New expression for the functional transformation of the vector Cramér-Rao lower bound

Assume that it is desired to estimate α = f(θ), where f(·) is an r-dimensional function. This paper derives the general expression for the functional transformation of the vector Cramér-Rao lower bound (CRLB). The derived bound is a tight lower bound on the estimation of uncoupled parameters, i.e., parameters that can be estimated separately. Unlike previous results in the literature, this new expression is not dependent on the inverse of the Fisher's information matrix (FIM) of the untransformed parameters, θ. Thus, it can be applied to scenarios where the FIM for θ is ill-conditioned or singular. Finally, as an application, the derived transformation is applied to determine the exact CRLB for estimation of channel parameters in amplify-and-forward relaying networks.This research was supported under Australian Research Council’s Discovery Projects funding scheme (project number DP110102548)

Multi-Stream LDPC Decoder on GPU of Mobile Devices

Low-density parity check (LDPC) codes have been extensively applied in mobile communication systems due to their excellent error correcting capabilities. However, their broad adoption has been hindered by the high complexity of the LDPC decoder. Although to date, dedicated hardware has been used to implement low latency LDPC decoders, recent advancements in the architecture of mobile processors have made it possible to develop software solutions. In this paper, we propose a multi-stream LDPC decoder designed for a mobile device. The proposed decoder uses graphics processing unit (GPU) of a mobile device to achieve efficient real-time decoding. The proposed solution is implemented on an NVIDIA Tegra board as a system on a chip (SoC), where our results indicate that we can control the load on the central processing units through the multi-stream structure

High-Rate and Low-Complexity Space-Time Block Codes for 2x2 MIMO Systems

The main design criteria for space-time block codes (STBCs) are the code rate, diversity order, coding gain, and low decoder complexity. In this letter, we propose a full-rate full-diversity STBC for 2 × 2 multiple-input multiple-output (MIMO) systems with a substantially lower maximum likelihood (ML) detection complexity than that of existing schemes. This makes the implementation of high-performance full-rate codes feasible for practical systems. Our numerical evaluation shows that the proposed code achieves significantly lower decoding complexity while maintaining a similar performance compared to that of existing rate-2 STBCs

High-Rate Space Coding for Reconfigurable 2x2 Millimeter-Wave MIMO Systems

Millimeter-wave links are of a line-of-sight nature. Hence, multiple-input multiple-output (MIMO) systems operating in the millimeter-wave band may not achieve full spatial diversity or multiplexing. In this paper, we utilize reconfigurable antennas and the high antenna directivity in the millimeter-wave band to propose a rate-two space coding design for 2x2 MIMO systems. The proposed scheme can be decoded with a low complexity maximum-likelihood detector at the receiver and yet it can enhance the bit-error-rate performance of millimeter-wave systems compared to traditional spatial multiplexing schemes, such as the Vertical Bell Laboratories Layered Space-Time Architecture (VBLAST). Using numerical simulations, we demonstrate the efficiency of the proposed code and show its superiority compared to existing rate-two space-time block codes

Hybrid Localization: A Low Cost, Low Complexity Approach Based on Wi-Fi and Odometry

Localization in indoor environments is essential to further support automation in a wide array of scenarios. Moreover, direction-of-arrival knowledge is essential to supporting high speed millimeter-wave (mmWave) links in indoor environments, since most mmWave links are of a line-of-sight nature to combat the high pathloss in this band. Accurate wireless localization in indoor environments, however, has proved a challenging task due to multi-path fading. Additionally, due to the effects of multi-path fading, methods such as trilateration alone do not result in accurate localization. As such, in this paper we propose to combine the knowledge of wireless localization methods with that of odometry sensors to track the location of a mobile robot. This paper presents significant real-world localization measurement results for both Wi-Fi and odometry in diverse environments at the Boise State University campus. Using these results, we devise an algorithm to combine data from both odometry and wireless localization. This algorithm is shown in hardware testing to reduce the localization error for a mobile robot

Reconfigurable Antenna for Next Generation Satellite & 5G Communication System

We propose the design of high gain electronic beam-forming antenna for next generation Satellite communication and 5G millimetric wave wireless communication systems. We are using transformation optics for steering antenna radiation pattern. Our design involves the use of a passive meta surface to converge the electromagnetic waves. Meta-surface comprises of multiple unit cells and each unit cell introduces a specific phase shift desired to steer the beam towards the intended direction. This concept is extremely cost effective to implement as no active components are used for beam-steering. In comparison to current market solutions, this configuration is low cost and easy to manufacture. This technology once implemented will be a game changer for whole Satcom industry and will open new horizons for wireless communication

Non-Orthogonal Multiple Access Based on Hybrid Beamforming for mmWave Systems

This paper aims to study the utilization of non-orthogonal multiple access (NOMA) in hybrid beamforming (HB) multiuser systems, called HB-NOMA, to serve a large number of mobile users. First, a sum-rate expression for the HB-NOMA problem is formulated. Second, an effective algorithm is proposed to maximize the sum-rate. Then, a lower bound is derived under two cases: i) the angle between the effective channel vectors of the MU with the highest channel gain and other MUs located inside a cluster is zero (or close to it) which is denoted by perfect correlation, and ii) this angle is non-zero, which we denote by imperfect correlation. For the second case, the relationship between the effective channels of two HB-NOMA users is modeled. The lower bound for the first case indicates that only the presence of inter-cluster interference and the use of an analog precoder negatively impact the sum-rate. However, in the case of imperfect correlation, which is more realistic, an inefficient MU cluster, can cause severe intra-cluster interference in the network. To verify our findings, numerical simulations have been conducted

High Rate/Low Complexity Space-Time Block Codes for 2x2 Reconfigurable MIMO Systems

In this paper, we propose a full-rate full-diversity space-time block code (STBC) for 2x2 reconfigurable multiple-input multiple-output (MIMO) systems that require a low complexity maximum likelihood (ML) detector. We consider a transmitter equipped with a linear antenna array where each antenna element can be independently configured to create a directive radiation pattern toward a selected direction. This property of transmit antennas allow us to increase the data rate of the system, while reducing the computational complexity of the receiver. The proposed STBC achieves a coding rate of two in a 2x2 MIMO system and can be decoded via an ML detector with a complexity of order M, where M is the cardinality of the transmitted symbol constellation. Our simulations demonstrate the efficiency of the proposed code compared to existing STBCs in the literature.Comment: arXiv admin note: text overlap with arXiv:1505.0646

Self-Organizing mmWave Networks: A Power Allocation Scheme Based on Machine Learning

Millimeter-wave (mmWave) communication is anticipated to provide significant throughout gains in urban scenarios. To this end, network densification is a necessity to meet the high traffic volume generated by smart phones, tablets, and sensory devices while overcoming large pathloss and high blockages at mmWaves frequencies. These denser networks are created with users deploying small mmWave base stations (BSs) in a plug-and-play fashion. Although, this deployment method provides the required density, the amorphous deployment of BSs needs distributed management. To address this difficulty, we propose a self-organizing method to allocate power to mmWave BSs in an ultra dense network. The proposed method consists of two parts: clustering using fast local clustering and power allocation via Q-learning. The important features of the proposed method are its scalability and self-organizing capabilities, which are both important features of 5G. Our simulations demonstrate that the introduced method, provides required quality of service (QoS) for all the users independent of the size of the network