Browsing by Author "Sourour, Essam"

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Biased-Power Allocation and Shared-Antenna Selection Techniques for Spatial Modulation-Based Layer Division Multiplexing Systems
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-06) Al-Ansi, Mohammed; Kolhar, Manjur; Sourour, Essam; Chatzinotas, Symeon
This study proposes two approaches for improving the effectiveness of spatial modulation integrated into layer division multiplexing (SM-LDM) in broadcasting systems: biased-power alloca- tion (Bi-PA) and shared antenna selection (SAS). Even though different data rates are employed in SM-LDM systems, Bi-PA enhances bit error rate (BER) fairness across layers. The ideal power ratios are adaptively determined by balancing signal-to-interference plus noise ratios with a preference for the lower layer (LL) that involves a higher modulation order. SAS alleviates the complexity of successive interference cancellation and enhances spectral and energy efficiencies. Both the LL and upper layer (UL) share the antenna selection decision and transmit using a single antenna. The UL carries a space shift keying signal while the entire power is allocated for the LL. We analyze the spectral efficiency for the SAS-based SM-LDM system with finite alphabet inputs. Numerical results demonstrate the advantages of the proposed approaches. Compared to pre-assigned-PA (Pre-PA), Bi-PA shows nearly identical BERs for both layers and solves the error floor problem. The sharing property and common layer transmission of SAS-based SM-LDM yield a significant BER reduction relative to conventional SM-LDM. It provides gains ranging from 7 to 15 dB for LL at BER equal to 10−3 , while UL performance ranges from slight gain to minor loss. Furthermore, both Bi-PA and SAS techniques enhance the achievable LL rate and sum-rate at low and intermediate signal-to-noise ratio values. They can achieve an improvement of up to two bits in LL rate and less than one bit in sum-rate at a signal-to-noise ratio of −0.5 dB. These findings show that both proposed techniques have a considerable impact on enhancing the fairness, BER performance, and feasible rates of SM-LDM systems, making them promise for broadcast system designs.
Reduced Complexity Spatial Modulation Transmit Precoding for PSK Constellation
(MSA University, 2022-02) Sourour, Essam
Spatial modulation (SM) conveys extra data by selecting the transmit antenna. This makes SM prone to channel irregularities like multipath Raleigh fading. Hence, employing and optimizing a transmit precoder (TPC) that matches the channel can enhance the SM bit error rate performance by increasing the Euclidean distance (ED) among all possible received vectors. However, it is common that optimization algorithms endure high complexity. Focusing on M- PSK constellation, and by reducing the number of Euclidean Distance constraints, we cut the complexity by nearly a factor of M. This is a significant reduction for high order constellations with a large value of M. This concept is shown to benefit any TPC optimization algorithm for SM and its variants. To further shrink the complexity, we introduce an optimization algorithm that minimizes the sum of the exponentials of negative EDs. The paper shows that the complexity can be reduced significantly without loss in performance.
Reduced Complexity Spatial Modulation Transmit Precoding for PSK Constellation
(October university for modern sciences and Arts MSA, 2022) Sourour, Essam
Spatial modulation (SM) conveys extra data by selecting the transmit antenna. This makes SM prone to channel irregularities like multipath Raleigh fading. Hence, employing and optimizing a transmit precoder (TPC) that matches the channel can enhance the SM bit error rate performance by increasing the Euclidean distance (ED) among all possible received vectors. However, it is common that optimization algorithms endure high complexity. Focusing on M-PSK constellation, and by reducing the number of Euclidean Distance constraints, we cut the complexity by nearly a factor of M. This is a significant reduction for high order constellations with a large value of M. This concept is shown to benefit any TPC optimization algorithm for SM and its variants. To further shrink the complexity, we introduce an optimization algorithm that minimizes the sum of the exponentials of negative EDs. The paper shows that the complexity can be reduced significantly without loss in performance.