NS-3, and analytical results show that the proposed delay bounds provide relatively tight approximations for the E2ED in the three alternative architectures for vehicular networks investigated in this paper.

Security and privacy have become increasingly critical demands in wireless networks, which, however, are particularly susceptible to eavesdropping attacks due to the broadcast nature of radio signals. This paper considers the problem of secure communication in the multiuser downlink with a passive eavesdropper (Eve), whose channel state information (CSI) is unavailable. The transmitter simultaneously transmits concurrent information signals to the users and artificial noise (AN) to Eve. We first assume that all users' CSI is perfectly known by the transmitter and derive a closed-form expression for the ergodic secrecy sum rate (SSR) in the large-system limit. We then use it as an objective function to optimize the power allocation between information signals and the AN. It shows that more power needs to be used for AN when Eve has more antennas and when the system serves fewer users. We also extend the analysis to the imperfect-CSI scenario, where the SSR saturates at high transmit power, and it is better to create more AN than to increase the signal strength when the channel estimation error is large. We derive a scale law of feedback bits (for frequency-division duplexing (FDD) systems) to maintain a constant rate offset compared with the perfect-CSI case and the optimal length of training sequence (for time-division duplexing (TDD) systems) to maximize the effective SSR. It shows that more feedback bits and longer training sequences are required to deal with the eavesdropping problem. Closed-form expressions derived in this paper can reduce the complexity of system analysis and design.

In a cellular network, the network coverage is partitioned into nonoverlapping areas called registration areas to facilitate location management (LM) that keeps track of the location of a user equipment (UE) unit. In the second-generation Global System for Mobile Communications (GSM) and the third-generation Universal Mobile Telecommunications System (UMTS), a registration area is called a location area (LA) in the circuit-switched domain or a routing area (RA) in the packet-switched domain. In the fourth-generation Long-Term Evolution (LTE), a registration area is called a tracking area (TA). To tackle the drawbacks of the LA/RA-based LM scheme used in GSM and UMTS, which is intrinsically a static scheme, LTE adopts a dynamic LM scheme called a TA list (TAL)-based scheme. Under the TAL-based scheme, the network allocates to a UE unit a group of TAs referred to as a TAL instead of only a single TA. The UE can move freely within the allocated TAL without performing any location updates that are called TA updates (TAUs) in LTE. Only when moving into a TA that is not included in the allocated TAL does the UE need to perform a TAU, and afterward, the network will allocate, to the UE, a new TAL. The performance of the TAL-based scheme relies on the allocated TAL. If the allocated TAL is inappropriate with respect to the UE's mobility and traffic characteristics, the TAL-based scheme may produce adverse effects. To find an optimal TAL allocation method for global UE units that exhibit weak regularity in their mobility, this paper develops an embedded Markov chain approach to analyze the signaling cost of the TAL-based scheme. This paper distinguishes itself from existing studies in the following aspects. First, this paper follows LTE technical specifications, that is, the number of TAs in a TAL can vary and, furthermore, is upper bounded, whereas existing studies partially or completely ignore this stipulation. Second, this paper emphasizes the impact of a call handling model that dictates whether a TAU occurs after the completion of a call by considering two call handling models, i.e., a call plus location update and a call without location update. Third, as for the dependence among the cell residence time, the TA residence time, and the TAL residence time, this paper proposes the use of a fluid flow model to describe this dependence, which is simple but does not compromise accuracy. Analytical formulas for the total signaling cost of the TAL-based scheme due to TAU and paging operations, as well as formulas that are useful in designing an optimal paging scheme, are derived, and their accuracy is validated through Mont Carlo simulation. Then, numerical studies are carried out to investigate the impact of diverse parameters on the signaling cost, revealing that the network can allocate, to a UE unit, an optimal TAL that is consistent with the UE's mobility and traffic characteristics to minimize the signaling cost of the TAL-based scheme.

Resource allocation is an important strategy to optimize system performance in multiuser cooperative orthogonal frequency-division multiple-access (OFDMA) systems. In this paper, we jointly consider three different transmission modes in cooperative OFDMA systems, i.e., direct transmission (DT) mode, half-duplex (HD) relay cooperative transmission (HDRCT) mode, and full-duplex (FD) relay transmission (FDRT) mode. The joint optimization problem of transmission mode selection, subcarrier assignment, relay selection, subcarrier pairing, and power allocation (PA) is investigated. In this paper, we transform the binary assignment problem into a maximum-weighted bipartite matching problem, which can be solved by the classical Hungarian method. Based on the dual method, we solve the joint PA and binary assignment problem iteratively. Specifically, since the direct link is considered interference in the FD relay transmission mode, the PA problem in FD relay transmission mode is nontrivial. Thus, we provide a novel hierarchical dual method to solve the PA problem in FD relay transmission mode. In addition, in HDRCT mode, the joint transmission of both the source and relay is taken into account, and we provide a simple and insightful PA scheme. Simulation results show that the proposed algorithms can significantly enhance the overall system throughput, compared with previous works.

This paper discusses over-the-air (OTA) testing for multiple-input–multiple-output (MIMO) capable terminals with emphasis on wideband MIMO channel capacity analysis in a multiprobe anechoic chamber setup. In the literature, the spatial correlation simulation accuracy at the receiver (Rx) side has been used to determine the test area size for a limited number of probes. However, it is desirable that the test area size is defined in terms of data rate deviation of the simulated channel in the laboratory from that of the target channel model. This paper reports MIMO capacity analysis results for wideband spatiotemporal channel models, with emphasis on the impact of the spatial correlation at the transmit (Tx) side, the channel model, and the spatial correlation at the Rx side on the capacity simulation accuracy. Simulation results show that the number of probes is irrelevant to capacity simulation accuracy when the spatial correlation at the Tx side is in the high region (e.g., $\rho > \mbox{0.7}$ ). Furthermore, when correlation at the Tx side is low, the spatial correlation accuracy is less critical with small correlation at the Rx side. The simulation results are further supported by measurements in a practical multiprobe anechoic chamber setup. The capacity simulation accuracy is shown to be a valid measure to determine the test area size.

This paper investigates the scenario in which a weak desired signal reaches a poorly selective receiver along with a high-powered pulsed radar occupying a neighboring channel. Traditionally, an automatic gain control (AGC) is used to fit the high-powered radar into the dynamic range of the receiver. However, this approach desensitizes the receiver because it also sacrifices the signal-to-noise ratio (SNR) of the desired signal. We propose the use of an auxiliary receive path to address this problem of strong neighboring channel signals. In this method, receiver gain is not lowered to avoid clipping. Instead, the strong signal is allowed to clip and distort the desired signal. This paper shows that only a subset of the symbols contained in the desired signal will be distorted; hence, redundancy within the desired signal (due to forward error correction) can be exploited to “fill the gaps” created by the distortion. The auxiliary path samples the envelope of the strong neighboring-channel signal and informs the decoder about which symbols are distorted (or “bad”) and which symbols are not distorted (or “good”). This additional information is shown to improve the estimation performance of the decoder in the presence of high-powered neighboring-channel radar. Using simulation and hardware-based experiments, it is shown that auxiliary-path-based receivers can obtain a significantly better throughput performance than AGC-based receivers.

In this paper, we focus on enhancing the energy efficiency in open-access femtocell networks where many femto base stations (BSs) are deployed in a large public area such as airports, shopping malls, etc. In those areas, the femtocells are overlapped and underutilized during most of the operation time because femto BSs are densely deployed to support the peak traffic load. Therefore, if we properly coordinate the user association (UA) with BSs and put the femto BSs having no associated users to sleep, the energy consumption can be saved remarkably. In this paper, we propose a scheme that jointly decides the operation modes (e.g., active or sleep) of femto BSs and the association between users and the active BSs to minimize the energy consumption in the network. Simulation results show that the proposed scheme can significantly reduce the total energy consumption in the open-access femtocell networks.