This abstract describes the project funded by the IEEE SMCS on Transforming Educational Assets and Materials (TEAM) in Systems, Man, and Cybernetics. The project develops an open course on Cyber Physical Systems (CPS) Foundation and Design for Unmanned Aerial Vehicles (UAVs). The course will be available to the public and serve the need of researchers, students and professionals who are interested in conducting UAVs related research. The open course contains integrated modules on control, communication and networking, computing, and artificial intelligence (AI) to provide trainees a comprehensive knowledge needed for UAVs. The course is self-paced and contains quizzes in each module for help students assess the quality of learning and also allow course designers to evaluate the effectiveness of the course materials for continuous improvement. The open course promotes CPS which is a SMCS technical field. It will also attract students and professionals to the SMC community.

Federated learning (FL) is a promising machine learning paradigm because it allows distributed edge devices to collaboratively train a model without sharing their raw data. In practice, a major challenge to FL is that edge devices are heterogeneous, so slow devices may compromise the convergence of model training. To address such a challenge, several recent studies have suggested different solutions, in which a promising scheme is to utilize coded computing to facilitate the training of linear models. Nevertheless, the existing coded FL (CFL) scheme is limited by a fixed coding redundancy parameter, and a weight matrix used in the existing design may introduce unnecessary errors. In this paper, we tackle these issues and propose a novel framework, namely CFL-HC, to facilitate CFL in heterogeneous computing scenarios. In our framework, we consider a computing system consisting of a central server and multiple computing devices with original or coded datasets. Then we specify an expected number of input-output pairs that are used in one round. Within such a framework, we formulate an optimization problem to find the best deadline of each training round and the optimal size of the computing task allocated to each computing device. We then design a two-step optimization scheme to obtain the optimal solution. To evaluate the proposed framework, we develop a real CFL system using the message passing interface platform. Based on this system, we conduct numerical experiments, which demonstrate the advantages of the proposed framework, in terms of both accuracy and convergence speed.

Mobile ad hoc computing (MAHC), which allows mobile devices to directly share their computing resources, is a promising solution to address the growing demands for computing resources required by mobile devices. However, offloading a computation task from a mobile device to other mobile devices is a challenging task due to frequent topology changes and link failures because of node mobility, unstable and unknown communication environments, and the heterogeneous nature of these devices. To address these challenges, in this paper, we introduce a novel coded computation scheme based on multi-agent reinforcement learning (MARL), which has many promising features such as adaptability to network changes, high efficiency and robustness to uncertain system disturbances, consideration of node heterogeneity, and decentralized load allocation. Comprehensive simulation studies demonstrate that the proposed approach can outperform state-of-the-art distributed computing schemes.

For the sixth-generation (6G) communication, it is required to support the massive Internet of Things (IoT) devices with high data rate applications such as vision-based sensors. Unfortunately, the current sub-6-GHz band is already congested, and lower-band communication is hard to support the high data rate transmission. The millimeter-wave (mmWave)-based communication technology is a promising solution to support the high rate transmission in a new band. However, the high power consumption and hardware cost of the mmWave communication system violates the low-cost design principle of IoT devices, which is a heavy burden for the mmWave application on IoT. In this work, we propose the multiple IoT nodes access-based wireless beam modulation (WBM) technology for the mmWave transmission, where the WBM employs the over-the-air modulation to achieve the low-cost mmWave hardware design with hundreds of megabit per second transmission. To support multiple IoT nodes access, we first design a hyper grant-based and grant-free protocols to achieve the balance between robustness and low latency access. The multiple beam search method is proposed to accelerate the beam alignment process. The channel estimation of WBM is achieved by the pilot detection and beam estimation process, where an iterative pilot cancelation beam estimation method is proposed. According to the simulation and hardware implementation results, the WBM-based communication system can provide a much higher data rate transmission service than the current IoT-based communication systems, and much lower power consumption and hardware cost than the mmWave-based system.

For the symmetric private information retrieval problem with K messages and N servers, we show that the minimum (symmetric) upload cost is log2(⌈K1/N-1⌉) bits per server, i.e., the user must upload a q-ary symbol to each server where q is at least ⌈K1/N-1⌉.

In recent years, we have witnessed fast‐growing unmanned aerial systems (UAS) based applications. To better facilitate these applications, many efforts have been made to enhance the capability of UAS from various aspects, including communications, control and networking, and so on. Nevertheless, most of these studies neglect the computation aspect. Recently, the UAS‐enabled mobile edge computing (MEC) has attracted increasing research attention, which utilises UAS with onboard computing capability to provide on‐demand computing services for mobile users. However, existing research on UAS‐enabled MEC remains at the theory stage and how to design a UAS platform with advanced onboard computing capability has not been addressed. In this study, the authors aim to fill this research gap and design an open UAS‐based airborne computing platform with advanced onboard computing capability. This platform was designed from three aspects: hardware, software, and applications. In particular, feasible computing hardware to perform UAS onboard computing is first considered and a prototype is then designed. To enhance the flexibility and programmability of the platform, two key virtualisation techniques are then investigated. Finally, they test the performance of their prototype by executing real UAS onboard computing tasks, the results of which verify the feasibility and potentials of the proposed airborne computing platform.

In this paper, we study consensus in distributed sensor networks (DSN) with communication time delays. In particular, we focus on the DSN with multi-layer multi-group (MLMG) communication structures and show that consensus can be achieved even in the presence of arbitrarily large but bounded time-varying communication delays. Moreover, we explicitly characterize the final consensus value for the case where communication time delays are fixed.

Sphere Decoding provides a computationally efficient method of solving the maximum-likelihood detection problem in multiple-input multiple-output communication systems. However, the average computational complexity is normally fixed based on an error criteria before hand, meaning that regardless of if the channel conditions support the information rate or a much higher one, the overall complexity does not change. In this paper, we adapt a maximum a-posteriori probability based sphere decoder to support a converging dynamic complexity using the information rate of the system, the receiver signal-to-noise ratio and maximum theoretical capacity with negligible computational overhead.

In this paper, we propose an intelligent parking management system by using mobile edge computing (MEC). The proposed system contains vehicle detection, vehicle plate binding and information uploading three processes, which are performed by magnetic sensor edge and gateway edge. Hence, it is critical to design an efficient communication and computing allocation strategy to minimize the power consumption for the power limited device. In this work, we first map the parking management system to a mobile edge computing model and covert the offloading strategy to an optimization problem. By solving the optimization problem, the system efficiency is improved significantly. According to the results, the MEC-based optimized solution can most save 58.52% power dissipation, 99.20% transmission cost or 62.48% latency compared with the cloud computing based method.

In this paper, we study the design and development of airborne WiFi networks through directional antennae. Specifically, we conduct an experimental study to investigate the feasibility of transmitting WiFi signals over two unmanned aerial vehicles (UAVs). WiFi has become the de facto configuration for most communication devices, from personal smartphones to industrial instruments. The integration of WiFi signals with airborne networks will enable a fast deployment of WiFi infrastructures, which provide real-time communication for disaster scenarios where a communication infrastructure does not exist. One unique feature of this work is the use of directional antennae for long range WiFi signal transmission. Directional antennae are considered because they not only boost the signal strength, but also have the potential to reduce interference with other WiFi channels. However, the performance of communication using directional antennae depends highly on the alignment of facing directions, which requires online control in response to the movement of UAVs. In our experimental study, we develop two hexacopters that are equipped with NanoStations. They maintain correct facing and thus connectivity through an automatic mechanical heading control. Field tests are conducted to understand how distance impacts the WiFi signal throughput. The experimental study suggests the promising use of directional antennas for WiFi aerial communication, and also discloses challenges to enable robust WiFi airborne networks.

Traditional consensus approaches involve a high communication cost because every node in the network will participate the information exchange with its neighbors. In this paper, we propose a new distributed average consensus with consideration of the network topology. More specifically, the information exchange only involves the connected dominating set (CDS) of the original graph. The nodes not in the CDS will only passively update their states according to the information received from the nodes in CDS. With the introducing of CDS, the overall power consumption will be reduced significantly because of less nodes transmitting signals. CDS determination algorithm has fixed number of procedures, which facilitates the estimation of the additional power consumption for the distributed wireless sensor networks. Numerical results show that the number of nodes involved in the consensus is reduced by half. It is also shown that the new consensus schemes over CDS not only achieve the similar performance as that over the original graph, but also demonstrate potential of faster convergence.

In this paper, we study properties of distributed consensus in layered sensor networks of the multi-layer multi-group (MLMG) structure. We show that properly designed MLMG networks maintain decentralized communication, whereas show the advantage of centralized structures. In particular, they require less number of transmissions required to reach consensus. This feature is critical for efficient distributed computing in large-scale sensor network applications. For typical classes of MLMG networks, we mathematically characterize the reduced number of transmissions compared to equivalent egalitarian decentralized structures of the same consensus dynamics. This explicit characterization based on simple graphical characteristics of MLMG structures permits an efficient design of large-scale network structures to meet desired performance requirements. In addition, we characterize the asymptotic and transient properties of consensus in MLMG networks of limited channel rates, using the probabilistic quantization schemes.

This paper presents a two-phase cooperative communication strategy and an optimal power allocation strategy to transmit sensor observations to a fusion center in a large-scale sensor network. Outage probability is used to evaluate the performance of the proposed system. Simulation results demonstrate that: 1) when signal-to-noise ratio is low, the performance of the proposed system is better than that of the multiple-input and multiple-output system over uncorrelated slow fading Rayleigh channels; 2) given the transmission rate and the total transmission SNR, there exists an optimal power allocation that minimizes the outage probability; 3) on correlated slow fading Rayleigh channels, channel correlation will degrade the system performance in linear proportion to the correlation level.

A recent study shows that the throughput of wireless networks can be further improved via combining intra-and intersession network coding (I2NC). The main idea of I2NC is to protect against packet loss by introducing additional redundancy via intra-session coding. However, the amount of redundancy depends on the quality of overhearing links. The poorer an overhearing link is, the less fraction of information is overheard, which results in a potential increase of redundancy needed. While lower transmission rate promises better link quality, it also means lower throughput. Motivated by this, we study the impact of transmission rates on network throughput and formulate the rate selection into an optimization problem. Also, we investigate the flow partition for the inter-session coding. In other words, we consider which sessions would be grouped together through network coding to improve the throughput. We aim to design a joint rate and partition selection in a wireless star network, so as to maximize the network throughput. We prove that finding the optimal joint rate selection and flow partition is NP-hard. An efficient heuristic algorithm is proposed for the networks with heterogenous rates and sessions that can be grouped together for the inter-session network coding. Simulation results show that the proposed scheme achieves throughput gains of up to 185% as compared to what is gained with a rate-unaware I2NC scheme.

In this paper, we study the transmission strategy in a two-way relay channel. In particular, we propose a new class of logM1(M2)-MA (multi-access) block relay protocols where an M1-ary modulation is used in the MA phase, and an M2-ary in the broadcast phase. Lower-order (e.g., BPSK) and higher-order (e.g., 16-QAM, 32-PSK) modulations are used respectively for the multi-access phase and the broadcast phase, in contrast to the conventional method of using the same modulation type (of either higher or lower order) throughout. To achieve this, the relay buffers the received symbols from consecutive multi-access phases and performs signal combining in conjunction with the decode-and-forward protocol. We derive the theoretical performance bounds for the Rayleigh fading channels and closed forms for the AWGN channels. Numerical results confirm the advantages of the proposed scheme with an improved throughput in lower signal-to-noise ratio range.

In the paper, an improved link adaptation scheme is proposed for the WiMedia MB-OFDM UWB system, in which quality of service (QoS) support is provided. The proposed scheme consists of three functional blocks: link quality indicator (LQI) calculator, frame error rate (FER) estimator, and transmitter (TX) parameter selector. Instead of using the average receive SNR (ASNR) as LQI, a new LQI metric is defined based on a union bound analysis to capture the effects of both path loss and frequency selectivity of an instantaneous UWB channel. How to calculate LQI for each rate mode is investigated by analyzing the distribution of soft bit information. With the calculated LQI, the FER performance of each rate mode can be accurately estimated with a look-up table method, which is suitable for practical implementation. Using the estimated FERs, TX parameter selector can optimize TX rate mode to improve the communication throughput under QoS constraints. It is shown the proposed scheme can significantly improve the throughput while maintaining the required QoS compared to conventional ASNR based link adaptation schemes.

In this paper, we investigate the throughput capacity of large-scale wireless networks, in which three network-assisted coding schemes are considered: (1) multi-point-to-point coding (MPPC); (2) MPPC based network coding (NC); and (3) MPPC based physical-layer network coding (PLNC). This study is based on the generalized physical model, in which the transmission rate depends on the signal to noise and interference ratio (SINR). Such a model has not been used to analyze the behaviors of large-scale wireless networks with the aforementioned coding schemes. To understand the capacity gains of these schemes, we develop constructive lower bounds for one-dimensional (1D) and two-dimensional (2D) networks with size factor w, in which we construct novel wireless highway systems. This study shows that, compared to point-to-point coding (PPC), MPPC can improve the scaling law of network capacity when w exceeds a certain scale. In addition, this study reveals that MPPC based NC and PLNC can improve the capacity by constant factors. Specifically, NC can always obtain a gain of 2 in both 1D and 2D networks. On the other hand, the gain of PLNC can be larger than 2 in 1D networks, and can be up to 2 in 2D networks, depending on w, transmission power, noise, and path-loss of propagation.

In conventional communication systems, error correction is carried out at the physical layer while data security is performed performed at an upper layer. As a result, these steps are done as separate steps. As opposed to this conventional system, we present a scheme that combines error correction and data security as one unit so that both encryption and encoding could be carried out at the physical layer. Hence, in this paper, we present an Error Correction Based Cipher (ECBC) that combines error correction and encryption/decryption in a single step. Encrypting and encoding or decoding and decrypting in a single step will lead to a faster and more efficient implementation. One of the challenges of using previous joint schemes in a communications channel is that there is a tradeoff between data reliability and security. However in ECBC, there is no trade off between reliability and security. Errors introduced at the transmitter for randomization are removed at the receiver. Hence ECBC can utilize its full capacity to correct channel errors. We show the result of randomization test on ECBC and its security against conventional attacks. We also present the result of the FPGA implementation of the ECBC encryption.

Due to the broadcast nature of wireless channels, the two-way system can be eavesdropped on when a confidential message is transmitted, which is one of the motivations of this paper. While most of existing work focuses on the discussion of secrecy rate with information theoretical approach, this paper discusses the probability of successful detection for the system experiencing exponential path loss. By investigating the symbol-error-rate at the legitimate nodes and eavesdropper, we find the optimal power allocation among the two-way communication systems. We also investigate the impact factor on the secrecy capacity including the location of eavesdropper, path loss exponent, and decoding strategies.

In the past few years, the capacity of multicast traffic in large-scale random wireless networks has attracted considerable attention because of the fundamental importance of network capacity and the multicast applications. However, there are still significant gaps between the upper bounds and the constructive lower bounds. In this paper, we develop a novel percolation highway system with which the constructive lower bounds can arbitrarily approach the upper bounds.

While original network coding is proposed over the data link layer, recent work suggests that it can also be implemented on the physical layer. In fact it is more natural for wireless networks because of its omnidirectional transmission. In this paper, we investigate the symbol-error-rate (SER) for binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK), but the approaches can be generalized to other constellation schemes. The closed-form SER results are derived for physical layer network coding over AWGN channels. The theoretical analysis is also validated by numerical simulation.

In this paper, we discuss the channel coding design to support the two-phase physical-layer network coding (PLNC) under a typical three-node network coding scenario. We prove, even two source nodes could use different channel codes, the error correction capability at the relay node is bounded by that of the weaker one, i.e. the code with a smaller minimum distance. Therefore, we propose to use the same channel code at two source nodes, which can also provide potential to simplify the joint PLNC-channel decoding procedure (PLNC-DEC) at the relay node. Moreover, we propose a channel coding scheme based on linear convolutional codes to relax the strict synchronization requirement, which is difficult to achieve in some real applications. The proposed coding scheme is robust to the synchronization error between two source nodes and enables the relay node to perform the PLNC-DEC with only one Viterbi decoding procedure. Compared to the three-phase network coding scheme, the proposed scheme reduces the decoding/demodulation complexity of the relay node almost by half and achieves significant throughput gain.

Physical-layer network coding (PLNC) is a novel wireless communication technology, in which multiple transmitters can send signals on the same channel to the same receiver at the same time. Our previous studies have revealed that PLNC can substantially improve the throughput performance of the whole network. In this paper, we address the security performance of PLNC. In particular, we investigate the symbol error performance of a potential eavesdropper in the PLNC system. Extensive simulation studies show that PLNC can provide security means against passive eavesdroppers.

Throughput capacity of a random wireless network has been studied extensively in the literature. Most existing studies were based on the assumption that each transmission involves only one transmitter in order to avoid interference. However, recent studies on physical-layer network coding (PLNC) have shown that such an assumption can be relaxed to improve throughput performance of a wireless network. In PLNC, signals from different senders can be transmitted to the same receiver in the same channel simultaneously. In this paper, we investigate the impact of PLNC on throughput capacity of a random wireless network. Our study reveals that, although PLNC scheme does not change the scaling law, it can improve throughput capacity by a fixed factor. Specifically, for a one-dimensional network, we observe that PLNC can eliminate the effect of interference in some scenarios. A tighter capacity bound is derived for a two-dimensional network. In addition, we also show achievable lower bounds for random wireless networks with network coding and PLNC.

Differential space-time modulation (DSTM) has been recently proposed by Hughes, and Hochwald and Sweldens when the channel information is not known at the receiver, where the demodulation is in fact the same as the coherent demodulation of space-time block coding by replacing the channel matrix with the previously received signal matrix. On the other hand, the DSTM also needs a recursive memory of a matrix block at the encoder and therefore provides a trellis structure when the channel information is known at the receiver, which is the interest of this paper. This recursive structure of the DSTM has been adopted lately by Schlegel and Grant in joint with a conventional binary code and joint iterative decoding/demodulation with a superior performance. The number of states of the trellis from the recursive structure depends on both the memory size, which is fixed in this case, and the unitary space-time code (USTC). When a USTC for the DSTM forms a group, the number of states is the same as the size of the USTC, otherwise the number of the states is the size of the semi-group generated by the USTC from all the multiplications of the matrices in the USTC. It is well known in the conventional convolutional coding (CC) or the trellis coded modulation (TCM), the free (Hamming or Euclidean) distance (or the performance) increases when the number of states increases by adding more memory with a properly designed CC or TCM. In this paper, we systematically study and design the USTC/DSTM for the recursive space-time trellis modulation and show that the diversity product increases when the number of states increases, which is not because of the memory size but because of the different USTC designs that generate different sizes of semi-groups. We propose a new USTC design criterion to ensure that the trellis structure improves the diversity product over the USTC as a block code. Based on the new criterion, we propose a new class of USTC design for an arbitrary number of transmit antennas that has an analytical diversity product formula for two transmit antennas. We then follow Schlegel and Grant's approach for joint encoding and iterative decoding of a binary coded DSTM (turbo space-time coding) and numerically show that our new USTC designs for the recursive space-time trellis modulation outperforms the group USTC used by Schlegel and Grant.

In this paper, we address the topology control issue for future wireless mesh networks (WMNs). In particular, we propose a novel topology control scheme that attempts to maximize the overall throughput in the network with random unicast traffic demands. The main idea of the scheme is to establish multiple semi-permanent wireless highways, each of which can convey the traffic for nodes along the highways. To evaluate the performance of the proposed scheme, we conduct theoretical analysis, which demonstrates that viable solutions for highways do exist with high probability. The theoretical analysis also proves the optimality. Within the new topology control framework, we demonstrate that advanced technologies, including network coding and physical- layer network coding (PLNC), can be applied to substantially improve the throughput capacity of the network.

Since the pioneer work by Gupta and Kumar, the throughput capacity of random wireless networks has been studied extensively in the literature. Nevertheless, most existing studies are based on the assumption that each node can receive at most one transmission at a time. However, several recent studies have shown that such a constraint can be relaxed. Particularly, with physical-layer network coding, one node can receive more than one transmission from different transmitters simultaneously. In this paper, we investigate the impact of physical-layer network coding on the throughput capacity of random wireless networks. Our analysis show that the physical-layer network coding scheme can improve the throughput capacity but cannot change the scaling law. Specifically, for one-dimensional random wireless network, our analysis provides the capacity of network with physical-layer network coding. For two-dimensional random wireless networks, we derive tighter capacity bounds for existing transmission schemes, as well as the bounds for physical-layer network coding.

In this paper, we propose an asynchronous cooperative scheme with a decentralized relay strategy. The single carrier block transmission (SCBT) technique is used to mitigate the effect of relay synchronization error. By utilizing an orthogonal space-time code with cyclic delay transmission, cooperative diversity can be achieved. Specifically, each relay node transmits a combination of all rows of the deployed space-time code and each row is randomly cyclic-shifted and scaled. The scale factor and the cyclic shift of each row at each relay node are generated locally. The random cyclic shift operation renders a good scalability to the number of relay nodes (or the network node density) while the random scale operation improves the performance greatly. Moreover, the proposed scheme is a decentralized scheme in the sense that it is independent of the number of relay nodes and does not need any side information exchange among cooperative nodes. The proposed scheme can inherently support both the amplify-and-forward (AF) and decode-and-forward (DF) cooperative mechanisms.

In wireless ad-hoc networks, a major challenge is how to provide robust and efficient communication. To achieve this goal, cooperative communication and network coding have been proven to be effective. In the literature, most existing studies focus on the performance of the two schemes separately. In our study, we will investigate the performance of system that combines them tightly together. In particular, we will propose a unified two-way traffic model that can characterize the features of both of them. Based on this model, we develop a new cooperative network coding scheme to further improve the system throughput. Both decode-and-forward and amplify-and-forward techniques are discussed for the two-way traffic model. Numerical results show that the new scheme can significantly improve the performance over traditional schemes.

In this paper, we propose a novel retransmission scheme that can substantially increase the throughput of wireless local area networks (WLANs). The main idea of the scheme is to enable cooperative communication in the medium access control (MAC) layer such that one node can retransmit messages for its neighboring nodes if the delivery of those messages failed previously due to transmission error. In addition, we also redesign the transmission and acknowledgement policy of the existing IEEE 802.11 protocol in that 1) an upper layer packet will be partitioned into blocks, and 2) the receiver of a message can acknowledge individual blocks through negative acknowledgement (NACK). To evaluate the performance of the proposed scheme, we conduct extensive simulation study under various conditions, such as number of nodes, size of packet, and bit error rate. Simulation results show that, the proposed scheme can significantly increase the throughput performance of WLANs under these conditions, and an optimal block size can lead to the highest throughput in each specific scenario.

In this paper, we study the design of future wireless ad hoc networks. Particularly, we consider that the future wireless ad hoc networks shall be able to efficiently provide connectivity and support a variety of quality of service requirements, such as bandwidth and delay requirements. To address these issues, we propose a novel framework for the design of future wireless ad hoc networks. The key idea of this framework is to establish an overlay hypernetwork, which consists of multiple hyperchannels, each of which can provide connectivity for multiple nodes in the hyperchannel. By comparison, a typical tunnel in existing overlay network schemes can only provide connectivity for two end nodes. Within the framework, we also develop advanced network coding design that can further improve the performance of the network in terms of throughput and delay.

Conventional cooperative communication schemes suffer from asynchronous relay transmissions of distributed relay nodes, which can destroy the deliberately designed code structure and result in severe diversity gain loss. In the paper, we propose a cooperative scheme based on the single carrier block transmission (SCBT) technique that is robust to asynchronous relay transmissions. By introducing the orthogonal structure in the frequency domain and deploying the frequency domain equalizer (FDE), cooperative diversity can be achieved. Moreover, a novel random cyclic delay diversity (CDD) technique is developed so that a higher cooperative diversity gain can be achieved when more than 2 relay nodes are available. The proposed scheme is independent of the number of relay nodes and does not need to exchange any side information among nodes. The proposed scheme can inherently support both the amplify-and-forward (AF) and decode-and-forward (DF) cooperative mechanisms.

In this paper, we propose a novel scheme to improve the performance of wireless local area networks (WLANs) in error-prone environment. The key idea of the scheme is to partition a frame into several blocks, and then to retransmit only the blocks that encountered errors in the previous transmission. To evaluate the performance of the scheme, we also develop an analytical model to analyze the saturated throughput performance. Extensive simulation and analysis results show that, 1) the proposed scheme can significantly improve the throughput performance of WLANs in error-prone conditions; 2) an optimum block size can lead to the maximum saturated throughput; 3) with an appropriate block size, the throughput can increase with the increase of the size of a frame, even in error-prone environment; and 4) the analytical results are highly accurate.

Differential space-time modulation (DSTM) has been recently proposed by Hughes, and Hochwald and Sweldens when the channel information is not known at the receiver. On the other hand, the DSTM also needs a recursive memory of a matrix block at the encoder and therefore provides a trellis structure when the channel information is known at the receiver, which is the interest of this paper. This recursive structure of the DSTM has been adopted lately by Schlegel and Grant as an inner trellis code concatenated with an outer binary code to achieve turbo gain. The number of states of the trellis from the recursive structure depends on both the memory size, which is fixed in this case, and the unitary space-time code (USTC). In this paper, we propose a new USTC design criterion to ensure that the trellis structure improves the diversity product over the USTC as a block code. Based on the new criterion, we propose a new class of USTC design for an arbitrary number of transmit antennas that has an analytical diversity product formula for two transmit antennas. We then follow Schlegel and Grant's approach for joint encoding and iterative decoding of a binary coded DSTM (turbo space-time coding) and numerically show that our new USTC designs for the recursive space-time trellis modulation outperforms the group USTC used by Schlegel and Grant.

In this correspondence, we present systematic and closed-form constructions of complex orthogonal space-time block codes from complex orthogonal designs of rates (k+1)/2k for 2k-1 or 2k transmit antennas for any positive integer k.

The audio/visual mapping problem of speech-driven facial animation has intrigued researchers for years. Recent research efforts have demonstrated that hidden Markov model (HMM) techniques, which have been applied successfully to the problem of speech recognition, could achieve a similar level of success in audio/visual mapping problems. A number of HMM-based methods have been proposed and shown to be effective by the respective designers, but it is yet unclear how these techniques compare to each other on a common test bed. In this paper, we quantitatively compare three recently proposed cross-modal HMM methods, namely the remapping HMM (R-HMM), the least-mean-squared HMM (LMS-HMM), and HMM inversion (HMMI). The objective of our comparison is not only to highlight the merits and demerits of different mapping designs, but also to study the optimality of the acoustic representation and HMM structure for the purpose of speech-driven facial animation. This paper presents a brief overview of these models, followed by an analysis of their mapping capabilities on a synthetic dataset. An empirical comparison on an experimental audio-visual dataset consisting of 75 TIMIT sentences is finally presented. Our results show that HMMI provides the best performance, both on synthetic and experimental audio-visual data.

This paper presents a closed form designs of complex orthogonal space-time block codes of rates (k + I)/(2k) for 2k-1 or 2k transmit antennas