Hsiao-feng Francis Lu

Bio: Hsiao-feng Francis Lu is an academic researcher from National Chiao Tung University. The author has contributed to research in topics: Decoding methods & MIMO. The author has an hindex of 1, co-authored 3 publications receiving 6 citations.

Selection and Rate-Adaptation Schemes for MIMO Multiple-Access Channels With Low-Rate Channel Feedback

Abstract: In this paper, two selection schemes are proposed for coded transmission over multiple-input multiple-output (MIMO) multiple-access channels (MAC) to yield a much higher diversity-multiplexing gain tradeoff (DMT) performance. These schemes require a channel feedback, but at an extremely low rate. The first scheme is based on user selection and can be easily implemented in the existing MIMO-MAC systems. Upper bounds on the minimal computational complexity required by sphere decoders to decode DMT-optimal codes for this scheme as well as for MIMO MAC without feedback are given. It is shown that this scheme can offer both a much larger DMT and an exponential reduction on decoding complexity, compared with the latter. The second scheme selects jointly the users and their transmit antennas. It requires an additional design of rate assignments for performance optimization. A very general framework on the design of optimal rate assignments is thus provided. It is shown that this scheme can yield DMT performances far superior to the optimal MIMO-MAC DMT without channel feedback. The simulation results confirm that in some cases, this scheme can provide an astonishing SNR gain of 14.64 dB at outage probability $10^{-6}$ compared with the optimal MIMO-MAC coding schemes without feedback.

Optimal Distributed Codes for Feedback-Aided Cooperative Relay Networks

Abstract: A novel transmission scheme for cooperative relay networks is presented in this paper. The proposed scheme is based on the non-orthogonal selection decode-and-forward protocol with an additional assumption of having a low rate feedback channel from the destination to relays. Benefited from the feedback information, an optimal distributed code that has an extremely short delay equal to four is constructed, and the same code is applicable to networks with the arbitrary number of relays to yield optimal cooperative diversity. The proposed code is sphere decodable with a decoding complexity again independent of the number of relays in high SNR regime. In particular, when operating at multiplexing gain ≥(1/2), the lattice decoder at the destination has a zero complexity exponent, meaning a constant decoding complexity and independent of transmission rate. Analyses for the decoding complexity of other existing diversity-optimal distributed codes are also provided. It is shown that these codes have a linear growth in delay and an exponential growth in decoding complexity as the number of relays increases.

An Error Event Sensitive Tradeoff Between Rate and Coding Gain in MIMO MAC

Abstract: This paper investigates the design of codes for multiple-input multiple-output (MIMO) multiple access channel (MAC). If a joint maximum-likelihood decoding is to be performed at the receiver, then every MIMO-MAC code can be regarded as a single-user code, where the minimum determinant criterion proposed by Tarokh et al. is useful for designing such codes and for upper bounding the maximum pairwise error probability (PEP), whenever the codes are of finite rate and operate in finite signal-to-noise ratio range. Unlike the case of single-user codes where the minimum determinant can be lower bounded by a fixed constant as code-rate grows, it was proved by Lahtonen et al. that the minimum determinant of MIMO-MAC codes decays as a function of the rates. This decay phenomenon is further investigated in this paper, and upper bounds for the decays of minimum determinant corresponding to each error event are provided. Lower bounds for the optimal decay are established and are based on an explicit construction of codes using algebraic number theory and Diophantine approximation. For some error profiles, the constructed codes are shown to meet the aforementioned upper bounds, hence they are optimal finite-rate codes in terms of PEPs associated with such error events. An asymptotic diversity-multiplexing gain tradeoff (DMT) analysis of the proposed codes is also given. It is shown that these codes are DMT optimal when the values of multiplexing gains are small.

Approximately Universal Codes over Slow Fading Channels

Abstract: Performance of reliable communication over a coherent slow fading channel at high SNR is succinctly captured as a fundamental tradeoff between diversity and multiplexing gains. We study the problem of designing codes that optimally tradeoff the diversity and multiplexing gains. Our main contribution is a precise characterization of codes that are universally tradeoff-optimal, i.e., they optimally tradeoff the diversity and multiplexing gains for every statistical characterization of the fading channel. We denote this characterization as one of approximate universality where the approximation is in the connection between error probability and outage capacity with diversity and multiplexing gains, respectively. The characterization of approximate universality is then used to construct new coding schemes as well as to show optimality of several schemes proposed in the space-time coding literature.

Optimal Distributed Codes for Feedback-Aided Cooperative Relay Networks

Abstract: A novel transmission scheme for cooperative relay networks is presented in this paper. The proposed scheme is based on the non-orthogonal selection decode-and-forward protocol with an additional assumption of having a low rate feedback channel from the destination to relays. Benefited from the feedback information, an optimal distributed code that has an extremely short delay equal to four is constructed, and the same code is applicable to networks with the arbitrary number of relays to yield optimal cooperative diversity. The proposed code is sphere decodable with a decoding complexity again independent of the number of relays in high SNR regime. In particular, when operating at multiplexing gain ≥(1/2), the lattice decoder at the destination has a zero complexity exponent, meaning a constant decoding complexity and independent of transmission rate. Analyses for the decoding complexity of other existing diversity-optimal distributed codes are also provided. It is shown that these codes have a linear growth in delay and an exponential growth in decoding complexity as the number of relays increases.

Efficiently sphere-decodable physical layer transmission schemes for wireless storage networks

Abstract: Three transmission schemes over a new type of multiple-access channel (MAC) model with inter-source communication links are proposed and investigated in this paper. This new channel model is well motivated by, e.g., wireless distributed storage networks, where communication to repair a lost node takes place from helper nodes to a repairing node over a wireless channel. Since in many wireless networks nodes can come and go in an arbitrary manner, there must be an inherent capability of inter-node communication between every pair of nodes. Assuming that communication is possible between every pair of helper nodes, the newly proposed schemes are based on various smart time-sharing and relaying strategies. In other words, certain helper nodes will be regarded as relays, thereby converting the conventional uncooperative multiple-access channel to a multiple-access relay channel (MARC). The diversity-multiplexing gain tradeoff (DMT) of the system together with efficient sphere-decodability and low structural complexity in terms of the number of antennas required at each end is used as the main design objectives. While the optimal DMT for the new channel model is fully open, it is shown that the proposed schemes outperform the DMT of the simple time-sharing protocol and, in some cases, even the optimal uncooperative MAC DMT. While using a wireless distributed storage network as a motivating example throughout the paper, the MAC transmission techniques proposed here are completely general and as such applicable to any MAC communication with inter-source communication links.

Adaptive beam formation and channel allocation using substance near multicast protocol and CS-iEHO

Abstract: Multiple-input multiple-output (MIMO) systems invite many researchers to contribute more in channels selection for improving the performance for enhancing the throughput and quality of the received signal. It is important to notice that target channel selection will also improve the performance while decreasing the signal-interference-plus-noise ratio. In MIMO channel allocation, it is found that utilization of resources tends to be a dangerous issue which could be tackled by identifying secondary users in addition to primary user for disseminating the information. This paper focuses on allocating the dynamic channels effectively by applying a centralized heuristic algorithm which is referred as cuckoo search with improved elephant herding optimization. In the previous approach, poor resource allocation causes desperate issue in MIMO channel allocation while calculating the energy of each user available in the network. Substance near multicast protocol has been applied for optimizing the energy along with elephant herding optimization algorithm in order to allocate channels dynamically for global optimization process. An improved elephant herding optimization algorithm for multiuser MIMO framework is integrated in the overall remote region. This initiative signifies the greatest number of mutually legitimate clients and the feasible bit rates of clients in the overall remote region. The iEHO algorithm concurrently enhances energy proficiency and framework throughput by client assortment and power distribution. Our trial outcomes ascertained that the recommended method of working fundamentally excelled the essential EHO. Simulation has been done by using MATLAB which is assumed to be the best simulator to show the results without missing the clarity.

Performance-Complexity Analysis for MAC ML-Based Decoding With User Selection

Abstract: The rate-reliability-complexity limits of a quasi-static $K$ -user multiple access channel (MAC), with or without feedback, are explored in this paper. Using high-SNR asymptotics, bounds on the computational resources required to achieve near-optimal (ML-based) decoding performance are first derived. They, in turn, yield bounds on the (reduced) complexity needed to achieve any (including suboptimal) diversity-multiplexing tradeoff (DMT) performance. Similar complexity-bounds in the presence of feedback-aided user selection are also given. This latter effort reveals the ability of a few bits of feedback not only to improve performance, but also to reduce complexity. In this context, our analysis reveals the interesting finding that a proper calibration of user selection can allow for near-optimal ML-based decoding, with complexity that need not scale exponentially in the total number of codeword bits. The derived bounds constitute the best known performance-versus-complexity behavior to date for ML-based MAC decoding, as well as a first exploration of the complexity-feedback-performance interdependencies in multiuser settings.