Dear Reader,

* This is the dataset of the paper (December, 2017):  I. A. Hemadeh, M. El-Hajjar and L. Hanzo, "Hierarchical Multi-Functional Layered Spatial Modulation"




* Paper Abstract:
Abstract--- In pursuit of optimal Index Modulation (IM)-aided Multiple-Input Multiple-Output (MIMO) systems, where information is implicitly conveyed by relying on the on/off mechanism of the system's components in addition to the classical amplitude, phase or frequency components, we present in a tutorial style our novel Multi-Functional (MF) architecture of Layered Multi-Set (LMS) modulation. This generalized framework subsumes various MIMO techniques exhibiting different multiplexing and diversity functionalities. Our LMS design relies on three constituents, namely the space-time (ST) unit, the layered unit as well as the spatial switching unit. More specifically, the ST unit relies on the Generalized Space-Time Shift Keying (GSTSK) scheme, where P -- rather than one -- out of Q ST dispersion matrices are selected for dispersing an equivalent number of PSK/QAM symbols across the antennas and time-slots. In the layered unit, multiple GSTSK codewords are stacked within the layers of codewords spread over time and space. The spatial switching unit activates N_{c}^{t} out of N_{t} transmit antennas. Owing to its hierarchical MF architecture, our LMS system strikes a flexible design trade-off between the achievable throughput as well as the attainable diversity gain and it can potentially subsume various conventional MIMO schemes, such as Bell Lab’s Layered Space-Time (BLAST), Space-Time Block Codes (STBCs), Layered Steered Space-Time Codes (LSSTCs), Spatial Modulation (SM), Space-Shift Keying (SSK), Linear Dispersion Codes (LDCs), Generalized SM (GSM), STSK, GSTSK, Quadrature SM (QSM) as well as Multi-Set STSK (MS-STSK). Additionally, we derive the LMS system's Discrete-input Continuous-output Memoryless Channel (DCMC) capacity, which encompasses the capacity limit of all the LMS subsidiaries. We also propose a two-stage serially concatenated soft-decision (SD) based LMS detector by relying on an inner and an outer decoder that iteratively exchange their extrinsic information in order to achieve a near-capacity performance. Last but not least, we utilize the EXtrinsic Information Transfer (EXIT) charts for analyzing the convergence behavior of our SD-aided coded LMS scheme.


* Project:
The financial support of the EPSRC projects EP/Noo4558/1 and EP/L018659/1, as well as of the European Research Council's Advanced Fellow Grant under the Beam-Me-Up project and of the Royal Society's Wolfson Research Merit Award is gratefully acknowledged.


* This dataset contains the data of Figures 21, 22, 23, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38 and 39 of the paper "Hierarchical Multi-Functional Layered Spatial Modulation". Each folder is named according to the figure's number and the dataset of each cruve - of each figure - is stored in a .dat file in that folder. There is THREE different plot types: BER plots, EXIT charts and CAPACITY plots, which are represented as follows:
      - The BER plots are represented by the Eb/N0, SNR and BER values as "Eb/N0 SNR BER". 
      - The EXIT charts are represented by the I_{Det, a} a priori and I_{Det, e} extrinsic mutual information.
      - The CAPACITY plots are reperesented by the Achievable Capacity vs SNR.
      -

To regenerate the results please use the command "gle Figure_Name.gle" (Graphics Layout Engine -GLE- should be installed on your machine)

Enjoy!
Ibrahim A. Hemadeh (BEng, MSc, PhD)
25/12/2017