Space-time coding for UMTS. Performance evaluation in combination with convolutional and turbo coding

Space-time codes provide both diversity and coding gain when using multiple transmit antennas to increase spectral efficiency over wireless communications systems. Space-time block codes have already been included in the standardization process of UMTS in conjunction with conventional channel codes (convolutional and turbo codes). We discuss different encoding and decoding strategies when transmit diversity is combined with conventional channel codes, and present simulations results for the TDD and FDD modes of UTRA.Peer ReviewedPostprint (published version

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

A universal space-time architecture for multiple-antenna aided systems

In this tutorial, we first review the family of conventional multiple-antenna techniques, and then we provide a general overview of the recent concept of the powerful Multiple-Input Multiple-Output (MIMO) family based on a universal Space-Time Shift Keying (STSK) philosophy. When appropriately configured, the proposed STSK scheme has the potential of outperforming conventional MIMO arrangements

High-rate codes that are linear in space and time

Multiple-antenna systems that operate at high rates require simple yet effective space-time transmission schemes to handle the large traffic volume in real time. At rates of tens of bits per second per hertz, Vertical Bell Labs Layered Space-Time (V-BLAST), where every antenna transmits its own independent substream of data, has been shown to have good performance and simple encoding and decoding. Yet V-BLAST suffers from its inability to work with fewer receive antennas than transmit antennas-this deficiency is especially important for modern cellular systems, where a base station typically has more antennas than the mobile handsets. Furthermore, because V-BLAST transmits independent data streams on its antennas there is no built-in spatial coding to guard against deep fades from any given transmit antenna. On the other hand, there are many previously proposed space-time codes that have good fading resistance and simple decoding, but these codes generally have poor performance at high data rates or with many antennas. We propose a high-rate coding scheme that can handle any configuration of transmit and receive antennas and that subsumes both V-BLAST and many proposed space-time block codes as special cases. The scheme transmits substreams of data in linear combinations over space and time. The codes are designed to optimize the mutual information between the transmitted and received signals. Because of their linear structure, the codes retain the decoding simplicity of V-BLAST, and because of their information-theoretic optimality, they possess many coding advantages. We give examples of the codes and show that their performance is generally superior to earlier proposed methods over a wide range of rates and signal-to-noise ratios (SNRs)

Power Efficient MISO Beamforming for Secure Layered Transmission

This paper studies secure layered video transmission in a multiuser multiple-input single-output (MISO) beamforming downlink communication system. The power allocation algorithm design is formulated as a non-convex optimization problem for minimizing the total transmit power while guaranteeing a minimum received signal-to-interference-plus-noise ratio (SINR) at the desired receiver. In particular, the proposed problem formulation takes into account the self-protecting architecture of layered transmission and artificial noise generation to prevent potential information eavesdropping. A semi-definite programming (SDP) relaxation based power allocation algorithm is proposed to obtain an upper bound solution. A sufficient condition for the global optimal solution is examined to reveal the tightness of the upper bound solution. Subsequently, two suboptimal power allocation schemes with low computational complexity are proposed for enabling secure layered video transmission. Simulation results demonstrate significant transmit power savings achieved by the proposed algorithms and layered transmission compared to the baseline schemes.Comment: Accepted for presentation at the IEEE Wireless Communications and Networking Conference (WCNC), Istanbul, Turkey, 201

Implementable Wireless Access for B3G Networks - III: Complexity Reducing Transceiver Structures

This article presents a comprehensive overview of some of the research conducted within Mobile VCE’s Core Wireless Access Research Programme,1 a key focus of which has naturally been on MIMO transceivers. The series of articles offers a coherent view of how the work was structured and comprises a compilation of material that has been presented in detail elsewhere (see references within the article). In this article MIMO channel measurements, analysis, and modeling, which were presented previously in the first article in this series of four, are utilized to develop compact and distributed antenna arrays. Parallel activities led to research into low-complexity MIMO single-user spacetime coding techniques, as well as SISO and MIMO multi-user CDMA-based transceivers for B3G systems. As well as feeding into the industry’s in-house research program, significant extensions of this work are now in hand, within Mobile VCE’s own core activity, aiming toward securing major improvements in delivery efficiency in future wireless systems through crosslayer operation

Media-Based MIMO: A New Frontier in Wireless Communications

The idea of Media-based Modulation (MBM), is based on embedding information in the variations of the transmission media (channel state). This is in contrast to legacy wireless systems where data is embedded in a Radio Frequency (RF) source prior to the transmit antenna. MBM offers several advantages vs. legacy systems, including "additivity of information over multiple receive antennas", and "inherent diversity over a static fading channel". MBM is particularly suitable for transmitting high data rates using a single transmit and multiple receive antennas (Single Input-Multiple Output Media-Based Modulation, or SIMO-MBM). However, complexity issues limit the amount of data that can be embedded in the channel state using a single transmit unit. To address this shortcoming, the current article introduces the idea of Layered Multiple Input-Multiple Output Media-Based Modulation (LMIMO-MBM). Relying on a layered structure, LMIMO-MBM can significantly reduce both hardware and algorithmic complexities, as well as the training overhead, vs. SIMO-MBM. Simulation results show excellent performance in terms of Symbol Error Rate (SER) vs. Signal-to-Noise Ratio (SNR). For example, a $4\times 16$ LMIMO-MBM is capable of transmitting $32$ bits of information per (complex) channel-use, with SER $\simeq 10^{-5}$ at $E_b/N_0\simeq -3.5$dB (or SER $\simeq 10^{-4}$ at $E_b/N_0=-4.5$dB). This performance is achieved using a single transmission and without adding any redundancy for Forward-Error-Correction (FEC). This means, in addition to its excellent SER vs. energy/rate performance, MBM relaxes the need for complex FEC structures, and thereby minimizes the transmission delay. Overall, LMIMO-MBM provides a promising alternative to MIMO and Massive MIMO for the realization of 5G wireless networks.Comment: 26 pages, 11 figures, additional examples are given to further explain the idea of Media-Based Modulation. Capacity figure adde