Terms Of Average Spectral Efficiency Research Articles

Caching popularity-unknown contents for massive communication channels via deep Q-learning

In order to reduce the backhaul link pressure of wireless networks, edge caching technology has been regarded as a promising solution. However, with massive and dynamical communication connections, it is challenging to provide analytical caching solution to achieve the best performance, particularly when the requested contents are changing and their popularities are unknown. In this paper, we propose a deep Q-learning (DQN) method to address the issue of caching placement. Considering a content caching network containing multiple cooperating SBSs with unknown content popularity, we need to determine which content to cache and where to cache. Therefore, the learning network has to be designed for dual aims, one of which is to estimate the content popularities while the other is to assign contents to the proper channels. An elaborate DQN is proposed to make decisions to cache contents with limited storage space of base-station by considering channel conditions. Specifically, the content requests of users are first collected as one of the training samples of the learning network. Second, the channel state information for the massive links are estimated as the other training samples. Then, we train the network based on the proposed method thereby improving spectral efficiency of the entire system and reducing bit-error rate. Our major contribution is to contrive a caching strategy for enhanced performance in massive connection communications without knowing the content popularity. Numerical studies are performed to show that the proposed method acquires apparent performance gain over random caching in terms of average spectral efficiency and bit-error rate of the network.

A NOMA Scheme for IoT Enabled by Selective Powering of Passive Backscattering Nodes

In this letter, we propose a novel communication strategy for Non-orthogonal Multiple Access (NOMA) systems with passive backscattering sensor nodes. The proposed scheme relies on the ability to control the number of backscattering sensors contending the channel, by tuning the transmission power of the illuminator incrementally. Multiple-access interference is then mitigated by Successive Interference Cancellation (SIC) at the receiver. To benchmark the performance of our proposal, a random access NOMA scheme is considered. We show that our proposal outperforms the random access protocol in terms of average spectral efficiency, while guaranteeing a substantial reduction in the energy consumption.

Reconfigurable Intelligent Surface aided Indoor and Outdoor User Distribution in Heterogeneous Network

Millimeter wave communication suffers from static blockages such as trees, buildings and so on. Reconfigurable Intelligent Surfaces (RISs) has been adapted to solve this blockage problem and enable the urban environment user to choose mmW enabled small cells as their source transmitter or to choose macro cells in case of non-line of sight exists. RIS is a promising network technology to improve the quality of service parameters such as spectral efficiency and energy efficiency by artificially reconfiguring the propagation environment of electromagnetic waves. An indoor user can be connected with mmW band if the line of sight (LOS) link exists. Otherwise, the system utilizes RIS transmission model to have reliable and low-latency communication. It reflects the capability of RISs to enable enhanced communications in challenging environments. An optimization problem is formulated to maximize the sum data rate of an indoor user by phase shift optimization at the RIS. The outage probability of the proposed scheme is analyzed under Rician fading channel. The proposed RIS enabled method targets to enhance the overall performance in terms of average spectral efficiency and achievable data rate in the presence of blockages and system imperfections. The data rate is increased by three fold times than that of the transmission without RIS. The utility of this framework is discussed for both indoor and outdoor environments.

Joint Adaptive M-QAM Modulation and Power Adaptation for a Downlink NOMA Network

In this paper, we study joint adaptive M-QAM modulation and power adaptation for a downlink two-user non-orthogonal multiple access (NOMA) network. Without sacrificing bit error rate (BER), joint adaptive transmission can fully utilize the time-varying nature of wireless channels, by allowing both power and rate to adapt to channel fading. Two adaptive power allocation strategies, namely, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 1</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 2</i> , each of which guarantees the minimum target rate for one user while supporting the highest possible rate for the other, are first proposed. Then, based on the two power schemes, the performance of joint adaptive transmission in terms of average spectral efficiency (SE) is studied for continuous-rate and discrete-rate modulation, while guaranteeing the minimum required rate and BER requirements. With the focus on practical discrete-rate M-QAM modulation, it is proved that for the strong user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 1</i> and the weak user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 2</i> , their average SEs converge to the minimum target rates. In order to further increase the total transmission rate, we then propose a dynamic rate and power adaptation (DRPA) algorithm, aiming to increase the rate of one user without sacrificing the rate of the other. It is shown that at high SNRs, the DRPA algorithm allows the strong user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 1</i> and the weak user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 2</i> to continue to increase their transmission rates until reaching the highest modulation order that the system can support. Hence, the total transmission rate can be greatly increased at high SNRs due to the adoption of DRPA, by allowing both users in each scheme to reach the highest transmission rate in the system.

Misalignment fading effects on the ACC performance of relay-assisted MIMO/FSO systems over atmospheric turbulence channels

&lt;span&gt;The continuous development of internet of things (IoT) technology enables many devices to be interconnected through the external environment. Meanwhile, 5G technology provides an enhanced quality of services with high data transmission rates, requiring IoT implementation in the 5G architecture. Free-space optical communication (FSO) is considered a promising technique that can provide high-speed communication links, so FSO is an optimal choice for wireless networks to fulfill the full potential of 5G technology, providing speeds of 100 Gb/s or more. By implementing 5G features in IoT, IoT coverage and performance will be enhanced by using FSO models. Therefore, the paper proposed and investigated the multiple-input and multiple-output/free-space optical communication (MIMO/FSO) model using subcarrier quadrature amplitude modulation (SC-QAM) and relay stations over atmospheric turbulence channels by log-normal and gamma-gamma distribution under different turbulence conditions. The performance is examined based on the average channel capacity (ACC), which is expressed in terms of average spectral efficiency (ASE) parameters while changing the different parameters of the model. The mathematical formulas of ACC for atmospheric turbulence cases are calculated and discussed the influence of turbulence strength, the different number of relay stations, misalignment effects, and different MIMO configurations.&lt;/span&gt;

User Scheduling Based on Multi-Agent Deep Q-Learning for Robust Beamforming in Multicell MISO Systems

Maximizing the rate in multiple input single output (MISO) systems using distributed algorithms is an important task that typically incurs high computational cost. In this work, we propose two deep Q-learning-based user scheduling schemes to solve the beamforming problem of sum-rate maximization with per base station power constraints in multicell MISO scenarios. The two key features of the proposed algorithms are that they are executed in a distributed fashion and are robust with respect to channel state information (CSI) errors. Simulation results show that in the presence of CSI errors the proposed schemes outperform state-of-the-art algorithms both in terms of average spectral efficiency and execution time.

Directional Training for FDD Massive MIMO

A key challenge for frequency-division duplexing (FDD) massive multi-input multi-output (MIMO) is the large overhead in acquiring channel state information (CSI) for transmits beamforming. In this paper, we propose a scalable method called directional training to obtain downlink CSI. Directional training is motivated by two empirical results derived from massive MIMO channel measurements. First, the number of dominant angle-of-arrivals (departures) is much smaller than and nearly independent of the number of base-station antennas. Second, there is a strong correlation between uplink arrival and downlink departure angles even in FDD systems, which leads to the idea of directional training, where a small number of training symbols can be sent to estimate the dominant components of the downlink channel. Therefore, directional training measures much fewer complex coefficients than full-training-based methods, and as a result, compared with full-training, the overall channel acquisition overhead for directional training scales much slower with the number of base-station antennas. We evaluate directional training with extensive experiments with a 64-antenna base-station at two bands separated by approximately 72 MHz. Our results show that directional training-based downlink beamforming outperforms full-training systems by 150% in terms of average spectral efficiency, and loses only 5.3% average spectral efficiency from genie-aided systems.

Performance Analysis of Output Threshold-Based Incremental Multiple-Relay Combining Scheme with Adaptive Modulation for Cooperative Networks

In this paper, we propose an output threshold-based incremental multiple-relay combining scheme for cooperative amplify-and-forward relay networks with nonidentically distributed relay channels. Specifically, in order to achieve the required performance, we consider both conventional incremental relaying and multiple-relay selection where relays are adaptively selected based on a predetermined output threshold. Moreover, the adaptive modulation technique is adopted by our proposed scheme for satisfying both the spectral efficiency and the required error rate. For the proposed scheme, we first derive an upper bound of the output combined signal-to-noise ratio and then provide its statistics such as cumulative distribution function (CDF), probability density function (PDF), and moment generating function (MGF) over independent, nonidentically distributed Rayleigh fading channels. Additionally, we analyze the system performance in terms of average spectral efficiency, average bit error rate, outage probability, and system complexity. Finally, numerical examples show that our proposed scheme leads to a certain performance improvement in the cooperative networks.

Reconfigurable Antenna-Based Space-Shift Keying (SSK) for MIMO Rician Channels

In this work, we use the concept of the new emerging technology of reconfigurable antennas (RAs) in an effort to improve the performance of space shift keying (SSK). Indeed, the reconfigurable properties of RAs can be used as additional degrees of freedom to enhance the performance of SSK in terms of throughput, system complexity, and error performance. In this context, considering correlated and nonidentically distributed Rician fading channels, we propose a number of SSK-RA schemes using SSK with antenna-state selection while taking advantage of the effect of RAs on the multipath propagation channel. More specifically, based on the variation of the Rician $K$ -factor and the correlation coefficients with different antenna states, the proposed schemes jointly optimize the fading and correlation parameters to enhance SSK’s performance. In this paper, we analyze the performance of the proposed SSK-RA schemes over Rician fading channels in terms of average spectral efficiency (ASE) and bit error rate (BER). We also provide several simulation examples through which we corroborate these analytical results. The proposed schemes are shown to enhance the performance of SSK both in terms of ASE and BER. For the same ASE, compared to that of SSK, not only do the proposed SSK-RA schemes provide much better error performance, they also reduce the implementation cost and the overall system complexity considerably.

Adaptive Spatial Modulation for Spectrum Sharing Systems With Limited Feedback

We have recently introduced adaptive spatial modulation (ASM) for multiple antenna systems, with the aim of improving the energy efficiency through spatial modulation (SM) and improving the average spectral efficiency (ASE) through adaptive modulation (AM). In this paper, we extend ASM to cognitive radio (CR) systems in an effort to improve the secondary system's performance in terms of energy efficiency and ASE. To this end, we propose two ASM schemes, one referred to as fixed power scheme (FPS) and the other as adaptive power scheme (APS). In both schemes, the secondary transmitter (ST) has limited knowledge of the channel state information (CSI) of the interference link. The difference between the two schemes, however, lies in the way the limited CSI is used to adapt the transmit power and/or modulation. As a benchmark, we also consider the scenario where the ST has perfect knowledge of the CSI of the interference link. For all cases, we analyze the performance in terms of ASE, average delay, and bit error rate (BER). We show that the proposed schemes offer tradeoffs in terms of the previously mentioned performance metrics, thus offering different options for applying ASM to CR systems. We also provide several simulation examples through which we corroborate the analytical results.

서비스 특성을 고려한 다 계층 재전송 방식 선택

The wireless communication system adopts an appropriate retransmission scheme on each system protocol layer to improve reliability of data transmission. In each system protocol layer, the retransmission scheme operates in independently other layers and operates based on the parameters without reference to end-to-end performance of wireless communication system. For this reason, it is difficult to design the optimal system parameters that satisfy the QoS requirements for each service class. Thus, the performance analysis of wireless communication system is needed to design the optimal system parameters according to the end-to-end QoS requirements for each service class. In this paper, we derive the mathematical model to formulate the end-to-end performance of wireless communication system. We also evaluate the performance at the MAC and transport layers in terms of average spectral efficiency and average transmission delay. Based on the results of performance evaluations, we design the optimal system parameters according to the QoS requirements of service classes. From the results, the HARQ combined with AMC is appropriate for the delay-sensitive service and the ARQ combined with AMC is appropriate for a service that is insensitive to transmission delay. Also, the TCP can be applied for the delay-insensitive service only.

System-Level Performance of Interference Alignment

Capitalizing on the analytical potency of stochastic geometry and on some new ideas to model intercell interference, this paper presents analytical expressions that enable quantifying the spectral efficiency of interference alignment (IA) in cellular networks without the need for simulation. From these expressions, the benefits of IA are characterized. Even under favorable assumptions, IA is found to be beneficial only in very specific and relatively infrequent network situations, and a blanket utilization of IA is found to be altogether detrimental. Applied only in the appropriate situations, IA does bring about benefits that are significant for the users involved but relatively small in terms of average spectral efficiency for the entire system.

AVERAGE CHANNEL CAPACITY OF FREE-SPACE OPTICAL MIMO SYSTEMS OVER ATMOSPHERIC TURBULENCE CHANNELS

In this paper, we theoretically analyze the performance of multiple-input multiple-output (MIMO) free-space optical (FSO) systems. The MIMO/FSO average channel capacity (ACC), which is expressed in terms of average spectral efficiency (ASE) is derived taking into account the atmospheric turbulence effects on the MIMO/FSO channel. They are modeled by log-normal and the gamma-gamma distributions for the cases of weak-to-strong turbulence conditions. We quantitatively discuss the influence of turbulence strength, link distance, and different MIMO configurations on the system ASE. Numerical and computer simulation results are presented in order to verify the validity of the mathematical analysis.

Performance Analysis of MIMO/FSO Systems Using SC-QAM Signaling over Atmospheric Turbulence Channels

SUMMARY We theoretically study the performance of multiple-input multiple-output (MIMO) free-space optical (FSO) systems using subcarrier quadrature modulation (SC-QAM) signaling. The system average symbolerror rate (ASER) is derived taking into account the atmospheric turbulence effects on the MIMO/FSO channel, which is modeled by log-normal and the gamma-gamma distributions for weak and moderate-to-strong turbulence conditions. We quantitatively discuss the influence of index of refraction structure parameter, link distance, and different MIMO configurations on the system ASER. We also analytically derive and discuss the MIMO/FSO average (ergodic) channel capacity (ACC), which is expressed in terms of average spectral efficiency (ASE), under the impact of various channel conditions. Monte Carlo simulations are also performed to validate the mathematical analysis, and a good agreement between numerical and simulation results is confirmed.

On the performance of adaptive modulation in cognitive radio networks

We study the performance of cognitive radio networks (CRNs) when incorporating adaptive modulation at the physical layer. Three types of CRNs are considered, namely opportunistic spectrum access (OSA), spectrum sharing (SS) and sensing-based SS. We obtain closed-form expressions for the average spectral efficiency achieved at the secondary network and the optimal power allocation for both continuous and discrete rate types of adaptive modulation assuming perfect channel state information. The obtained numerical results show the achievable performance gain in terms of average spectral efficiency and the impact on power allocation when adaptive modulation is implemented at the physical layer that is due to the effect of the cut-off level that is determined from the received signal-to-noise ratio for each CRN type. The performance assessment is taking place for different target bit error rate values and fading regions, thereby providing useful performance insights for various possible implementations.

SINR and Throughput Analysis for Random Beamforming Systems with Adaptive Modulation

In this paper, we derive the exact probability distribution of post-scheduling signal-to-interference-plus-noise ratio (SINR) considering both user feedback and scheduling. We also develop an optimized adaptive modulation scheme in orthogonal random beamforming systems with M transmit antennas and K single-antenna users. The exact probability distributions of each user's feedback SINR and the exact post-scheduling SINR are derived rigorously by direct integration and multinomial distribution. It is also shown that the derived cumulative distribution function (CDF) of the post-scheduling SINR happens to be identical to the the existing approximate CDF for SINR higher than 0 dB. The closed form expressions of system performance, such as average spectral efficiency (ASE) and average bit error ratio (A-BER), are derived using the CDF of the post-scheduling SINR. The optimal SINR thresholds that maximize the ASE with a target A-BER constraint are solved using the derived closed form CDF and a Lagrange multiplier. Key contributions of this paper include the derivation of the exact CDF of post-scheduling SINR by direct integration, and its application to an optimized adaptive modulation based on a Lagrange multiplier. Simulations show the correspondence between theoretical and empirical CDF's, and the performance improvement of the proposed adaptive modulation method in terms of ASE.

Dynamic rate-adaptive MIMO mode switching between spatial multiplexing and diversity

In this article, we propose a dynamic multiple-input multiple-output (MIMO) mode switching scheme between spatial multiplexing and diversity modes, which also includes adaptive modulation. At each transmission, we select the modulation level and the MIMO mode that maximize the spectral efficiency while satisfying a given target bit error rate. The dynamic MIMO mode scheme considers instantaneous spectral efficiency whereas the conventional static scheme considers only the average SNR. As for adaptive modulation, a new method is proposed to compute the SNR thresholds for adaptive modulation in each MIMO mode, and it can avoid the computational difficulty of the conventional Lagrangian (optimal) method at high average SNR. To deal with the case where the rates of the two MIMO modes are the same, we also propose a new measure based on the BER exponent, which has lower computational complexity than a conventional measure. Numerical results show that the proposed dynamic mode switching improves over the conventional static mode switching in terms of average spectral efficiency.

Performance analysis of decode-and-forward relaying schemes with adaptive quadrature amplitude modulation (QAM)

In this study, the authors propose two schemes to enhance the spectral efficiency of the decode-and-forward adaptive relaying with adaptive modulation. The first scheme, called the minimum error rate scheme, uses cooperative transmission all the time to achieve transmit diversity whereas the second scheme, called the maximum spectral efficiency scheme, tries to avoid cooperative transmission if the spectral efficiency cannot be improved. For each scheme, the authors introduce a policy that depends on the channel state information of each link. They provide performance analysis in terms of average spectral efficiency, average bit error rate and outage probability over independent non-identically Rayleigh fading channels. Our analysis is verified by simulation results. These results show that our proposed schemes lead to an improvement in the performance of cooperative wireless systems.

Cross-Layer Design in Dynamic Spectrum Sharing Systems

We consider a dynamic spectrum sharing system consisting of a primary user, whose licensed spectrum is allowed to be accessed by a secondary user as long as it does not violate the prescribed interference limit inflicted on the primary user. Assuming the Nakagami-m block-fading environment, we aim at maximizing the performance of secondary user's link in terms of average spectral efficiency (ASE) and error performance under the specified packet error rate (PER) and average interference limit constraints. To this end, we employ a cross-layer design policy which combines adaptive power and coded discrete M-QAM modulation scheme at the physical layer with a truncated automatic repeat request (ARQ) protocol at the data link layer, and simultaneously satisfies the aforementioned constraints. Numerical results affirm that the secondary link of spectrum sharing system combining ARQwith adaptive modulation and coding (AMC) achieves significant gain in ASE depending on the maximum number of retransmissions initiated by the ARQ protocol. The results further indicate that the ARQ protocol essentially improves the packet loss rate performance of the secondary link.

Analysis of Adaptive MIMO Transmit Beamforming Under Channel Prediction Errors Based on Incomplete Lipschitz–Hankel Integrals

This paper provides new results for a family of incomplete Lipschitz-Hankel integrals (ILHIs) which also lead to the evaluation of certain integrals involving the generalized Marcum Q function. These mathematical results are then applied to analyze the bit error rate (BER) of adaptive modulation over multiple-input-multiple-output (MIMO) fading channels under imperfect channel state information (CSI). A novel exact closed-form expression for the average BER of adaptive modulation under MIMO transmit beamforming with maximal ratio combining, assuming prediction errors at the receiver for the adaptation CSI required by the transmitter, is obtained. The benefit of this result with respect to previous analysis is threefold. First, the expression is an exact closed form. Second, it is applicable to any antenna configuration, and third, it allows a design improvement of the cutoff SNR thresholds, which leads to better system performance in terms of average spectral efficiency at no extra cost.