Capacity Improvement in Wideband Reconfigurable Intelligent Surface-Aided Cell-Free Network

Zhang, Zijian; Dai, Linglong

doi:10.1109/spawc48557.2020.9154244

Cited by 48 publications

(44 citation statements)

References 8 publications

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“…Let

d_{BS, k}

d_{BS, RIS}

d_{RIS, k}

denote the distance between BS‐

k

th user, BS‐RIS and RIS‐

k

th user, respectively. Thus, the distance‐dependent path loss (PL) for the BS‐user link can be written as

\begin{matrix} true \\ right PL {false(d_{BS, k} false)}_{d} = C_{d} G_{BS} G_{k} d_{BS, k}^{- ν_{BS, k}}, \end{matrix}

and the PL for the BS‐RIS‐user link can be written as

PL {(d_{BS, RIS}, d_{RIS, k})}_{r} = C_{normalr} G_{BS} G_{k} d_{BS, RIS}^{- ν_{BS, RIS}} d_{RIS, k}^{- ν_{RIS, k}},

where

C_{d}

and

C_{r}

are the channel fading variables depending on the wavelength, channel status, and angle of departure (AoD); Moreover,

C_{r}

is also related to the angle of arrival (AoA), the material and size of RIS element [3];

G_{BS}

and

G_{k}

denote the antenna gain of the BS and the

k

th user; Here, we assume

C_{normald} G_{BS} G_{k}

= −30 dB and

C_{normalr} G_{BS} G_{k}

= −40 dB [6]; The PL exponents for the BS‐RIS link and RI...…”

Section: Simulation Resultsmentioning

confidence: 99%

“…From this figure, it is observed that as the horizontal distance

D

between the BS and users increases, the achievable spectral efficiency performance decreases rapidly due to the serious attenuation of the signals. However, a peak at

D

= 30 m indicates that the spectral efficiency of both PSO and existing scheme [6] increases when the users approach the RIS, since the users receive strong signals reflected from the RIS. On the other hand, no peak is observed for the conventional without RIS scheme.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Simulation results: In this section, simulation results are provided to validate the performance of the RIS-aided MIMO communication system. We compare the spectral efficiency performance of the PSO algorithm with the existing work [6].…”

Section: Algorithm 1 Pso Algorithmmentioning

confidence: 99%

“…The spectral efficiency performance of the PSO algorithm is shown in Figure 3, [6] in the whole transmit power range. Moreover, the PSO algorithm achieves about 93% of the spectral efficiency achieved by the existing scheme [6], but with much lower complexity as we have discussed before. Figure 4 shows the spectral efficiency performances against the horizontal distance D between BS and users.…”

Section: Achievable Spectral Efficiency Comparisonmentioning

confidence: 99%

See 3 more Smart Citations

Low‐complexity joint active and passive beamforming for RIS‐aided MIMO systems

Siddiqi

Mir

Hao

et al. 2021

Electronics Letters

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In this paper, we consider the reconfigurable intelligent surface (RIS)aided MIMO systems to realize a high quality link between the base station (BS) and the users via a RIS. To achieve this goal, the active beamforming at the BS and the passive beamforming at the RIS should be jointly optimized. However, most of the existing joint optimization schemes that maximize the sum-rate have high computational complexity due to the complex derivative calculations and matrix inversion. To this end, a biologically inspired particle swarm optimization (PSO) algorithm is exploited to solve the non-convex sum-rate optimization problem with low-complexity. Simulation results show that the proposed scheme provides a better trade-off between performance and complexity than existing solutions for RIS-aided MIMO systems.

show abstract

“…Let

d_{BS, k}

d_{BS, RIS}

d_{RIS, k}

denote the distance between BS‐

k

th user, BS‐RIS and RIS‐

k

th user, respectively. Thus, the distance‐dependent path loss (PL) for the BS‐user link can be written as

\begin{matrix} true \\ right PL {false(d_{BS, k} false)}_{d} = C_{d} G_{BS} G_{k} d_{BS, k}^{- ν_{BS, k}}, \end{matrix}

and the PL for the BS‐RIS‐user link can be written as

PL {(d_{BS, RIS}, d_{RIS, k})}_{r} = C_{normalr} G_{BS} G_{k} d_{BS, RIS}^{- ν_{BS, RIS}} d_{RIS, k}^{- ν_{RIS, k}},

where

C_{d}

and

C_{r}

are the channel fading variables depending on the wavelength, channel status, and angle of departure (AoD); Moreover,

C_{r}

is also related to the angle of arrival (AoA), the material and size of RIS element [3];

G_{BS}

and

G_{k}

denote the antenna gain of the BS and the

k

th user; Here, we assume

C_{normald} G_{BS} G_{k}

= −30 dB and

C_{normalr} G_{BS} G_{k}

= −40 dB [6]; The PL exponents for the BS‐RIS link and RI...…”

Section: Simulation Resultsmentioning

confidence: 99%

“…From this figure, it is observed that as the horizontal distance

D

between the BS and users increases, the achievable spectral efficiency performance decreases rapidly due to the serious attenuation of the signals. However, a peak at

D

Section: Simulation Resultsmentioning

confidence: 99%

Section: Algorithm 1 Pso Algorithmmentioning

confidence: 99%

Section: Achievable Spectral Efficiency Comparisonmentioning

confidence: 99%

See 2 more Smart Citations

Low‐complexity joint active and passive beamforming for RIS‐aided MIMO systems

Siddiqi

Mir

Hao

et al. 2021

Electronics Letters

View full text Add to dashboard Cite

show abstract

“…To the best of authors' knowledge, the RIS aided weighted sum rate (WSR) maximization problem for mmWave vehicular uplink is not investigated in the literature. Although, WSR maximization for RIS aided communication systems are investigated in [23], [24] and [25], those did not consider the vehicular scenario, and a continuous phase shift model is used for the RIS. WSR maximization for an RIS aided multiple-input single-output (MISO) downlink communication system is investigated in [25], where the authors use fractional programming (FP) techniques [26] to decompose the original problem into four disjoint blocks and to design a lowcomplexity algorithm based on the non-convex block coordinate descent (BCD) method.…”

Section: Introductionmentioning

confidence: 99%

Weighted-Sum-Rate Maximization for an Reconfigurable Intelligent Surface Aided Vehicular Network

Dampahalage

Manosha

Rajatheva

2021

IEEE Open J. Commun. Soc.

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Recently, reconfigurable intelligent surfaces (RISs) have been identified as one potential solution to avoid performance degradation of using millimeter wave (mmWave) frequencies in vehicular communications. In this paper, we investigate the use of an RIS in a mmWave vehicular communication network. The problem of weighted sum-rate maximization in the uplink is considered, where an RIS is used to assist the communication. We focus on both single-user and multi-user cases. Single user case is solved using successive refinement algorithm, where two phase-optimization schemes that help reducing the channel estimation overhead are considered. In multi-user case, fractional programming technique is used to reformulate the original problem into a more convenient form, and an algorithm based on alternating optimization is proposed. The validity of the proposed methods is confirmed by numerical simulations. A significant performance increase is seen when utilizing an RIS in both cases. Considered phase optimization schemes are shown to result in a significant reduction in channel estimation at a cost of small performance degradation compared to the full channel state information beamforming scenario. We perform simulations to investigate the effects of mobility, and the results demonstrate the ability of an RIS to mitigate the effects of mobility to some extent. Furthermore, to get practical insights into vehicular communications aided by an RIS, we use a commercial ray-tracing tool to evaluate the performance.

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