Cooperative Detection and Network Coding in Wireless Networks

In cooperative communication systems, multiple terminals in wireless networks share their antennas and resources for information exchange and processing. Recently, cooperative communications have been shown to achieve significant performance improvements in terms of transmission reliability, coverage area extension, and network throughput, with respect to existing classical communication systems. This dissertation is focused on two important applications of cooperative communications, namely: (i) cooperative distributed detection in wireless sensor networks, and (ii) many-to-many communications via cooperative space-time network coding. The first application of cooperative communications presented in this dissertation is concerned with the analysis and modeling of the deployment of cooperative relay nodes in wireless sensor networks. Particularly, in dense wireless sensor networks, sensor nodes continuously observe and collect measurements of a physical phenomenon. Such observations can be highly correlated, depending on the spatial separation between the sensor nodes as well as how the physical properties of the phenomenon are evolving over time. This unique characteristic of wireless sensor networks can be effectively exploited with cooperative communications and relays deployment such that the distributed detection performance is significantly improved as well as the energy efficiency. In particular, this dissertation studies the Amplify-and-Forward (AF) relays deployment as a function of the correlation of the observations and analyzes the achievable spatial diversity gains as compared with the classical wireless sensor networks. Moreover, it is demonstrated that the gains of cooperation can be further leveraged to alleviate bandwidth utilization inefficiencies in current sensor networks. Specifically, the deployment of cognitive AF cooperative relays to exploit empty/under-utilized time-slots and the resulting energy savings are studied, quantified and compared. The multiple terminal communication and information exchange form the second application of cooperative communications in this dissertation. Specifically, the novel concept of Space-Time-Network Coding (STNC) that is concerned with formulation of the many-to-many cooperative communications over Decode-and-Forward (DF) nodes is studied and analyzed. Moreover, the exact theoretical analysis as well as upper-bounds on the network symbol error rate performance are derived. In addition, the tradeoff between the number of communicating nodes and the timing synchronization errors is analyzed and provided as a network design guideline. With STNC, it is illustrated that cooperative diversity gains are fully exploited per node and significant performance improvements are achieved. It is concluded that the STNC scheme serves as a potential many-to-many cooperative communications scheme and that its scope goes much further beyond the generic source-relay-destination communications

Optimisation in behavioural synthesis using hierarchical expansion: module ripping

During behavioural synthesis, an abstract functional description of a system is mapped automatically onto a physical structure. In a competitive setting, this mapping will be highly optimised - the dataflow is re-arranged, units and registers are multiplexed and so on - to deliver a final structure that meets some overall user supplied specification. Ultimately, however, the physical functional units are drawn from some predefined (human designed) library - these may be thought of as the leaf-level modules in the design hierarchy. Design re-use and increasing sophistication of module libraries inevitably leads to leaf modules becoming larger and more complex. As these modules are, by definition, atomic, a synthesis system is unable to capitalise on any internal similarities the leaf modules may possess. This paper describes the design, construction and effects of using a hierarchically defined module library. The set of leaf-level modules made available to the synthesis environment is conventional - add, subtract, multiply and so on - but the optimiser is capable of ?ripping apart? these modules to manipulate their inner structures. Two advantages accrue from this technique: (1) it is possible to optimise behavioural designs far more effectively, with up to a 65% reduction in area, and a 46% reduction in delay reported, and (2) it is possible to build library modules that have tightly controllable internal timing relationships. This is essential when designing systems that communicate externally via low-level protocols, but behavioural synthesis, by its very nature, usually distorts timing information. Using this technique, it is possible to create ?islands of fixed timing? embedded in the synthesised design

A Dual-Function Massive MIMO Uplink OFDM Communication and Radar Architecture

This paper proposes a joint uplink massive multiple-input-multiple-output (MIMO) communication and orthogonal frequency-division multiplexing (OFDM) radar sensing architecture. Specifically, uplink communication and short-range radar sensing are considered, where the user equipments (UEs) transmit data to the base-station (BS), which simultaneously receives radar returns from the targets over the same subcarriers. Hence, the signals received at each BS antenna include radar returns and communication signals to be processed for extracting the sensing and communication data. The separation and detection of such signals are achieved by utilizing the channel diversity between the UEs and the targets. To this end, the UEs' signals are first detected and demodulated, and then subtracted from the received signal to acquire the radar returns. Symbol-based radar processing is then employed, as it provides substantial processing gains, and its detection performance is independent of the transmitted radar waveform. Furthermore, self-interference - due to the simultaneous operation of transmit and receive antennas - is taken into account. The communication rate and normalized error of the radar-target channel estimation are mathematically analyzed, and the trade-off between the achievable rate and radar detection performance is demonstrated in terms of the output power of the communication and radar sub-systems and the signal-to-noise ratio

A Dual-Functional Massive MIMO OFDM Communication and Radar Transmitter Architecture

In this study, a dual-functional radar and communication (RadCom) system architecture is proposed for application at base-stations (BSs), or access points (APs), for simultaneously communicating with multiple user equipments (UEs) and sensing the environment. Specifically, massive multiple-input multiple-output (mMIMO) communication and orthogonal frequency-division multiplexing (OFDM)-based MIMO radar are considered with the objective to jointly utilize channel diversity and interference. The BS consists of a mMIMO antenna array, and radar transmit and receive antennas. Employing OFDM waveforms for the radar allows the BS to perform channel state information (CSI) estimation for the mMIMO and radar antennas simultaneously. The acquired CSI is then exploited to predict the radar signals received by the UEs. While the radar transmits an OFDM waveform for detecting possible targets in range, the communication system beamforms to the UEs by taking into account the predicted radar interference. To further enhance the capacity of the communication system, an optimum radar waveform is designed. Moreover, the network capacity is mathematically analyzed and verified by simulations. The results show that the proposed RadCom can achieve higher capacity than conventional mMIMO systems by utilizing the radar interference while simultaneously detecting targets

Optimized Precoders for Vehicular Massive MIMO RadCom Systems

This paper proposes optimized precoders for dual-functional radar and communication (RadCom) systems to maximize the sum-rate (SR) while satisfying radar target detection and user data rate constraints towards 6G networks. For this purpose, a RadCom precoder scheme that exploits radar interference is utilized with massive multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. Firstly, the communication capacity and radar detection performance metrics are analytically derived. Then, optimum precoders that utilize these analytical expressions are designed via convex optimization to maximize the SR with modest computational complexity. The analytical results are also verified by simulations. The results show that the optimized precoder can substantially enhance the SR compared to the benchmark methods

A Dual-Functional Massive MIMO OFDM Communication and Radar Transmitter Architecture

In this study, a dual-functional radar and communication (RadCom) system architecture is proposed for application at base-stations (BSs), or access points (APs), for simultaneously communicating with multiple user equipments (UEs) and sensing the environment. Specifically, massive multiple-input multiple-output (mMIMO) communication and orthogonal frequency-division multiplexing (OFDM)-based MIMO radar are considered with the objective to jointly utilize channel diversity and interference. The BS consists of a mMIMO antenna array, and radar transmit and receive antennas. Employing OFDM waveforms for the radar allows the BS to perform channel state information (CSI) estimation for the mMIMO and radar antennas simultaneously. The acquired CSI is then exploited to predict the radar signals received by the UEs. While the radar transmits an OFDM waveform for detecting possible targets in range, the communication system beamforms to the UEs by taking into account the predicted radar interference. To further enhance the capacity of the communication system, an optimum radar waveform is designed. Moreover, the network capacity is mathematically analyzed and verified by simulations. The results show that the proposed RadCom can achieve higher capacity than conventional mMIMO systems by utilizing the radar interference while simultaneously detecting targets

Optimized Precoders for Massive MIMO OFDM Dual Radar-Communication Systems

This paper considers the optimization of a dual-functional radar and communication (RadCom) system with the objective is to maximize its sum-rate (SR) and energy-efficiency (EE) while satisfying certain radar target detection and data rate per user requirements. To this end, novel RadCom precoder schemes that can exploit downlink radar interference are devised for massive multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. First, the communication capacity and radar detection performance metrics of these schemes are analytically evaluated. Then, using the derived results, optimum beam power allocation schemes are deduced to maximize SR and EE with modest computational complexity. The validity of the analytical results is confirmed via matching computer simulations. It is also shown that, compared to benchmark techniques, the devised precoders can achieve substantial improvements in terms of both SR and EE

An Algorithm for Strong Stability in the Student-Project Allocation Problem With Ties

We study a variant of the Student-Project Allocation problem with lecturer preferences over Students where ties are allowed in the preference lists of students and lecturers (spa-st). We investigate the concept of strong stability in this context. Informally, a matching is strongly stable if there is no student and lecturer l such that if they decide to form a private arrangement outside of the matching via one of l’s proposed projects, then neither party would be worse off and at least one of them would strictly improve. We describe the first polynomial-time algorithm to find a strongly stable matching or report that no such matching exists, given an instance of spa-st. Our algorithm runs in O(m2) time, where m is the total length of the students’ preference lists

Information society in Palestine : the human capital dimension

Includes CD-ROM in back pocke

Intrathecal treatment of neoplastic meningitis due to breast cancer with a slow-release formulation of cytarabine

DepoCyte is a slow-release formulation of cytarabine designed for intrathecal administration. The goal of this multi-centre cohort study was to determine the safety and efficacy of DepoCyte for the intrathecal treatment of neoplastic meningitis due to breast cancer. DepoCyte 50 mg was injected once every 2 weeks for one month of induction therapy; responding patients were treated with an additional 3 months of consolidation therapy. All patients had metastatic breast cancer and a positive CSF cytology or neurologic findings characteristic of neoplastic meningitis. The median number of DepoCyte doses was 3, and 85% of patients completed the planned 1 month induction. Median follow up is currently 19 months. The primary endpoint was response, defined as conversion of the CSF cytology from positive to negative at all sites known to be positive, and the absence of neurologic progression at the time the cytologic conversion was documented. The response rate among the 43 evaluable patients was 28% (CI 95%: 14–41%); the intent-to-treat response rate was 21% (CI 95%: 12–34%). Median time to neurologic progression was 49 days (range 1–515(+)); median survival was 88 days (range 1–515(+)), and 1 year survival is projected to be 19%. The major adverse events were headache and arachnoiditis. When drug-related, these were largely of low grade, transient and reversible. Headache occurred on 11% of cycles; 90% were grade 1 or 2. Arachnoiditis occurred on 19% of cycles; 88% were grade 1 or 2. DepoCyte demonstrated activity in neoplastic meningitis due to breast cancer that is comparable to results reported with conventional intrathecal agents. However, this activity was achieved with one fourth as many intrathecal injections as typically required in conventional therapy. The every 2 week dose schedule is a major advantage for both patients and physicians. © 2001 Cancer Research Campaign http://www.bjcancer.co