Grant-Free Random Access (GFRA) is a key enabler for massive Machine-Type Communications (mMTC) and ultrareliable low-latency communication (URLLC) in 5G and beyond. Traditional methods for user activity detection often rely on prior knowledge of Large Scale Fading Coefficients (LSFC) and the number of active users, which limits their practical applicability. In this paper, we propose a novel manifold-based activity detection method that utilizes the covariance structure of received signals to efficiently identify active users without requiring LSFC or prior knowledge of the number of active users. The proposed method integrates Riemannian distance metrics with machine learning techniques, including logistic regression, Gaussian modeling, and k-means clustering, to enhance detection accuracy. We evaluate three variants: (1) a threshold-based approach trained using logistic regression, (2) an adaptive Gaussian modeling technique for real-time threshold determination, and (3) a k-means clustering method, which proves to be the most effective among the three. Simulation results demonstrate that the manifold-based method outperforms the Multiple Measurement Vector (MMV) approach in detection accuracy while maintaining significantly lower computational complexity. Our findings establish the proposed manifold-based framework as a promising solution for scalable, low-latency activity detection in next-generation wireless networks.

Grant-free (GF) or random access is a key enabler for low-latency massive machine-type communications (mMTC), where devices are sporadically active and transmit small amounts of data. Massive multiple-input multiple-output (mMIMO) technology can enable users’ activity detection for such random access, due to its inherent spatial diversity. One approach employs the sample covariance matrices of received signals to estimate the activity detection. Such covariance-based schemes utilize sub-optimal search algorithms (e.g., coordinate-wise gradient descent) to find solutions for the non-convex maximum likelihood (ML) estimation problem of user activity detection. Covariance matrices are symmetric positive definite (SPD) ones and hence they can be represented over Riemannian manifolds (i.e., curved surfaces). Consequently, users can be represented over such non-Euclidean manifold using a combination of the sufficient-statistic sample covariance matrices and user-dependent pilot sequences. Such unique user’s modeling over Riemannian manifolds paves the road to use geometric-based solutions for activity detection. Specifically in this paper, we propose to utilize geometric k-means clustering to divide users of multi-cell massive MIMO system into two distinct groups, namely, active and inactive ones. Geodesic distances among users’ representations over Riemannian manifold are measured using log-determinant Bregman divergence. Simulation results show that the proposed method reduces probability of miss detection compared to Euclidean-based state-of-the-arts. Finally, the proposed method requires less complexity than Euclidean ones.

5G is the beginning of a new era in cellular communication, bringing up a highly connected network with the incorporation of the Internet of Things (IoT). To flexibly operate all the IoT devices over a cellular network, Device-to-Device (D2D) communication standard was developed. However, IoT devices such as drones utilizing 5G D2D services could be a perfect target for malicious attacks as they pose several safety threats if they are compromised. Furthermore, there will be heavy traffic with an increased number of IoT devices connected to the 5G core. Therefore, we propose a lightweight, fast, and reliable authentication mechanism compatible with the 5G D2D ProSe standard mechanisms. Specifically, we propose a distributed authentication with a delegation-based scheme instead of the repeated access to the 5G core network key management functions. Hence, a legitimate drone is authorized by the core network via offering a proxy signature to authenticate itself to other drones. We implemented the proposed protocol in ns-3 that supports 5G D2D-based communication. We also conducted computational calculations on the RaspberryPi3 IoT device to mimic the drone calculation process and delays. The results demonstrate that the proposed protocol is lightweight and reliable.

Unmanned Aerial Vehicles (UAVs), or drones, are increasingly being utilized for public safety circumstances including post-disaster recovery of destroyed communication infrastructure. For instance, drones are temporarily positioned within an affected area to create a wireless mesh network among public safety personnel. To serve the need for high-rate video-based damage assessment, drone-assisted communication can utilize high-bandwidth millimeter wave (mm Wave) technologies such as IEEE 802.11ad. However, short-range mm Wave communication makes it hard for optimally-positioned drones to be authenticated with a centralized network control center. Therefore and assuming that there are potential imposters, we propose two lightweight and fast authentication mechanisms that take into account the physical limitations of mm Wave communication. First, we propose a drone-to-drone authentication mechanism, which is based on proxy signatures from a control center. Accordingly, any newly joining drone can authenticate itself to an exist one rather than attempting to authenticate to the out-of-reach control center. Second, we propose a drone-to-ground authentication mechanism, to enable each drone to authenticate itself to its associated ground users. Such authentication approach is based on challenge-response broadcast type, and it is still utilizing fast proxy signature approach. The evaluation of the proposed authentication mechanisms, conducted using NS-3 implementation of IEEE 802.11ad protocol, show their efficiency and practicality.

Increasing data rate in wireless networks (e.g., vehicular ones) can be accomplished through a two-pronged approach, which are 1) increasing the network flow rate through parallel independent routes and 2) increasing the user's link rate through beamforming codebook adaptation. Mobile relays (e.g., mobile road side units) are utilized to enable achieving these goals given their flexible positioning. First at the network level, we model regularized Laplacian matrices, which are symmetric positive definite (SPD) ones representing relay-dependent network graphs, as points over Riemannian manifolds. Inspired by the geometric classification of different tasks in the brain network, Riemannian metrics, such as Log-Euclidean metric (LEM), are utilized to choose relay positions that result in maximum LEM. Simulation results show that the proposed LEM-based relay positioning algorithm enables parallel routes and achieves maximum network flow rate, as opposed to other conventional metrics (e.g., algebraic connectivity).Second at the link level, we propose an unsupervised geometric machine learning (G-ML) approach to learn the unique channel characteristics of each relay-dependent environment. Given that spatially-correlated fading channels have SPD covariance matrices, they can be represented over Riemannian manifolds. Consequently, LEM-based Riemannian metric is utilized for unsupervised learning of the environment channels, and a matched beamforming codebook is constructed accordingly. Simulation results show that the proposed G-ML model increases the link rate after a short training period.

Self-driving vehicles will need low-latency and high-capacity vehicular communication for acquiring wider view of their surroundings. Such vehicle-to-vehicle communication can be indirectly supported in some circumstances (e.g., if blocked) through adjacent road side units (RSUs). RSUs will be acting as full-duplex repeaters among the vehicles to ensure low latency and high data rate. However, full-duplex repeaters result in self-interference phenomenon which can degrade the reliability of the communication links. In this work, we aim to enhance the reliability of full-duplex repeaters by canceling out the self-interference impact, and applying a beamforming scheme that is matched to the source-destination composite channel. We show that the proposed self-interference cancellation and beamforming (SICAB) algorithm significantly reduces the error rate for low-isolated repeaters. Finally, we illustrate the impact of the repeater isolation capability on the performance of the proposed SICAB algorithm.

We consider intermittently connected vehicular networks (ICVNs) in which base stations (BSs) are installed along the highway to connect moving vehicles with internet. Due to the deployment cost, it is hard to cover the entire highway with BSs. To minimize the outage time in the uncovered area (UA), several cooperative store-carry-forward (CSCF) schemes have been proposed in which a vehicle is selected to act as a relay by buffering data to be relayed to a target vehicle in the UA. In this paper, we propose an energy-efficient full-duplex (FD) CSCF scheme that exploits the relay ability to receive and transmit simultaneously to improve the effective communication time, Te, between the relay and the target vehicle. Accordingly, it can minimize the outage time and deliver more data to the the target vehicle. In addition, the power allocation that minimizes the transmission cost (TC) under the required rates constraints is found. The problem is formulated as a geometric program (GP) and globally solved using the interior-point method. As compared to the half-duplex CSCF scheme, simulation results show that the proposed FD scheme offers more effective time, more successfully delivered data in the UA and lower TC.

Autonomous vehicles are equipped with multiple high-resolution sensors and cameras for an accurate local view of their surroundings. Equally important, they will need to exchange such high data-rate among each other for a wider view of their environments. The use of high-bandwidth millimeter-wave (mmWave) spectrum bands in vehicular communications can satisfy such demand for high data-rate exchange. Before attempting to design any mmWave vehicular communication system, there is a need to fully understand the propagation characteristics of such mmWave mobile environment. In this paper, we leverage the ray tracing capabilities in the WinProp software suite and study the propagation characteristics of mmWave channels in vehicular communications. In doing so, we present the implementation of the Vehicle-to-Infrastructure (V2I) communication scenario in WinProp. Via simulation results, we are able to show that approximately 20 dB degradation of signal strength can happen within 5 seconds.

The use of Millimeter-wave (mmWave) spectrum in cellular communications has recently attracted growing interest to support the expected massive increase in traffic demands. However, the high path-loss at mmWave frequencies poses severe challenges. In this paper, we analyze the potential coverage gains of using unmanned aerial vehicles (UAVs), as hovering relays, in integrated access and backhaul (IAB) mmWave cellular scenarios. Specifically, we utilize the WinProp software package, which employs ray tracing methodology, to study the propagation characteristics of outdoor mmWave channels at 30 and 60 GHz frequency bands in a Manhattan-like environment. In doing so, we propose the implementation of amplify-and-forward (AF) and decode-and-forward (DF) relaying mechanisms in the WinProp software. We show how the 3D deployment of UAVs can be defined based on the coverage ray tracing maps at access and backhaul links. Furthermore, we propose an adaptive UAV transmission power for the AF relaying. We demonstrate, with the aid of ray tracing simulations, the performance gains of the proposed relaying modes in terms of downlink coverage, and the received signal to interference and noise ratio (SINR).

We introduce the concept of using unmanned aerial vehicles (UAVs) as drone base stations for in-band Integrated Access and Backhaul (IB-IAB) scenarios for 5G networks. We first present a system model for forward link transmissions in an IB-IAB multi- tier drone cellular network. We then investigate the key challenges of this scenario and propose a framework that utilizes the flying capabilities of the UAVs as the main degree of freedom to find the optimal precoder design for the backhaul links, user-base station association, UAV 3D hovering locations, and power allocations. We discuss how the proposed algorithm can be utilized to optimize the network performance in both large and small scales. Finally, we use an exhaustive search-based solution to demonstrate the performance gains that can be achieved from the presented algorithm in terms of the received signal to interference plus noise ratio (SINR) and overall network sum-rate.

Unmanned aerial vehicle (UAV) plays prominent role in enhancing backhaul connectivity and providing extended coverage areas due to its mobility and flexible deployment. To realize these objectives simultaneously, we present a new framework for positioning the UAV to maximize the small-cells backhaul network connectivity characterized by its Fiedler value, the second smallest eigenvalue of the Laplacian matrix representing the network graph, while maintaining particular signal-to-noise ratio constraint for each individual user equipment. Moreover, we show that the localization problem can be approximated by a low complexity convex semi-definite programming optimization problem. Finally, our extensive simulations verify the approximation validity and demonstrate the potential gain of UAV deployment.

Backhaul technologies include traditional technologies such as Radio Frequency (RF) or Optical Fibers (OF) backhauls and include new technologies such as Free Space Optical (FSO) or hybrid RF/FSO backhauls. This paper aims to improve the network connectivity by adding a limited number of OF links along with the wireless connections of RF, FSO or hybrid RF/FSO backhaul links between the small cells. The connectivity is improved while satisfying the minimum data rate (R) constraint and taking into consideration the cost and reliability of different links. We address the problem of maximizing the algebraic connectivity due to inserting different types of backhaul technologies. The Fiedler value, which is the algebraic connectivity of a graph, is used to measure the connectivity of the network. We show that under realistic cost assumption and linear relaxation, the problem is a convex optimization problem. Simulation results show that, using the proposed solution, a high connectivity can be achieved.

Millimeter-wave (mmWave) communications, along with massive multiple-input multiple-output (MIMO) systems, are recently being considered extensively as enabling technologies for emerging 5G cellular networks. The existing literature shows that the capacity in massive MIMO systems is limited by the pilot contamination effect, caused by the reuse of pilot sequences during the uplink channel estimation stage. It has also been proved that the pilot contamination effect increases with the angular spread (AS) of the multipath clusters. In this work, we study the relation between the AS and the capacity of a cellular network, where we show that there exists an optimal AS that maximizes the capacity. Furthermore, we observe that the optimal AS depends on the specific configuration of the network, such as the number of antennas installed at the base station, and the number of cells and users per cell. Since the AS depends on the operating frequency, we argue that the system capacity can be maximized by proper selection of the carrier frequency.

Millimeter-wave large-scale antenna systems typically apply hybrid analog-digital precoders to reduce hardware complexity and power consumption. In this paper, we design hybrid precoders for physical-layer security under two types of channel knowledge. With full channel knowledge at transmitter, we provide sufficient conditions on the minimum number of RF chains needed to realize the performance of the fully digital precoding. Then, we design the hybrid precoder to maximize the secrecy rate. By maximizing the average projection between the fully digital precoder and the hybrid precoder, we propose a low-complexity closed-form hybrid precoder. We extend the conventional projected maximum ratio transmission scheme to realize the hybrid precoder. Moreover, we propose an iterative hybrid precoder design to maximize the secrecy rate. With partial channel knowledge at transmitter, we derive a secrecy outage probability upper-bound. The secrecy throughput maximization is converted into a sequence of secrecy outage probability minimization problems. Then, the hybrid precoder is designed to minimize the secrecy outage probability by an iterative hybrid precoder design. Performance results show the proposed hybrid precoders achieve performance close to that of the fully digital precoding at low and moderate signal-to-noise ratios (SNRs), and sometimes at high SNRs depending on the system parameters.

Unmanned aerial vehicles (UAVs) can be used as aerial base stations (BSs) to deliver broadband wireless connectivity during temporary events, at hotspot areas, or after disasters that may destroy existing communication infrastructure. Since UAV- BSs are low power nodes, their efficient placement is important to reap the maximum capacity and coverage benefits from their deployments. By making use of \emph{UAV mobility} and multi- antenna arrays, it is possible to achieve angular domain user separation with lower feedback requirement. In this paper, we propose an approach to identify optimum hovering locations for UAV-BSs equipped with multi-antenna arrays. We formulate the problem as a signal-to-noise ratio (SNR) maximization at ground nodes subject to a constraint that interference leakage is lower than a threshold. We consider a scenario with two UAVs each with a single user attached and develop our proposed scheme to achieve: 1) angular domain user separation, and 2) SNR maximization at each user. The performance evaluation of the proposed scheme is carried out through simulations, which show that under interference limited conditions the proposed scheme provides capacity performance better than linear zero-force-beamforming (LZFBF), without the requirement of full channel state information of all the users.

Due to the tiny wavelength of millimeter waves (mmWave), tens of antennas can be packed into a small area in mmWave transceivers. However, implementing a radio-frequency (RF) chain for each antenna is impractical due to the high cost and power of mixed-signal devices. To reduce the cost and get benefit from the antennas, an analog RF beamformer is implemented using variable gain amplifiers and analog phase shifters. In this paper, we design the RF precoder for physical layer security. We consider two degrees of channel knowledge at the transmitter. For full channel knowledge at the transmitter, the RF precoder is optimized to maximize the secrecy rate. Two solution algorithms, with different computational complexity, are proposed based on semidefinite relaxation and gradient ascent. For partial channel knowledge at the transmitter, the RF precoder is designed to maximize the secrecy rate under secrecy outage constraint. The problem is safely approximated, and solved by a gradient ascent algorithm within bisection search. Numerical results show that the proposed algorithms converge quickly, and outperform the conventional secrecy schemes.

In this paper we investigate the performance of a densely populated relay network as a massive distributed system. The distributed relaying nodes construct a large set of antennas providing the system with the advantages of both the relays and the massive MIMO systems. We apply large scale analysis to evaluate the performance of the dense relay network as a massive system, and show that the signal-to-noise ratio (SNR) increases almost linearly with the number of relaying devices in the case of amplify-and-forward relaying protocol. In the case of decode-and-forward relaying protocol, we show that the SNR is proportional to the square of number of relaying nodes. We then explore bounds and approximation for the deduced expression. Finally we maximize the energy efficiency of the proposed system by choosing the optimum number of relays.

Device-to-device communication (D2D) is an emerging technology aiming at enhancing the performance of next generation wireless communication systems. D2D communication enables two mobile stations to communicate directly without traversing the Base Station (BS). Smart techniques should be applied to manage the interference between the BS and the D2D communicating devices. In this paper, we investigate the problem of BS precoder design and Power Allocation (PA) to deploy D2D communication in a single-cell network. We assume that the BS uses a very large number of antennas, referred to as Massive Multiple-Input-Multiple-Output (MIMO). We propose solution algorithms to maximize the sum of the achievable data rates of the D2D pairs, or their minimum, while maintaining some Quality of Service (QoS) constraints on the Cellular User Equipments (CUEs) which communicate with the BS. Simulation results show that the proposed solutions are superior to the conventional power allocation schemes.

Introducing low-power Small Cells (SCs) in Heterogeneous Networks (HetNets) deployment can help in satisfying the increasing demands of mobile data rates. On/Off switching of SCs is one of the techniques introduced in LTE-Advanced to improve user throughput in HetNets via reducing interference. In this paper, we propose a novel traffic-aware user association technique which increases the throughput achieved by dynamic SC on/off switching by (12.7% to 24.7%) and reduces the energy consumed per bit by (41.1% to 60.7%) at different traffic loads. The proposed algorithm takes into consideration multiple factors including traffic load and dynamic on/off switching delays of SCs. The new technique also outperforms existing static on/off techniques at most traffic loads.

We consider the design of the radio-frequency (RF) precoder for minimum outage probability transmission for millimeter wave (mmWave) MISO-OFDM systems under the assumption of partial channel knowledge at the transmitter and full channel knowledge at the receiver. We formulate the problem as minimizing the cumulative distribution function (CDF) of an L-stage hypo-exponentially distributed random variable, where L is the number of propagation paths. To solve the optimization problem of the RF precoder, we propose an iterative gradient ascent algorithm. Simulation results show that the proposed algorithm converges in a small number of iterations and achieves lower outage probability, with full diversity order, than the conventional eigenvector beamforming. Moreover, the proposed scheme is more robust against human blockage than the conventional eigenvector beamforming and the maximum capacity scheme with full channel knowledge at the transmitter.

With recent traffic explosion, more innovative solutions are required to accommodate user demands. Various studies were done to promote small cells as possible low cost solution to the current capacity problem. Motivated by the capacity crunch problem, we carried out this study on indoor small cell performance using simulation model which mimics real traffic scenario. In this paper we provide an extensive study using small cell deployment simulation model. Further gain can be added by utilizing higher order modulation. We believe that deploying higher order modulation (256 QAM) enabled small cell will help to solve the capacity problem.

In Heterogeneous networks (HetNet), low-power Small Cells (SCs) can serve a good portion of the mobile users. These users are likely to have good Signal-to-Interference-plus-Noise-Ratio (SINR) values, which can be exploited to satisfy the expected demand of huge data rates. In this paper, we investigate the effect of introducing higher order modulation, mainly 256QAM, from a link-level perspective as a possible solution to this data explosion. 256 QAM in ideal channel conditions and high SINR range, achieves higher spectral efficiency compared to 64 QAM. However, due to transmitter and receiver impairments the gain of 256 QAM is questionable. we developed a physical-layer abstraction for the link-level performance of the 256QAM modulation order. Then, we evaluated the performance of 256 QAM in realistic environment including the impairments at the transmitter and receiver. These impairments can diminish the gains of 256 QAM depending on their magnitude.

In this paper, we propose a novel spatial diversity scheme for the radio-frequency (RF) beamforming in millimeter wave (mmWave) MIMO-OFDM systems under the assumption of partial channel knowledge at the transmitter and full channel knowledge at the receiver. We formulate the spatial diversity problem as maximizing the geometric mean of the projections of the RF precoder on the transmit steering vectors and the geometric mean of the projections of the RF combiner on the receive steering vectors. To solve the optimization problem of the RF beamformers, we propose a simple gradient ascent algorithm. Simulation results show that our proposed spatial diversity scheme outperforms the other spatial diversity schemes in literature in case of no blockage and in case of blockage to any propagation path regardless of the number of propagation paths.

Heterogeneous Networks (HetNet), particularly Femto cells, were introduced to meet the exigent need for higher network capacity. Although Femto cells increased the network capacity, they increased the interference to the Macro Indoor users.In order to avoid the high decrease in cell edge throughput different interference mitigation techniques were introduced like Inter-Cell Interference Coordination and Power Control techniques. In this paper, Non- Unanimous Power Inter-cell Interference Coordination (NUP-ICIC), and Non Unanimous Power Control with Constraint (NUP-C) algorithms are proposed . The schemes can achieve high spectral efficiency with an increase the cell-edge and with high power efficiency.

Heterogeneous Networks (HetNets) comprising of Macro and Femto stations are very promising to increase indoor coverage and throughput of the future cellular networks. In this paper, we characterize the interference environment of the Femto HetNets based on the Femto dual strip deployment model. We show that the Macro Indoor subscribers or User Equipments (UEs), who are not associated with Femto stations (FSs), are the victim UEs. Motivated by this performance degradation, we propose three interference mitigation (IM) techniques. The first technique turns off the interfering FSs in some of the available time-frequency resource blocks (RBs) to free these RBs to be utilized by the Macro UEs. The second technique applies adaptive multi-user zero-forcing (A-MUZF) scheme causing zero interference to the Macro Indoor UEs. The third scheme applies power control in addition to either A-ICIC or A-MUZF. Via Extensive system level simulations (SLS), we show that the proposed schemes significantly improve the performance of the Macro Indoor UEs, while maintaining the high throughput achieved by the FSs.

The current WiMAX operators have to choose whether to utilize reuse-1 (R-1) or reuse-3 (R-3) frequency planning pattern. The R-1 pattern achieves high spectral efficiency but results in high inter-cell interference(ICI), especially at the cell-edge users. As for the R-3, it reduces the ICI and guarantees coverage to the cell-edge users. However, the R-3 pattern still achieves low cell-edge user throughput due to the reduction in the available bandwidth. In this paper, we aim to enhance the performance of the current WiMAX networks by considering multiple Fractional Frequency Reuse (FFR) schemes. We will show that the FFR can significantly improve the cell-edge users throughput with slight degradation in the spectral efficiency compared to the R-1 scenario. More specifically, we will characterize the performance of the FFR by considering multiple FFR algorithms including 2-threshold FFR and adaptive power FFR. Furthermore, we quantify the tradeoff between the the spectral efficiency and cell edge users throughput achieved by these FFR algorithms. The evaluation of these different FFR schemes is done via WiMAX (IEEE 802.16e) system level simulations (SLS).

In the recent years, the WiMAX cellular system has been greatly deployed worldwide as it can provide high data rate to mobile subscribers. However, a few works has been done to characterize the behavior of the WiMAX network in different deployment scenarios. In this paper, we investigate the performance of the WiMAX system in various morphological scenarios, namely, dense urban, urban, and sub-urban. Moreover, we evaluate the behavior of the WiMAX system with different environment parameters such as cell radius, penetration loss, and receiver antenna gain. For each WiMAX scenario, relevant set of performance criteria such as the spectral efficiency is evaluated via system level simulations (SLS). Finally, this paper provides understanding and insights on the main design parameters affecting the performance of WiMAX systems.

In this paper, a binary hypothesis distributed detection problem in correlated wireless sensor networks with cooperative relays deployment is considered. In particular, the effect of correlation between sensor nodes is modeled and analyzed in Rayleigh flat fading channels in order to explore the natural tradeoffs between the number of sensor/relay nodes and the detection error performance in the network. Specifically, two communication protocols are utilized; in protocol I, each sensor node communicates its observation directly to the fusion center while in protocol II, amplify-and-forward (AF) cooperative relays are deployed and a fewer number of sensors is used. Based on the theoretical analysis and simulations, it is revealed that employing less sensor nodes and instead deploying relay nodes results in significant performance gains under strict network power constraint It is concluded that with cooperative distributed detection and exploitation of spatial diversity, better detection error performance is achieved as well as reduction in the required number of sensor nodes.

Channel estimation error problem is among the main causes of performance degradation in wireless networks. In this paper, we investigate the impact of cooperative communications on mitigating the effect of channel estimation error. Two main performance criteria, namely, the traditional outage probability and the proposed signal-to-noise ratio (SNR) gap ratio, are utilized to characterize such impact. The SNR gap ratio measures the reduction in the SNR due to channel estimation error. Taking into consideration the channel estimation error, we show that the outage probability is reduced by utilizing cooperative transmission. We also show that cooperative transmission results in lower SNR gap ratio compared to that of the direct transmission. Thus, cooperative transmission is less susceptible to the effect of channel estimation error compared to direct transmission. Finally, we illustrate that increasing the number of cooperating relays reduces the effect of the channel estimation error more.

In this paper we address the network maintenance problem, in which we aim to maximize the lifetime of a sensor network by adding a set of relays to it. The network lifetime is defined as the time until the network becomes disconnected. The Fiedler value, which is the algebraic connectivity of a graph, is used as an indicator of the network health. The network maintenance problem is formulated as a semi-definite programming (SDP) optimization problem that can be solved efficiently in polynomial time. First, we propose a network maintenance algorithm that obtains the SDP-based locations for a given set of relays. Second we propose a routing algorithm, namely, Weighted Minimum Power Routing (WMPR) algorithm, that significantly increases the network lifetime due to the efficient utilization of the deployed relays. Third, we propose an adaptive network maintenance algorithm that relocates the deployed relays based on the network health indicator. Further, we study the effect of two different transmission scenarios, with and without interference, on the network maintenance algorithm. Finally, we consider the network repair problem, in which we find the minimum number of relays along with their SDPbased locations to reconnect a disconnected network. We propose an iterative network repair algorithm that utilizes the network maintenance algorithm.

In wireless networks, reducing aggregate transmit power and in many cases, having even power distribution increase the network lifetime. Conventional direct transmission (DTX) scheme results in high aggregate transmit power and uneven power distribution. In this paper, we consider location-aware cooperation-based schemes namely immediate-neighbor cooperation (INC), maximal cooperation (MAX), and wireless network cocast (WNC) that achieve spatial diversity to reduce aggregate transmit power and even power distribution. INC utilizes twouser cooperative communication, resulting in good reduction of aggregate transmit power and low transmission delay; however, power distribution is still uneven. MAX utilizes multi-node cooperative communication, providing incremental diversity to achieve even power distribution and substantial reduction in aggregate transmit power. Transmission delay in MAX, however, grows quadratically with network sizes. As a result, the novel WNC is proposed to achieve incremental diversity as in MAX and low transmission delay as in INC. In WNC, mobile units acting as relays form unique linearly-coded signals from overheard signals and transmit them to the destination, where a multiuser detector jointly detects the symbols from all received signals. Performance evaluation in uniformly distributed networks shows that INC, MAX, and WNC substantially reduce aggregate transmit power while MAX and WNC also provide even power distribution.

Cooperative communication can be used to reduce the transmit power of distant mobile units, compared to conventional direct transmission, given the same quality-of-service. However, imposing the constraint of having orthogonal transmission for the source and relays leads to large delay in TDMA systems. For a network of N mobile units, the transmission delay would be N(N+1)/2. In this work, we propose a location-aware cooperation-based scheme that aims to reduce transmit power of distant mobile units while maintaining a low transmission delay. The scheme utilizes a linear network coding protocol, where each mobile unit applies linear network coding to a set of transmit symbols that it has received previously. At the base station, multiuser detection is used to decouple the transmit symbols. Both decode-and-forward and amplify-and-forward cooperative protocols are considered. We show that our proposed scheme achieves a comparable bit-error-rate performance with the conventional cooperation-based TDMA scheme while requiring a delay of (2N-1) time slots, a substantial reduction in the transmission delay.

In this paper, we address the network maintenance problem, in which we aim to maximize the lifetime of a sensor network by adding a set of relays to it. The network lifetime is defined as the time until the network becomes disconnected. The Fiedler value, which is the algebraic connectivity of a graph, is used as an indicator of the network health. The network maintenance problem is formulated as a standard semi- definite programming (SDP) optimization problem that can be solved efficiently in polynomial time. First, we present a network maintenance algorithm that obtains the near-optimum locations for a given set of relays. Second we propose a routing algorithm, namely, Weighted Minimum Power Routing (WMPR) algorithm, that significantly increases the network lifetime due to the efficient utilization of the deployed relays. Third, we propose an adaptive network maintenance algorithm that relocates the deployed relays based on the network health indicator. Finally, we consider the network repair problem, in which we find the minimum number of relays along with their near-optimum locations to reconnect a disconnected network. We propose an iterative network repair algorithm that utilizes the network maintenance algorithm.

Recently, the merits of cooperative communication in the physical layer have been explored. However, the impact of cooperative communication on the design of the higher layers has not been well-understood yet. Cooperative routing in wireless networks has gained much interest due to its ability to exploit the broadcast nature of the wireless medium in designing power efficient routing algorithms. Most of the existing cooperation based routing algorithms are implemented by finding a shortest path route first and then improving the route using cooperative communication. As such, these routing algorithms do not fully exploit the merits of cooperative communications, since the optimal cooperative route might not be similar to the shortest path route. In this paper, we propose a cooperation-based routing algorithm, namely, the minimum power cooperative routing (MPCR) algorithm, which makes full use of the cooperative communications while constructing the minimum-power route. The MPCR algorithm constructs the minimum-power route, which guarantees certain throughput, as a cascade of the minimum-power single-relay building blocks from the source to the destination. Thus, any distributed shortest path algorithm can be utilized to find the optimal cooperative route with polynomial complexity. Using analysis, we show that the MPCR algorithm can achieve power saving of 65.61% in regular linear networks and 29.8% in regular grid networks compared to the existing cooperation-based routing algorithms, where the cooperative routes are constructed based on the shortest-path routes. From simulation results, MPCR algorithm can have 37.64% power saving in random networks compared to those cooperation-based routing algorithms.

In this paper; we propose a new cooperative communication protocol, which achieves higher bandwidth efficiency while guaranteeing the same diversity order as that of the conventional cooperative schemes. The proposed scheme considersrelayselectionvia the available partial channel state information (CSI) at the source and the relays. In particular, we discuss the multi-node decode-and-forward cooperative scenarios, where arbitrary N relays are available. The source determines when it needs to cooperate with one relay only, and which relay to cooperate with in case of cooperation, i.e., "Whentocooperate?" and "Whomtocooperatewith?". An optimal relay is the one which has the maximum instantaneous scaled harmonic mean functionof its source-relay and relay-destination channel gains. For the symmetric scenario, we derive an approximate expression of the bandwidth efficiency and obtain an upper bound on the symbol error rate (SER) performance. We show that full diversity is guaranteed and that a significant increase of the bandwidth efficiency is achieved. Moreover, we present the tradeoff between the achievable bandwidth efficiency and the corresponding SER. Finally, the obtained analytical results are verified through computer simulations.

Recently, cooperative routing in wireless networks has gained much interest due to its ability to exploit the broadcast nature of the wireless medium in designing power-efficient routing algorithms. Most of the existing cooperation-based routing algorithms are implemented by finding a shortest-path route first. As such, these routing algorithms do not fully exploit the merits of cooperative communications at the physical layer. In this paper, we propose a cooperation-based routing algorithm, namely, minimum power cooperative routing (MPCR) algorithm, which makes full use of the cooperative communications while constructing the minimum-power route. The MPCR algorithm constructs the minimum-power route as a cascade of the minimum-power single-relay building blocks from the source to the destination. Hence, any distributed shortest-path algorithm can be utilized to find the optimal route with polynomial complexity, while guaranteeing certain throughput. We show that the MPCR algorithm can achieve power saving of 57.36% compared to the conventional shortest-path routing algorithms. Furthermore, the MPCR algorithm can achieve power saving of 37.64% compared to the existing cooperative routing algorithms, in which the selected routes are constructed based on the noncooperative routes.

Enhancing the connectivity of wireless sensor networks is necessary to avoid the occurrence of coverage gaps. In this paper, we aim at improving the network connectivity of a given network by adding a set of relays to it. We characterize the network connectivity by the Fiedler value, which is the second smallest eigenvalue of the Laplacian matrix representing the network graph. We propose a network-maintenance algorithm, which finds the best locations for a given set of relays. The proposed algorithm obtains the best relays' locations through a multi-level approach. In each level, the search problem can be formulated as a standard semi-definite programming (SDP) optimization problem. We show that the proposed algorithm can increase the average Fiedler value by 35% by adding one relay only.

In this paper, we consider the design of synchronization-aware distributed space-time codes, which we denote as diagonal distributed space-time codes (DDSTC), for N relay nodes helping the source. We impose the diagonal structure of the distributed space-time code to simplify synchronization among the different relay nodes because it is very difficult to synchronize simultaneous transmissions of randomly located relay nodes. We derive an upper bound on the outage probability of the system, which shows that a diversity of order N can be achieved using the diagonal structure of the code. Then, we derive the code design criterion for the DDSTC based on minimizing the pairwise error probability (PEP) to achieve full diversity.

Concealed weapons detection is one of the greatest challenges facing national security nowadays. Recently, it has been shown that each weapon can have a unique fingerprint, which is a set of electromagnetic (EM) resonant frequencies determined by its size, shape, and physical composition. Extracting the resonant frequencies of each weapon is one of the major tasks of any detection system. In this paper, we model the reflected signal from each object as a summation of sinusoidal signals, each at certain frequency equal to one of the object's resonant frequencies. Using this model, we propose a detection approach that is based on a modified version of the multiple signal classification (MUSIC) algorithm. We show by simulations that each object can be represented using a two-dimensional vector, which consists of its two major resonant frequencies.

In this paper, we propose a new cooperative communication protocol, which achieves high bandwidth efficiency while guaranteeing full diversity order. The proposed scheme considers relay selection via the available partial channel state information (CSI) at the source and the relays. More precisely, the source determines when it needs to cooperate with one relay only among arbitrary N relays and which relay to cooperate with in case of cooperation, i.e., "When to cooperate?" and "Whom to cooperate with?". In case of cooperation, the source employs the optimal relay, which has the maximum instantaneous scaled harmonic mean function of its source-relay and relay-destination channels' gains. For the symmetric scenario, we prove that full diversity is guaranteed and that a significant increase of the bandwidth efficiency is achieved. Furthermore, we show the tradeoff between the achievable bandwidth efficiency and the corresponding error rate. Finally, the obtained analytical results are verified through computer simulations.

In this paper we propose a new cooperative protocol, which takes into consideration the partial channel state information (CSI) available at the source. With such protocol a significant improvement in the transmission rate can be achieved in decode-and-forward cooperative transmission, while guaranteeing full diversity order. We derive closed-form expressions for the transmission rate and the symbol error rate (SER) for the M-PSK and the M-QAM signalling. Moreover, we consider two optimization metrics in the protocol design to enhance the system performance; the first is based on minimizing the SER only, while the second is based on minimizing a joint function of both the SER and the transmission rate. Finally, the obtained analytical results are verified through computer simulations