Radar is a key technology in automotive driving for target detection and perception. In this work, we leverage prior environmental information in the form of occupancy maps to design space-time codes for a fully digital MIMO radar. We transform this design problem into the optimization of spatial beamforming gains and time-domain codes. The beamforming gains are optimized to enhance the strength of returns from cells associated with a higher uncertainty of occupancy. The time-domain codes are optimized to minimize the correlation between returns of targets within the drivable space. We validate our method on the nuScenes dataset to show that the designed space-time codes achieve higher detection rates than designs that do not rely on prior information from occupancy maps.

Radar is a key sensing modality to obtain scene understanding in automotive driving applications. However, automotive radars that are based on the widely used frequency-modulated continuous-wave (FMCW) signal waveforms are vulnerable to signal spoofing attacks. These attacks can distort the resulting radar images at the victim radar receiver via a false positive by introducing artificial objects, or due to a false negative by concealing real objects. In this work, we propose a deep learning method to detect radar points compromised by spoofing attacks and to classify the type of attack. Leveraging mid-fusion of radar and camera sensors, as well as a multi-head architecture, our method simultaneously identifies the specific spatial locations where spoofing attacks distort the radar image, which enables the use of undistorted portions of the data for partial functionality. Evaluation on real data with simulated cases of spoofing attacks shows that our approach achieves mean classification F1scores of 0.93 for false positive and 0.82 for false negative attacks, demonstrating its effectiveness in enhancing radar image integrity.

Synthetic generation of radar range-azimuth (RA) maps remains challenging due to limited automotive radar datasets. While camera images are abundant across diverse driving environments, translating visual information directly to radar representations requires sophisticated multi-modal fusion techniques. In this paper, we introduce RAILS, a novel convolutional autoencoder architecture that synthesizes realistic RA maps by integrating RGB camera images, LiDAR depth information, and semantic scene segmentation. By leveraging a U-Net inspired architecture with convolutional block attention mechanisms, our approach transforms multi-modal inputs into accurate radar representations. We demonstrate the model's effectiveness across various driving scenarios using the RADIal dataset, showing superior performance in target localization and scene reconstruction compared to existing methods. Experimental results highlight the potential of using auxiliary depth and semantic information to address the scarcity of radar training data, offering a promising approach for enhancing machine learning-based radar perception in autonomous driving systems.

The scarcity of automotive radar datasets is a hindrance in the adoption of machine learning-based radar solutions for assisted and autonomous driving systems. In contrast, there is a larger availability of camera images under different driving environments. In this paper, we develop a radar point cloud data emulation methodology to estimate the radar point cloud probability density function (PDF) corresponding to co-centered camera images. Our method uses convolutional neural networks (CNNs) trained on camera images and available radar point cloud data to predict a set of Gaussian mixture model (GMM) parameters. The resulting parametric PDF model can then be used to emulate radar point clouds for a given scene, and also to produce a high-density radar point cloud dataset. Qualitative and quantitative evaluation of the proposed method on the RADIal dataset shows promising results in synthesizing realistic radar point clouds from the corresponding camera images.

Millimeter-wave radar is a common sensor modality used in automotive driving for target detection and perception. These radars can benefit from side information on the environment being sensed, such as lane topologies or data from other sensors. Existing radars do not leverage this information to adapt waveforms or perform prior-aware inference. In this paper, we model the side information as an occupancy map and design transmit beamformers that are customized to the map. Our method maximizes the probability of detection in regions with a higher uncertainty on the presence of a target. Simulation results on the nuScenes dataset show that the designed beamformer achieves substantially higher detection rates than a conventional omnidirectional beamformer for the same transmitted power.

Security and energy efficiency are two critical design metrics in the future wireless communication networks. In this paper, a Reconfigurable Intelligent Surface (RIS) assisted multiple-input single-output (MISO) downlink network is investigated. In order to counteract the multiple randomly distributed eavesdroppers, an artificial noise (AN) jamming scheme is proposed. For achieving a desirable performance tradeoff between security and energy efficiency, a new metric of secrecy energy efficiency (SEE) is proposed. In order to maximize the SEE, an optimization problem is then formulated, subject to the maximum transmit power limit and minimum required data rate. For tackling the challenging non-convex fractional order problem with multiple mutually coupled variables, an efficient alternating optimization algorithm based on Dinkelbach and semi-definite programming (SDP) relaxation is proposed. This corresponds to a joint design of the transmit pre-coding matrix, the covariance matrix of AN, and the phase shifts of RIS. Simulation results demonstrate that an inherent trade-off exists between the secrecy rate and SEE, and significant performance gains in terms of SEE are achieved by the proposed scheme as compared to existing schemes. Furthermore, the introduction of AN into the transmit beamforming plays a crucial role in enhancing the SEE, especially as the number of eavesdroppers increases.

With the emergence of new services and applications, it becomes indispensable to jointly allocate heterogeneous network resources in face of various quality-of-experience (QoE) requirements. In order to quantitatively characterize the tradeoff between communication, computation and caching (3C), which is still unclear, a typical application of adaptive bitrate (ABR) content streaming is considered in fog radio access networks (F-RAN). For improving the QoE, an optimization problem of minimizing the average delay is first formulated subject to constrained 3C resources. To solve the resulting problem that is NP-hard, it is first relaxed as a linear programming problem, then an alternating direction method of multipliers (ADMM)-based algorithm is proposed, which has the advantages of relatively low complexity and fast convergence. Simulation results show that with a joint allocation of 3C, significant performance gains are achieved by the proposed ADMM-based algorithm. Furthermore, while the scarcity of one resource can be compensated by other resources to a certain extent, it requires a matched allocation of 3C resources to effectively improve QoE and at the same time avoid resource waste.

In this paper, edge caching is investigated subject to time-varying content popularity where no systematic distri-bution of content popularity can be known in advance. For achieving efficient caching updates sequentially, two optimization problems of maximizing the long-term accumulated-cache-hit-ratio (ACHR) and minimizing the long-term average-content-provision-cost (ACPC) are formulated. In order to solve these two problems, a deep deterministic policy gradient (DDPG)-based caching algorithm is proposed, which is capable of pro-cessing large-scale and continuous action space and adjusting the caching strategies based on the historical observations of users' requests. To evaluate the performance of the proposed DDPG-based caching algorithm, a real-world data set from MovieLens is adopted. Simulation results demonstrate that sig-nificant performance gains in terms of both ACHR and ACPC are achieved by the proposed algorithm over existing caching strategies. Furthermore, an inherent performance tradeoff exists between the ACHR and the ACPC, and the balance between these performance metrics requires careful system parameter selection.

In order to enhance the service provisioning to users in the indoor environment, a hybrid visible light communication (VLC)/radio-frequency (RF) Internet of Things (IoT) system is proposed based on simultaneous lightwave information and power transfer (SLIPT). A mobile user equipment, which serves as an off-the-grid relay, is able to extract information from the light-emitting diode source and then forward the processed information to the destination far away, thus dividing the signal transmission into two hops. Specifically, the optical signal received at the relay is separated into alternating current and direct current components for information decoding and energy harvesting, respectively, in the first hop. Then, the energy harvested is used to forward the processed source information to the destination by using RF in the second hop. Subject to the constraints imposed on both the average and the peak powers of the source, the end-to-end outage probability of the system is analytically derived in a closed form. On this basis, the minimization of the end-to-end outage probability is formulated as an optimization problem. This problem is then solved with a joint design of the peak amplitude and the direct current bias of the source transmitter, by trading-off between the performance of two successive hops. Simulation results demonstrate that by using the proposed optimal solution, the information flow and energy flow can be dynamically balanced, resulting in significant performance gains in terms of outage probability and throughput.

We consider the problem of detecting commissioning changes in connected lighting systems. Commissioning changes can occur due to repositioning of luminaires/sensors or space renovation. This results in incorrect commissioning mapping of devices to areas, thereby impacting analysis and interpretation of data from such devices. We propose an automated method to detect changes in commissioning mapping using occupancy sensor data. We use similarity features across occupancy sensors and employ a random forest binary classifier to detect changes. The proposed method is evaluated using data from a simulated office environment and an experimental testbed, and is shown to have high accuracy.

We consider the problem of classifying anomalous occupancy sensor behavior in connected indoor lighting systems. Anomalous occupancy sensor behavior may occur in the form of either a high number of false alarms (type-1 anomalies) or missed detections (type-2 anomalies). Two anomaly discovery scenarios are considered: one, in which no anomalies exist post-deployment, and two, in which both anomaly types are found together with normally functional sensors. We address the problem of classifying anomalies that may occur subsequently using a machine learning approach. Under scenario 1, we consider a one class random forest classifier to determine whether an occupancy signal is normal or not. In scenario 2, we consider a supervised random forest classifier to determine whether the detection signal of an occupancy sensor is normal, or exhibits type-1 or type-2 anomalies. We devise occupancy signal features in time and frequency domains to perform 2-class classification in scenario 1, and 3-class classification in scenario 2. The proposed method is evaluated using motion sensor data from an office building, and is shown to have higher true positive rate and a lower false positive rate in comparison to an unsupervised k -means method and a random forest classifier with a single signal energy feature.

In this paper, content caching is considered at the edge of the network with an objective of offloading recurrent traffic on the capacity-stringent backhaul links to the vicinity of end users. A radio access network equipped with edge servers is considered for caching contents of various sizes, based on which problems of maximizing the edge cache-hit-ratio and minimizing the average content-provisioning cost are respectively formulated. To solve the underlying 0-1 Knapsack problem, a size-weighted popularity (SWP)-based caching framework is proposed, where both content popularity and content size are taken into account when determining the contents to be cached. Depending on the available knowledge and the manner in which the contents are pre-fetched and cached at the edge servers, two algorithms: proactive and reactive, are proposed for the implementation of SWP-based caching. Simulation results are presented to evaluate the performance of our proposed algorithms. We observe a fundamental tradeoff between the average content-provisioning cost and the cache-hit-ratio, and the proactive algorithm outperforms the reactive algorithm.

Building space accounts for one of the largest operational costs for companies. While space management has traditionally been done based on human observations, technology solutions are increasingly been considered. In this paper, we consider advanced sensing systems that provide location data at a certain spatio-temporal granularity. Location data analytics is then considered to realize two space management applications: (i) space utilization, and (ii) workspace recommendation. Towards this end, location data is processed to determine potential workspaces. The processed historic location data is used to compute defined metrics that characterize space utilization. Filtering of real-time location data is presented to recommend workspaces that may be potentially unoccupied and present to a user. Using datasets from an experimental office testbed, we evaluate the proposed sensing and analytics solution.

Visible light communications (VLC) with light-emitting diodes (LEDs) has attracted applications, such as data communications, lighting control, and light interaction. In this paper, we propose a system by which two LED devices are used for two-way VLC while also providing illumination. We consider Manchester encoding with on-off keying for transmission. A reception scheme in which the LEDs themselves are used as receivers by sensing in the OFF periods is considered. A synchronization scheme to achieve frame- and symbol-level synchronization is also proposed. A prototype of the proposed system is designed and the communication performance is evaluated.

Visible light communications (VLC) with light emitting diodes (LEDs) has attracted applications like data communications, lighting control and interaction. In this paper, we propose a system in which two LED devices are used for two-way VLC while also providing illumination. We consider a redundant run-length limited encoding for data transmission. A reception scheme in which the LEDs themselves are used as receivers by sensing in the off period is considered. A prototype of the proposed system is designed and the communication performance is evaluated. An advantage of the proposed system is that no additional light sensors are needed as the LEDs themselves are used as communication transceivers.

In this paper, we consider a two-path relay channel (TPRC) with the assistance of two decode-and-forward relays alternatively. Upon successfully decoding a source packet, a relay proceeds to forward the decoded packet to the destination, which brings an interference to the other relay. Owing to this inter-relay interference, the decoding result at one relay in the current time slot depends on the decoding result at the other relay in the previous time slot. Exploiting this single-slot memory, the decoding performance of the relays is analyzed using a Markov chain. Furthermore, since the relay transmission is one slot behind the source transmission, the neighboring source packets received at the destination interfere with one another. Then depending on whether a packet is subject to the residual interference from its previous packet, the decoding performance of the destination can be similarly analyzed using a Markov chain. Thus we can obtain the overall outage probability of TPRC in closed-form expressions. Simulation results are provided to demonstrate the performance of the considered TPRC, where the effects of various parameters are evaluated. By comparisons with existing works, a reasonably good performance is achieved for TPRC with only a single-slot delay.

We consider a cooperative multi-path relay channel (MPRC) where multiple half-duplex relays assist in the packet transmissions from a source to its destination. A virtual full-duplex (FD) relaying scheme is proposed that allows the source to transmit a new packet simultaneously with the selected best relay, with the rest of the relays attempting to decode this new packet. Thus, a new source packet can be served in each time slot, as in FD relay systems. Taking into account the effect of inter-relay interference (IRI) that is caused by simultaneous relay and source transmissions, a Markov chain analytical model is used to characterize the decoding performance at the relays, based on which the overall outage probability of MPRC is obtained in closed-form expressions. The asymptotic performance analysis reveals that in low rate scenarios, a close-to-full diversity order is achieved by the proposed scheme while substantially improving the spectrum efficiency. In high rate scenarios, the decoding performance of relays is limited by IRI and the system outage performance experiences an error floor. Simulation results demonstrate the performance gains of the proposed scheme by comparisons with existing half-duplex and FD relay systems in the literature.

We consider a cooperative two-path relay channel (TPRC) where a data source transmits new packets to a corresponding destination, with the assistance of two intermediate relays alternatively. When the transmitted source packet is successfully decoded by a relay, the relay proceeds to forward this packet in the subsequent time slot, otherwise it simply stays silent. Due to the inter-relay channels, the decoding result at a relay in the current time slot depends on the decoding result at the other relay in the previous time slot and not on that preceded it. In view of this property, we employ a Markov framework to analyze the decoding performance at the relays. The decoding of successive packets received at the destination can be similarly analyzed by using a Markov chain. Closed-form expressions of the outage probability are derived for TPRC by exploiting the properties of a Markov chain. Numerical results demonstrate that with the proposed scheme, a reasonably good performance is achieved with only a single-slot delay and relatively low complexity.

Secure indoor positioning is critical to successful adoption of location-based services in buildings. However, positioning based on off-the-air signal measurements is prone to various security threats. In this paper, we provide an overview of security threats encountered in such indoor positioning systems, and particularly focus on the relay threat. In a relay attack, a malicious entity may gain unauthorized access by introducing a rogue relay device in a zone of interest, which is then validly positioned by the location network, and then transfer the control rights to a malicious device outside the zone. This enables the malicious entity to gain access to the application network using the rogue device. We present multiple solutions relying on a presence sensing system to deal with this attack scenario. In one solution, a localized presence sensing system is used to validate the user presence in the vicinity of the position before location-based control is allowed. In another solution, the user device is required to respond to a challenge by a physical action that may be observed and validated by the presence sensing system.

We consider control of multiple luminaires with a central controller and occupancy and light sensors co-located at the luminaires. The sensors periodically provide local occupancy state and illumination information to the central controller. Using this sensor feedback, the central controller determines the dimming levels of the luminaires so as to adapt artificial light output to changing daylight levels and occupancy conditions, in an energy efficient way. We propose a multivariable feedback controller based on optimizing a cost function with a component corresponding to power consumption and another corresponding to illumination errors at the light sensors. The constraints are that the attained illumination value at the light sensors be no smaller than the reference set-points and that the dimming levels of luminaires are within physical limits. We compare the performance of the proposed controller with a simple stand-alone reference controller. We show via simulations in an open-plan office lighting system that the proposed controller has better performance in terms of achieving the reference set-points.

Occupancy analytics refers to statistical analysis related to occupancy of users in a building to derive information and insights based on which control and management of building systems may be improved. We consider the use of a wireless sensors infrastructure in a lighting system to derive occupancy analytics. Specifically, radio received signal strength indicator (RSSI) values at wireless motion and light sensors are used that result from transmissions of user devices. Statistical methods are proposed to derive occupancy metrics: occupancy density, area usage, and occupant dwell times. We evaluate the performance of the proposed approach using an open-plan office wireless lighting control model.

A cooperative multi-path relay channel (MPRC) with multiple decode-and-forward relay terminals is considered in this paper. In order to enhance the system reliability, the source is encouraged to transmit at a higher power such that more relays can successfully decode the source symbol. This, however, may lead to unnecessary energy waste. For reliable symbol delivery while improving the system energy efficiency, we propose power adaptation schemes at the source and relays depending on the availability of channel state information (CSI). In order to minimize the energy consumption for successfully delivering a source symbol, both the source and relay adaptively select a suitable transmit power from a finite set of discrete power levels. The outage probability and energy efficiency of the cooperative MPRC are analyzed and simulated. Simulation results demonstrate a tradeoff between the outage performance and energy efficiency. Under the same outage performance, the system energy efficiency can be significantly improved by the proposed power adaptation schemes compared to a benchmark case with blind source transmissions.

The problem of speech enhancement is considered in an interference environment, typical to applications like hands‐free voice communication and multi‐party conferencing. In the proposed system, a directional microphone placed at each interference is used to estimate the power spectral density (PSD) of the interference and the quantised PSD estimate is transmitted over a wireless link to an omnidirectional primary microphone that observes the corrupted source speech signal. At the primary microphone, the received observations are fused to obtain an estimate of the PSD of the desired speech signal. The problem of minimising transmitted power is considered subject to constraints on total transmission rate and maintaining the mean‐squared error in the estimated speech signal PSD below a prescribed limit, under narrowband and broadband signal models. The optimisation problem is solved by determining the optimum rate for encoding signal PSDs. The proposed strategy is analysed using sample speech and music signals.

An ultrasonic sensor that employs moving target processing based on differential echo processing and occupant tracking is considered for indoor occupant presence detection. We present a simple statistical model to analyze the presence detection performance of such a sensor. The probability distributions of the differential power signal are first obtained under vacancy and occupancy conditions. We then study the influence of occupant tracking and derive an upper bound on the probability of false alarm. Experimental data is used to verify that the presented analytical statistical models match actual distributions of the differential power.

We consider a spectrum sharing protocol wherein the primary and secondary transmitters cooperatively relay each other's message. Transmission is done in two phases, with each transmitter attempting to decode messages from the other system transmission in a first phase. The second phase transmission consists of the decoded message superposed onto its own message. Priority is given to the primary system transmissions by having the primary message always transmitted over the two phases, while the secondary message is transmitted depending on successful decoding. We consider the scenario where the primary and secondary receivers are co-located, forming a virtual two-antenna receiver. We assess the performance of the system in terms of outage probability and characterize performance corresponding to each state of the Markov chain that governs the proposed transmission protocol. We show that joint decoding offers a 20 dB performance improvement over separate decoding for the primary user and 1.8 dB for the secondary user.

Luminaires based on light emitting diode (LEDs) offer ease of control for light adaptation. In particular, adapting light output of the LED luminaires to daylight leads to energy-efficient lighting solutions. In a daylight-adaptive lighting system, the dimming levels are determined such that the artificial illuminance together with the daylight illuminance meets specified illuminance constraints. Closed-loop illumination control is traditionally used based on feedback obtained by measurements using light sensors, adding to cost and installation complexity. In this paper, we present a solution wherein the LED luminaire is used as a light source as well as a light sensor. We propose a protocol wherein the LEDs are driven in forward-bias by a pulse width modulation signal, thus emitting light, and in reverse-bias over a duration where they sense light. Under the proposed solution, the sensed illuminance is solely the daylight contribution. This enables use of simple open-loop illumination control schemes for daylight adaptation. We demonstrate the proof-of-principle with an LED array prototype.

Visible light communications (VLC) with light emitting diodes (LEDs) and photodiodes enables a wide range of applications in LED lighting systems. One of the main challenges in VLC is the limited range of reliable communications, owing mainly to the non-coherent nature of optical communications and limited output power of LED luminaires. In order to enhance VLC range without compromising the network throughput, we consider full-duplex relay VLC. Specifically, we consider a basic 3-luminaire (source, relay and destination) linear system topology under amplify-and-forward and decode-and-forward processing at the relay luminaire. Due to full-duplex operation at the relay luminaire, a self-interference signal component arises and is subsequently canceled out as part of the relay processing. We analyze the system performance in terms of bit error rate (BER) and show that multiple orders of magnitude improvement in BER is achieved as compared to direct link VLC under practical indoor conditions.

We consider a cognitive spectrum sharing system on an interference channel with a cognitive relay (IFC-CR) assisting both the primary and secondary users in forwarding their messages to the respective destination nodes. The CR uses a successive interference cancelation scheme to decode the primary and secondary messages after a first transmission phase. The CR performs power allocation and in the second transmission phase, forwards a linear weighted combination of the decoded primary and secondary messages. We demonstrate that with a properly designed power allocation, secondary spectrum sharing is achieved and at the same time a better performance can be achieved for the primary user than the case without spectrum sharing. The proposed spectrum sharing scheme further does not require any non-causal knowledge of the primary message at the secondary user or at the CR.

We consider energy-efficiency- and user-comfort-driven design of indoor light-emitting-diode (LED) lighting control systems by achieving spatial illumination rendering adapted to presence and daylight conditions, and user preference for the amount of rendered illuminance. A localized illumination rendering strategy for lighting control is presented, where a given level of uniform illuminance is provided with a certain user satisfaction level over a user-occupied zone, and a lower illuminance level is maintained in unoccupied zones. Under these illuminance constraints, our objective is to minimize a weighted sum of power consumed in localized illumination rendering and the net user dissatisfaction with the rendered illumination. This is achieved by determining the dimming levels for controlling the multiple LED luminaires. Algorithms for centralized and distributed lighting control are proposed. Simulation results are presented to evaluate the performance of the algorithms in achieving power savings and in meeting user preferences of illumination levels.

In this paper, we consider a hidden terminal scenario where two transmitters A and B, hidden to each other, wish to communicate to a common access point, AP. When a collision occurs at AP, due to the inherent asynchrony between the colliding packets, the mutual interference between them is effectively decreased. This achieves a higher signal-to-interference-plus-noise (SINR) ratio which improves the probability of successfully decoding both colliding packets through conventional successive interference cancellation (SIC). When neither colliding packet can be decoded first through SIC, we propose an enhanced SIC (ESIC) scheme. The proposed decoding scheme does not require synchronization, coordination or power control between the transmitters or a sophisticated coding design. By exploiting the inherent asynchrony between the two colliding packets, there exists, with high probability, an interference-free chunk together with an interfered chunk in a packet ready for decoding. Thus it is still possible for both colliding packets to be recovered eventually from a single collision. Our results demonstrate that through the proposed ESIC scheme, both colliding packets can be recovered with a higher probability thus improving the system throughput.

We consider an ultrasonic sensor system deployed for indoor presence detection. In such a presence sensing system, we are interested in the problem of user localization using time-difference-of-arrival (TDOA) measurements collected, due to transmission from sensors in different time slots, at a particular sensor. We present a tracking algorithm to improve estimation of TDOA values resulting from a user movement. Subsequently the localization algorithm to obtain user position from the estimated TDOA values is described. Validation of the algorithms is done using an experimental setup to demonstrate proof-of-concept in an office setup.

We consider the control of lighting systems with embedded sensing, communication, computation and control functions at the luminaire-level. Each intelligent luminaire has (i) local presence sensing information, (ii) local light distribution information, (iii) a controller that determines its dimming level, and (iv) connectivity with other luminaires in its neighborhood. In a lighting system of such luminaires, we are interested in achieving localized illumination rendering wherein average illuminance levels of Loand Luare to be provided in occupied and unoccupied zones respectively, with a given uniformity level. Under these constraints, we minimize the power expended for rendering in the lighting system. A distributed control algorithm is designed to determine dimming levels of each luminaire. The performance of the proposed algorithm is compared with a centralized control algorithm in terms of power consumption and achieved illumination rendering, under different occupancy conditions.

In this paper, we propose a two-phase protocol based on cooperative relaying for a secondary system to achieve spectrum access along with a selective relaying primary system. The primary system comprises of a transmitter-receiver pair PT-PR and M relays Ri, i G {1,2,⋯ , M}. The secondary system is a multi-user system with N transmitters Ri, i ϵ {M +1, M + 2, ⋯ , M + N } which intend to communicate with a common receiver SR. In the proposed protocol, terminals Ri, i ϵ M1= {1, 2, ⋯ , M + Q} are designated as possible candidates for assisting the primary system while the remaining secondary transmitters Ri', i' ϵ M2= {M + Q + 1, M + Q + 2, ⋯ ,M + N} are chosen as possible candidates for secondary spectrum access, where 0 ≤ Q ≤ N. The relaying terminal Rp, p ϵ M1which achieves the request target rate for the primary system and has the best channel to PR, is first selected from M1to serve as a decode-and-forward (DF) relay for the primary system. With the cooperation of Rp, the primary system is able to tolerate some interference lower than a certain threshold in the relaying phase, without degrading its outage performance. The secondary transmitter Rs, s ϵ M2which satisfies this interference constraint and optimizes the outage performance for the secondary system, is then selected from M2to access the spectrum band simultaneously when Rpis relaying the primary signal. Analytical and simulation results confirm the efficiency of the proposed spectrum sharing protocol. We show that there exists an optimal value for Q and both primary and secondary systems are able to achieve better outage performance with increasing N.

We consider spectrum sharing in a cognitive radio network where a secondary system co-exists with an automatic repeat-request (ARQ)-based primary system. A cooperate-and-access spectrum sharing protocol is proposed where the secondary system alternates between cooperation and access modes. In the cooperation mode, the secondary system serves as a relay to assist the primary transmission, and in return accumulates credits. The credits allow the secondary system to gain spectrum access by exploiting the ARQ retransmissions of the primary system. We show analytically that through the proposed credit system, as long as the credits accumulated in cooperation mode compensate for the degradation in primary performance during access mode, an equal or higher average throughput is achieved for the primary system than in the case without spectrum sharing, while providing spectrum access opportunities for the secondary system.

In the context of spectrum sensing, we investigate the performance of detectors equipped with M antennas (co-located or distributed) under Rayleigh fading, in terms of detection diversity. Rather than the high-SNR concept of diversity order common in the communications literature, we adopt the notion recently advocated by Daher and Adve in the radar community: the slope of the average probability of detection (P̅D) vs. SNR curve at P̅D= 0.5. This definition is well suited to spectrum sensing, which invariably deals with low SNR levels. It is shown that the diversity order grows as M for an optimal centralized detector having access to all observations, whereas for the two distributed schemes considered (the multiantenna energy detector and the OR detector) it grows no faster than √M.

In this paper, we propose a cooperative spectrum sharing protocol (CSSP) between two overlapping static ad hoc wireless networks where the primary and secondary networks consist of n and m randomly distributed nodes respectively. The secondary network achieves spectrum access along with the primary network by allowing its nodes to relay the primary traffic. Taking advantage of the broadcast nature of wireless channels, the secondary nodes are able to forward primary and secondary packets simultaneously by transmitting a superimposed signal. We analyze the throughput and delay scaling performance of the proposed protocol and show that given m ≥ n, the primary network is able to achieve a per-node throughput scaling which is better than that of a stand-alone network with n nodes. At the same time, the secondary network achieves the same throughput scaling as a stand-alone network with m nodes. We also derive the throughput-delay tradeoff for both the primary and secondary systems in this scenario.

In this study, the authors consider a cognitive radio scenario and focus on the spectrum efficiency of sensing-transmission protocols for a secondary dual-hop relay system. A straightforward dedicated sensing protocol is first considered as a benchmark, where sensing is performed in dedicated sensing periods at both the source (S) and the relay (R) before their respective transmissions. This, however, leads to a substantial loss in spectrum efficiency for the secondary system. In view of the spectrum efficiency loss in the dedicated sensing protocol, the authors propose an alternative approach, namely simultaneous sensing protocol. In this protocol, sensing is only performed at S, during the period when R transmits to destination (D), by cancelling out the self-interference component that is known a priori. The authors derive the closed-form expression of the average probability of detection for the proposed simultaneous sensing protocol. Furthermore, by deriving the average collision time and average utilisation time for both the dedicated and simultaneous sensing protocols, the authors show that the simultaneous sensing protocol significantly improves the spectrum efficiency for the secondary system and also achieves a higher overall spectrum utilisation of the spectrum band, compared to the dedicated sensing protocol.

We consider a two-stage sensing scheme for cognitive radios where coarse sensing based on energy detection is performed in the first stage and, if required, fine sensing based on cyclostationary detection in the second stage. We design the detection threshold parameters in the two sensing stages so as to maximize the probability of detection, given constraints on the probability of false alarm. We compare this scheme with ones where only energy detection or cyclostationary detection is performed. The performance comparison is made based on the probability of detection, probability of false alarm and mean detection time.

We consider illumination sensing in a light emitting diode (LED) lighting system based on frequency division multiplexing (FDM). In the FDM scheme, LEDs render periodical illumination pulses at different frequencies with prescribed duty cycles. The purpose of illumination sensing is to identify the illumination contributions of different LEDs at a target location, within a limited response time. With the use of a photosensor at the target location, the problem of interest is to estimate the amplitude of the sensor signal component due to each LED. In this paper, we propose a successive estimation approach exploiting higher order harmonics of the sensor signal. We show that a larger number of LEDs can be supported using the proposed approach, as compared to our previous approach using only the fundamental frequency component, at the same estimation error.

In this paper, we propose a two-phase protocol based on cooperative relaying for a secondary system to achieve spectrum access along with a primary system. The primary system comprises of a transmitter-receiver pair PT-PR, and the secondary system comprises of M transmitter-receiver pairs STi-SRi, i ∈ {1,2,⋯M}. The secondary pair STb-SRbwhich is able to provide the best performance for the primary system, is selected to access the spectrum, with STbserving as a cooperative relay for the primary system. In the first transmission phase, PT transmits the primary signal to PR, which is also received by STband SRb, where it is decoded. At STb, the primary signal is regenerated and linearly combined with the secondary signal by assigning fractions α and (1-α) of the available power to the primary and secondary signals respectively. This combined signal is then broadcasted by STbin the second transmission phase, and PR combines the signal it received in the two phases to decode for the primary signal. Theoretical and simulation results confirm that the outage performance for both primary and secondary systems are improved with a larger M by using the proposed scheme.

The concept of analog network coding (ANC) considers the concurrent transmission of signals over the wireless medium so that they intentionally interfere. Higher network throughput can be achieved with ANC when an intended transmission that a receiver desires to receive is made to interfere with a concurrent transmission of a signal known a priori at the receiver. In this paper, we present a cooperative protocol that exploits ANC. We consider a system with cooperative relaying of overlapped transmissions from two independent users. More specifically, we explore the case that network nodes may allow the transmitted signals to interfere both at the final destination node, and also at an intermediate node that acts subsequently as a relay. The relay employs a cooperative and multicast amplify-and-forward protocol so that the two destinations can use the interfered signals in order to recover the desired packet. We analyze this protocol in terms of the achieved rate and present an algorithm to recover signals from the overlapped transmissions. We study the impact of overlapping in signal transmissions on the throughput of the system. We show that even with considerable overlapping, the throughput under the proposed protocol is better in comparison to an orthogonal amplify-and-forward protocol.

In this paper, we propose a two-phase protocol based on cooperative relaying for a secondary system to achieve spectrum access along with a primary system. The primary system comprises of a transmitter-receiver pair PT-PR, and the secondary system comprises of M transmitters STi, i ∈ {1, 2,..., M} and a common receiver SR. The secondary transmitter STpwhich achieves the request target rate for the primary system is selected to serve as a decode-and-forward (DF) relay for the primary system. With the cooperation of STp, the primary system is able to tolerate interference lower than a certain threshold in the relaying phase, without degrading its outage performance. The secondary transmitter STs, which satisfies this interference constraint and provides the optimal outage performance for the secondary system, is then selected to access the spectrum band simultaneously when STpis relaying the primary signal. Theoretical and simulation results confirm the efficiency of the proposed spectrum sharing protocol, and we show that both primary and secondary systems are able to achieve better outage performance with increasing M.

We present a compressive wide-band spectrum sensing scheme for cognitive radios. The received analog signal at the cognitive radio sensing receiver is transformed in to a digital signal using an analog-to-information converter. The autocorrelation of this compressed signal is then used to reconstruct an estimate of the signal spectrum. We evaluate the performance of this scheme in terms of the mean squared error of the power spectrum density estimate and the probability of detecting signal occupancy.

We propose a two-phase protocol based on cooperative decode-and-forward relaying for a secondary system to achieve spectrum access along with a primary system. The primary and secondary systems comprise of a transmitter-receiver pair, PT-PR and ST-SR, respectively. In the first transmission phase, PT transmits the primary signal to PR, which is also received by ST and SR, where it is decoded. At ST, the primary signal is regenerated and linearly combined with the secondary signal by assigning fractions alpha and (1 - alpha) of the available power to the primary and secondary signals respectively. This combined signal is then broadcasted by ST in the second transmission phase. We show that as long as ST is located within a critical radius from PT, there exists a threshold value for alpha above which the outage probability of the primary system will be equal to or lower than the case without spectrum sharing. We also determine the outage probability achieved by the secondary system. Theoretical and simulation results confirm the efficiency of the proposed spectrum sharing scheme.

This paper analyzes the outage performance of cooperative protocols for the two-way relaying model in which a half-duplex relay assists in the bi-directional communication of two terminals. We first define the outage events and derive closed form results for the outage probabilities of conventional nonadaptive Amplify-and-Forward (AF) and Decode-and-Forward (DF) two-way relaying protocols.We then consider a simple adaptive protocol in the two-way relaying scenario, which switches between AF and DF depending on the decodability of the two bi-directional data streams at the relay. We also derive the outage probability for this adaptive scheme in closed form expressions, and our results show that it always outperforms the non-adaptive schemes. All the closed form results derived in this paper are applicable to arbitrary channel gains between terminals.

We present Nyquist pulse shaping conditions for two- dimensional (2-D) digital communication systems to be free from inter-symbol interference, for general regular sampling grids. We provide examples of 2-D pulse functions satisfying these Nyquist conditions. In particular, we show that a family of 2-D pulse functions that we construct as separable pulse functions from one-dimensional Nyquist-1 pulse functions obey the 2-D Nyquist criterion and moreover include the one with minimum support area in the frequency domain.

We consider relay-assisted communications from a source to a destination based on OFDM. The relay performs sub-carrier permutation by exploiting full channel state information (CSI), in addition to conventional amplify-and-forwarding. That is, the relay permutes the received signals over the subcarriers in the frequency domain, then amplifies and forwards the data to the destination. In this paper, we obtain optimal subcarrier permutations that minimize the uncoded BER for several relaying scenarios. From these insights, we develop a low-complexity ordering-based subcarrier permutation for the general relaying scenario. Simulations indicate that the proposed subcarrier permutation outperforms a random subcarrier permutation (where CSI is not exploited), and performs close to an optimal subcarrier permutation (which incurs a high complexity).

We consider a cognitive wireless relay system that operates on secondary spectrum sharing basis using spectrum pooling. A spectrum pool comprises of a set of available narrowband subchannels over which secondary users may communicate without causing harmful interference to primary users. In the proposed relay system, a source node transmits data symbols on an available spectrum pool to the relay node. At the relay, the received data symbols are amplified, permuted and forwarded to the destination node on an available spectrum pool. The problem of spectrum pool reassignment constitutes the determination of the permutation mapping at the relay node. Our goal is to maximize the ergodic capacity of the relay system, given knowledge of the average signal to noise ratios pertaining to the subchannels in the spectrum pools, by determining the optimum spectrum pool reassignment.

We consider the problem of detecting a primary user signal over a wireless channel by a cognitive radio with multiple antennas. We present a multiple antenna processing based energy detector. In this detection method, the multiple copies of the primary user signal at the antennas of the cognitive radio receiver are combined and input to an energy detector. We consider two multiple antenna processing methods and analyze their detection performance - the achieved probability of detection for a pre-specified probability of false alarm and given signal-to-noise ratio. We derive closed-form expressions for the probabilities for detection and false alarm for each of the processing schemes. Finally, we show through numerical results the potential improvement in primary user detection with multiple antenna processing based energy detection at the cognitive radio receiver.

In this paper we present an efficient bitloading algorithm that applies to both subband coding and multicarrier communication. The goal is to effect an optimal distribution of positive integer bit values among various subchannels to achieve a minimum distortion error variance for subband coding and transmitted power for multicarrier communications. Existing algorithms in the literature grow with the total number of bits that must be distributed. The novelty of our algorithm lies in the fact that its complexity is independent of the total number of bits to be allocated

We consider a low-complexity adaptive MIMO transmission approach for spatially correlated channels. The proposed scheme adaptively switches between different transmission modes depending on the changing channel conditions, as a means to enhance system capacity. Each mode is a combination of a transmission technique (i.e. statistical beamforming, double space-time transmit diversity and spatial multiplexing) and a modulation/coding scheme. We first motivate our adaptive algorithm by deriving new closed-form capacity expressions, and demonstrating significant information theoretic improvements over non-adaptive transmission. We then present a practical method to switch between different modes, based on the channel statistics. Our approach is shown to yield significant improvements in spectral efficiency for typical channel scenarios.

In this paper, we present an efficient bit loading algorithm for subband coding. The goal is to effect an optimal distribution of positive integer bit values among various subchannels to achieve a minimum distortion error variance. Existing algorithms in the literature grow with the total number of bits that must be distributed. The novelty of our algorithm lies in the fact that its complexity is independent of the total number of bits to be allocated.

This paper considers the design of biorthogonal DMT multicarrier transceiver systems supporting multiple services. The supported user services may have differing quality of service (QoS) requirements, quantified in this paper by bit rate and symbol error rate specifications. To reflect their service priorities, different users on the system can be potentially assigned different number of subchannels. Our goal is to minimize the transmitted power given the QoS specifications for the different users, subject to the knowledge of colored interference at the receiver input of the DMT system. In particular we find an optimum bit loading scheme that distributes the bit rate transmitted across the various subchannels belonging to the different users, and subject to this bit allocation, determine an optimum transceiver. This work differs from our prior work where the same number of subchannels were assigned to each user.

This paper considers the design of multicarrier transceiver systems like OFDM/DMT supporting multiple users. The supported users may have differing quality of service (QoS) requirements, quantified by their respective bit rate and symbol error rate specifications. Different users on the system can be potentially assigned different number of subchannels, to reflect their service priorities. Our goal is to minimize the transmitted power given the QoS specifications for the different users, subject to the knowledge of colored interference at the receiver input of the OFDM system. In particular we find an optimum bit loading scheme that distributed the bit rate transmitted across the various subchannels belonging to the different users, and subject to this bit allocation, determine an optimum transceiver.

We provide a complete characterization of discrete multitone transmission (DMT) systems that employ a cyclic prefix redundancy and that can be equalized by a bank of one-tap equalizers in each subchannel, for almost all values of channel parameters. We show that among all possible finite-impulse response transmitting and receiving filters of arbitrary order, such channel-resistant transmission requires 1) that the receive filters be matched to the transmit filters and 2) that to within a scaling and delay, the transmit and receive filters have inverse discrete Fourier transform and discrete Fourier transform (DFT) coefficients. Thus, we prove that, should cyclic prefix be applied, only trivial variants of traditional DFT-based DMT systems are channel resistant.

The paper considers discrete multitone (DMT) modulation for multiuser communications when multiple users are supported by the same system, a zero-padding redundancy is employed at the transmitter output, and linear redundancy removal is used at the channel output. These users may have differing quality of service (QoS) requirements, as quantified by bit rate and symbol-error rate specifications, and are each assigned an equal number of subchannels. Our goal is to minimize the transmitted power, given the QoS specifications and subject to the knowledge of the channel and the second-order statistics of the colored interference at the receiver input. In particular, we find an optimum bit-loading scheme that distributes the bit rate transmitted across the various subchannels belonging to each user, and, subject to this bit allocation, we determine the precise subchannels assigned to each user, the optimum transceiver characterized by the input/output block transforms, and the redundancy removal operation. A major conclusion is that even though the optimum bit-rate allocation differs from the single-user case, the optimum transceiver does not. Further, it is determined entirely by the channel and interference conditions, and is unaffected by the QoS requirements.

This paper considers the energy compaction problem for wide-sense cyclostationary (WSCS) signals. Periodic Nyquist-N filters and optimum compaction filters are defined and their properties examined. A procedure for designing compaction filters is given, and application to subband coding of WSCS signals is explored.

This paper considers discrete multitone (DMT) modulation for multiuser communications where different users are supported by the same system. These users may have differing quality of service (QoS) requirements, as quantified by their respective bit rate and symbol error rate specifications. Our goal is to minimize the transmitted power given the QoS specifications for the different users, subject to the knowledge of colored interference at the receiver input. In particular we find an optimum bit loading scheme that distributes the bit rate transmitted across the various subchannels belonging to the different users, and subject to this bit allocation, determine an optimum transceiver.

We consider the optimal orthonormal subband coding of zero mean wide sense cyclostationary signals (WSCS), with N-periodic second order statistics. An M-channel uniform filterbank, with N-periodic analysis and synthesis filters, is used as the subband coder. A static bit allocation scheme is used. An average variance condition is used to measure the output distortion. The conditions for maximizing the coding gain parallel those for the case when the signals are wide sense stationary (WSS) and the analysis and synthesis filters and the bit allocation time invariant.