Transmit Antenna Selection Schemes for Quadrature Spatial Modulation

Naidu, Suvigya; Pillay, Narushan; Xu, Hongjun

doi:10.1007/s11277-017-5060-z

Cited by 11 publications

(18 citation statements)

References 18 publications

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“…Recently, cooperative diversity techniques have become the techniques of great interest by researchers since cooperative communication has advantages such as coverage improvement, link reliability, long network life, high‐energy efficiency, balanced quality of service (QoS), and diversity gain 6,9,10 . Therefore, in this study, instead of the classical quadrature spatial modulation (QSM) based on antenna selection technique mentioned in Naidu et al and Kim, 11,12 we have found it appropriate to study cooperative QSM (CQSM) based on antenna selection technique. The idea behind cooperative communication technique is the communication between the source terminal (ST) and the destination terminal (DT), which is carried out with the help of an additional terminal called relay terminal (RT).…”

Section: Introductionmentioning

confidence: 91%

“…Therefore, to calculate the complexity analysis performed at RT, the expression

(||) {boldh}_{1, λ_{ℜ}}^{S R} x_{1, ℜ} + j {boldh}_{1, λ_{1, ℑ}}^{S R} x_{1, ℑ} - {boldh}_{2, λ_{ℜ}}^{S R} x_{2, ℜ} - j {boldh}_{2, λ_{2, ℑ}}^{S R} x_{2, ℑ} {(||)}_{F}^{2}

in () must be calculated individually for all possible symbol and transmission antenna combinations. Using the similar approach in Naidu et al and Ntontin et al, 11,31 the computational complexity of () is obtained as

4 M false(4 M - 1 false) false(9 N_{R}^{r} - 1 false)

for each antenna pair within each antenna subset. Since EDAS technique is performed for each antenna pair within each antenna subset, EDAS must be executed

((), \binom{N_{χ}^{t}}{2}) κ_{S}

times in total.…”

Section: Computational Complexity For the Edas/coas‐cqsm Systemmentioning

confidence: 99%

“…We can express the total complexity of the COAS‐CQSM system (

{scriptO}_{COAS‐CQSM}

) as follows:

{scriptO}_{COAS‐CQSM} = {scriptO}_{RT}^{COAS} + {scriptO}_{DT}^{COAS},

where

{scriptO}_{RT}^{COAS}

refers to the complexity of RT; on the other hand,

{scriptO}_{DT}^{COAS}

refers to the complexity of DT when COAS is executed. Considering the approach used in Naidu et al, 11 the computational complexity of the COAS‐CQSM technique is equal to the sum of the number of complexities calculated for Step 1 in RT and DT. For each channel gain vector in (), the number of flops is equal to

((), 2 N_{R}^{r} - 1)

for RT.…”

Section: Computational Complexity For the Edas/coas‐cqsm Systemmentioning

confidence: 99%

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Cooperative quadrature spatial modulation with Euclidean distance and capacity optimized antenna selection

Cogen

Aydin

2020

Int J Communication

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SummaryIn this study, new cooperative‐quadrature spatial modulation techniques based on Euclidean distance and capacity optimized antenna selection techniques (EDAS‐CQSM and COAS‐CQSM) are proposed for cooperative communication systems. The considered cooperative system consists of three terminals that are the source terminal (ST), relay terminal (RT), and destination terminal (DT). The decode‐and‐forward (DF) cooperative technique is considered to retransmit the signal at the RT. In order to improve the performance of the conventional QSM demodulator in the RT and DT, both antenna selection techniques have been used in both the ST and RT to reduce performance degradation due to error propagation of the DF scheme. Therefore, the overall performance of the considered CQSM system has been increased. Furthermore, computer simulations have shown that the proposed EDAS/COAS‐CQSM systems have better the performances than the cooperative spatial modulation (CSM), CQSM, EDAS‐CSM, COAS‐CSM, and traditional DF‐based cooperative system with the same bit rate.

show abstract

Section: Introductionmentioning

confidence: 91%

“…Therefore, to calculate the complexity analysis performed at RT, the expression

(||) {boldh}_{1, λ_{ℜ}}^{S R} x_{1, ℜ} + j {boldh}_{1, λ_{1, ℑ}}^{S R} x_{1, ℑ} - {boldh}_{2, λ_{ℜ}}^{S R} x_{2, ℜ} - j {boldh}_{2, λ_{2, ℑ}}^{S R} x_{2, ℑ} {(||)}_{F}^{2}

4 M false(4 M - 1 false) false(9 N_{R}^{r} - 1 false)

for each antenna pair within each antenna subset. Since EDAS technique is performed for each antenna pair within each antenna subset, EDAS must be executed

((), \binom{N_{χ}^{t}}{2}) κ_{S}

times in total.…”

Section: Computational Complexity For the Edas/coas‐cqsm Systemmentioning

confidence: 99%

“…We can express the total complexity of the COAS‐CQSM system (

{scriptO}_{COAS‐CQSM}

) as follows:

{scriptO}_{COAS‐CQSM} = {scriptO}_{RT}^{COAS} + {scriptO}_{DT}^{COAS},

where

{scriptO}_{RT}^{COAS}

refers to the complexity of RT; on the other hand,

{scriptO}_{DT}^{COAS}

((), 2 N_{R}^{r} - 1)

for RT.…”

Section: Computational Complexity For the Edas/coas‐cqsm Systemmentioning

confidence: 99%

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Cooperative quadrature spatial modulation with Euclidean distance and capacity optimized antenna selection

Cogen

Aydin

2020

Int J Communication

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“…In order to further reduce the complexity, a splitting technique is also introduced, where the computational complexity is drastically reduced compared to the hybrid scheme. All the above optimal and sub-optimal schemes are tested for quadrature spatial modulation (QSM) and double-spatial modulation (D-SM) systems [61,62].…”

Section: Introductionmentioning

confidence: 99%

Spatial Correlation Based Transmit Antenna Selection Assisted Fully Generalized Spatial Modulation for Peer-to-Peer Communications

Kumaravelu

Gudla

Asha

et al. 2021

Preprint

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The next generation technologies like device-to-device ( D2D ) and small cells employ small scale multiple input multiple output ( MIMO ) systems for peer-to-peer ( P2P ) communications. Due to higher spectral and energy efficiencies , spatial modulation (SM) has become one of the dominant next generation technologies. To maximize spectral efficiency and user experience, high rate SM variants like fully generalized spatial modulation ( FGSM ) can be employed for P2P applications. Due to insufficient spacing between antenna elements of devices, access points (AP), millimetre wave ( mmWave ) and sub- THz bands of operations, the performance of SM variants are hindered in P2P scenarios. The average bit error rate ( ABER ) performance of FGSM is severely degraded by atleast 13 dB under spatially correlated channel conditions. To enhance the performance of FGSM , three different transmit antenna selection ( TAS ) schemes are utilized, which eliminate transmit antennas with maximum spatial correlation. First TAS scheme performs antenna selection based on spatial correlation angle alone, whereas other two schemes use channel capacity in addition to spatial correlation angle. Through extensive Monte Carlo simulations, it has been proved that TAS based on spatial correlation ( TAS -SC- FGSM ) scheme offers a performance gain of at least 8 dB over conventional FGSM without antenna selection ( FGSM - NTAS ). TAS -SC- FGSM also outperforms other two hybrid TAS schemes at the cost of higher computational complexity.

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“…As a result, QSM has the advantage of doubling the number of bits that can be transmitted in the spatial constellation. Proposals for enhancing the performance of the SM/QSM scheme include for example; precoding [6], trellis code modulation [7], differential spatial modulation [8], antenna selection [9], combined QSM-spatial multiplexing (SMux) [10], and low complexity detection algorithms [11] among others.…”

Section: Introductionmentioning

confidence: 99%

EQSM-based multiuser MIMO downlink transmission for correlated fading channels

Castillo-Soria

Gutiérrez

García-Barrientos

et al. 2020

J Wireless Com Network

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This paper presents three multiuser multiple input-multiple output (MU-MIMO) downlink transmission strategies based on the extended quadrature spatial modulation (EQSM) system for mobile communication. The three MU-MIMO precoding strategies utilised are block diagonalisation (BD), dirty paper coding (DPC), and a combined BD-DPC strategy. We analyse and compare the performance of these three MU-MIMO-EQSM schemes with the conventional MU-MIMO spatial multiplexing (MU-MIMO-SMux) system in terms of bit error rate (BER) and detection complexity considering correlated and uncorrelated fading channels. Results show that the BD-MIMO-EQSM and DPC-MIMO-EQSM systems outperform by 2 − 3 dB in BER performance their conventional counterparts with the additional advantage of a detection complexity reduction of up to 62% for the analysed cases. For the uncorrelated fading channel, the BD technique has better BER performance for a spectral efficiency (SE) of 12 bits per channel use (bpcu), while the DPC technique has better BER performance for an SE of 8 bpcu. Considering the correlated channel, DPC suffers a deep BER degradation of up to 30 dB compared with BD. However, still in this scenario, both proposed MU-MIMO-EQSM systems outperform their conventional counterparts. In terms of detection complexity, DPC has a complexity reduction of 77% as compared with the BD technique. The BD-DPC-MIMO-EQSM hybrid system heritages the low detection complexity of DPC with the advantage of all users in the system having the same BER performance.

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Transmit Antenna Selection Schemes for Quadrature Spatial Modulation

Cited by 11 publications

References 18 publications

Cooperative quadrature spatial modulation with Euclidean distance and capacity optimized antenna selection

Cooperative quadrature spatial modulation with Euclidean distance and capacity optimized antenna selection

Spatial Correlation Based Transmit Antenna Selection Assisted Fully Generalized Spatial Modulation for Peer-to-Peer Communications

EQSM-based multiuser MIMO downlink transmission for correlated fading channels

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