Large-scale Fading Research Articles

Overcoming Large-Scale Fading in Cellular Systems With Network Coordination

The cellular systems with network coordination are known for increasing the cell edge user throughput by processing signals captured by geographically distributed base stations coherently. This concept is also known as macrodiversity or coordinated multipoint (CoMP) in the literature. It is now well known that large-scale fading has a significant influence on the link-level performance of users in multiuser (MU) multicell systems. In this paper, we investigate a channel distribution information (CDI)-based MU multiple-input-multiple-output (MIMO) power control problem in the uplink with joint processing to overcome the large-scale fading in macrodiversity systems. There are many power control algorithms for different variants of this problem, but the CDI-based problem in MU scenario has not been well addressed in the literature. Perhaps, the lack of understanding of the performance of macrodiversity MU systems, in terms of CDI, may have prohibited advanced power control solutions. Despite such analytical difficulties, we propose a simple algorithm for this uplink power control problem, and its accuracy is proved using Monte Carlo simulation.

Robust Design of Coordinated Set Planning with the Non-Ideal Channel

In practical wireless systems, the erroneous channel state information (CSI) sometimes deteriorates the performance drastically. This paper focuses on robust design of coordinated set planning of coordinated multi-point (CoMP) transmission, with respect to the feedback delay and link error. The non-ideal channel models involving various uncertainty conditions are given. After defining a penalty factor, the robust net ergodic capacity optimization problem is derived, whose variables to be optimized are the number of coordinated base stations (BSs) and the divided area’s radius. By the maximum minimum criterion, upper and lower bounds of the robust capacity are investigated. A practical scheme is proposed to determine the optimal number of cooperative BSs. The simulation results indicate that the robust design based on maxmin principle is better than other precoding schemes. The gap between two bounds gets smaller as transmission power increases. Besides, as the large scale fading is higher or the channel is less reliable, the number of the cooperated BSs shall be greater.

5.8 GHz propagation of low‐height wireless links in sea port scenario

Experimental fading measurements were performed in Cadiz Bay, Spain, for a variety of operational scenarios over the sea at the unlicensed 5.8 GHz frequency band. Measurements are based on continuous wave (CW) transmissions with both the transmitter and the receiver installed in typical low-height maritime platforms, such as oceanographic buoys, military ships and boats. Based on the measurements, large-scale and small-scale fading statistics are characterised by cumulative distribution functions (CDFs) and key wireless channel parameters are estimated and discussed. Results show, first, that large-scale fading can be modelled using classical log-normal path-loss models and, secondly, that small-scale fading statistics fits the extreme value distribution (EVD) function when they are expressed in decibel units. This study can be used for practical planning of wireless communications in maritime applications and as an experimental basis for further simulation works.

Optimization of Cluster-Based Cooperative Spectrum Sensing Scheme in Cognitive Radio Networks with Soft Data Fusion

This paper investigates cluster-based cooperative spectrum sensing issues in two-layer hierarchical cognitive radio networks with soft data fusion. We first define a two-phase reporting protocol in the paper. In the first phase, secondary users forward their soft sensing information to cluster heads (CHs) over large-scale fading. In the second phase, all CHs transmit the aggregated soft energy information to the fusion center (FC) with different weights. Thus we derive the network false alarm (FA) and the detection probabilities as functions of the FC decision threshold, the clustering algorithm and different weights. Given a target on the detection probability, minimizing the FA probability is then formulated as a constraint optimization problem within two scenarios including additive white Gaussian noise environment and Rayleigh fading environment. A close-form upper bound of the FA probability is derived and a novel clustering scheme is also proposed for each scenario. Numerical results show that the proposed schemes achieve a satisfying performance.

Performance Analysis of 3D Massive MIMO Cellular Systems with Collaborative Base Station

Massive MIMO have drawn considerable attention as they enable significant capacity and coverage improvement in wireless cellular network. However, pilot contamination is a great challenge in massive MIMO systems. Under this circumstance, cooperation and three-dimensional (3D) MIMO are emerging technologies to eliminate the pilot contamination and to enhance the performance relative to the traditional interference-limited implementations. Motivated by this, we investigate the achievable sum rate performance of MIMO systems in the uplink employing cooperative base station (BS) and 3D MIMO systems. In our model, we consider the effects of both large-scale and small-scale fading, as well as the spatial correlation and indoor-to-outdoor high-rise propagation environment. In particular, we investigate the cooperative communication model based on 3D MIMO and propose a closed-form lower bound on the sum rate. Utilizing this bound, we pursue a “large-system” analysis and provide the asymptotic expression when the number of antennas at the BS grows large, and when the numbers of antennas at transceiver grow large with a fixed ratio. We demonstrate that the lower bound is very tight and becomes exact in the massive MIMO system limits. Finally, under the sum rate maximization condition, we derive the optimal number of UTs to be served.

An Improved Multicell MMSE Channel Estimation in a Massive MIMO System

Massive MIMO is a promising technology to improve both the spectrum efficiency and the energy efficiency. The key problem that impacts the throughput of a massive MIMO system is the pilot contamination due to the nonorthogonality of the pilot sequences in different cells. Conventional channel estimation schemes cannot mitigate this problem effectively, and the computational complexity is increasingly becoming larger in views of the large number of antennas employed in a massive MIMO system. Furthermore, the channel estimation is always carried out with some ideal assumptions such as the complete knowledge of large-scale fading. In this paper, a new channel estimation scheme is proposed by utilizing interference cancellation and joint processing. Highly interfering users in neighboring cells are identified based on the estimation of large-scale fading and then included in the joint channel processing; this achieves a compromise between the effectiveness and efficiency of the channel estimation at a reasonable computational cost, and leads to an improvement in the overall system performance. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

Joint Power and Antenna Selection Optimization in Large Cloud Radio Access Networks

Large multiple-input multiple-output (MIMO) networks promise high energy efficiency, i.e., much less power is required to achieve the same capacity compared to the conventional MIMO networks if perfect channel state information (CSI) is available at the transmitter. However, in such networks, huge overhead is required to obtain full CSI especially for Frequency-Division Duplex (FDD) systems. To reduce overhead, we propose a downlink antenna selection scheme, which selects S antennas from M>S transmit antennas based on the large scale fading to serve K\leq S users in large distributed MIMO networks employing regularized zero-forcing (RZF) precoding. In particular, we study the joint optimization of antenna selection, regularization factor, and power allocation to maximize the average weighted sum-rate. This is a mixed combinatorial and non-convex problem whose objective and constraints have no closed-form expressions. We apply random matrix theory to derive asymptotically accurate expressions for the objective and constraints. As such, the joint optimization problem is decomposed into subproblems, each of which is solved by an efficient algorithm. In addition, we derive structural solutions for some special cases and show that the capacity of very large distributed MIMO networks scales as O\left(K\textrm{log}M\right) when M\rightarrow\infty with K,S fixed. Simulations show that the proposed scheme achieves significant performance gain over various baselines.

Distributed Cooperative Spectrum Sensing in Mixture of Large and Small Scale Fading Channels

In this paper, we study distributed energy detectors for spectrum sensing in cognitive radio networks. We treat the primary signal as unknown and deterministic with a known power and the channels as random with a Nakagami-Lognormal mixture distribution. In other words, the channel gains are modeled as product of two terms corresponding to the small and large-scale fadings. The small-scale terms are all Nakagami and independent for all sensors. Whereas for large-scale fading, sensors in each cluster are assumed to have identical Lognormal terms. We also assume that different clusters have independent large-scale fading. Assuming that the total energies from clusters are received, we investigate four distributed detection strategies: 1) Equal Gain Combining detector (EGCD), 2) Neyman-Pearson detector (NPD) or Likelihood Ratio detector (LRD) for known channel gains, 3) Generalized Likelihood Ratio detector (GLRD) for unknown gains, and 4) Average Likelihood Ratio detector (ALRD) given a priori distribution of channel gains. The simulation results show that the effects of both small and large-scale fadings on sensing performance should be considered simultaneously and confirm that a priori statistical information about large and small-scale fading used in ALRD result in performance improvement compared to EGCD and GLRD.

Development and Performance Evaluation of MMSE MacroDiversity Reception System With Delay Difference Correction

We have been developing a minimum-mean-square-error macrodiversity (MMSE-MD) reception system using distributed remote antennas and radio-on-fiber (RoF) links for use in live broadcasts of road races. The system selects remote antennas with good signal quality and combines their signals based on the MMSE algorithm to combat both small-scale and large-scale fading. For the system to be feasible, we have to consider propagation delay differences among diversity branches due to the RoF links and radio propagation. This paper describes a practical delay difference correction (DDC) technique that can keep signal continuity in any situation, the hardware implementation of an MMSE-MD receiver embodying the technique, and indoor and outdoor performance evaluations. Our prototype receiver perfectly corrected the propagation delay differences among diversity branches without losing signal continuity and maintained MD reception without signal outage across a wide area on an actual road-race course.

Uplink Performance Analysis of Multicell MU-SIMO Systems With ZF Receivers

We consider the uplink of a multicell multiuser single-input multiple-output system (MU-SIMO), where the channel experiences both small- and large-scale fading. The data detection is done by using the linear zero-forcing technique, assuming the base station (BS) has perfect channel state information of all users in its cell. We derive new exact analytical expressions for the uplink rate, the symbol error rate (SER), and the outage probability per user, as well as a lower bound on the achievable rate. This bound is very tight and becomes exact in the large-number-of-antenna limit. We further study the asymptotic system performance in the regimes of high signal-to-noise ratio (SNR), large number of antennas, and large number of users per cell. We show that, at high SNRs, the system is interference limited, and hence, we cannot improve the system performance by increasing the transmit power of each user. Instead, by increasing the number of BS antennas, the effects of interference and noise can be reduced, thereby improving system performance. We demonstrate that, with very large antenna arrays at the BS, the transmit power of each user can be made inversely proportional to the number of BS antennas while maintaining a desired quality of service. Numerical results are presented to verify our analysis.

Intervehicle Communication: Cox-Fox Modeling

Safety message dissemination in a vehicular ad-hoc network (VANET) requires vehicle-to-vehicle (V2V) communication with low latency and high reliability. The dynamics of vehicle passing and queueing as well as high mobility create distinctive propagation characteristics of wireless medium and inevitable uncertainty in space-time patterns of the vehicle density on a road. It is therefore of great importance to account for random vehicle locations in V2V communication. In this paper, we characterize intervehicle communication in a random field of vehicles, where a beacon or head vehicle (transmitter) broadcasts safety or warning messages to neighboring client vehicles (receivers) randomly located in a cluster on the road. To account for a doubly stochastic property of the VANET, we first model vehicle's random locations as a stationary Cox process with Fox's H-distributed random intensity (vehicle concentration) and derive the distributional functions of the lth nearest client's distance from the beacon in such a Fox Cox field of vehicles. We then consolidate this spatial randomness of receiving vehicles into a path loss model and develop a triply-composite Fox channel model that combines key wireless propagation effects such as the distance-dependent path loss, large-scale fading (shadowing), and small-scale fading (multipath fading). In Fox channel modeling, each constituent propagation effect is described as Fox's H-variate, culminating again in Fox's H-variate for the received power or equivalently the instantaneous signal-to-noise ratio at the lth nearest client vehicle. Due to versatility of Fox's H-functions, this stochastic channel model can encompass a variety of well-established or generalized statistical propagation models used in wireless communication; be well-fitted to measurement data in diverse propagation environments by varying parameters; and facilitate a unifying analysis for fundamental physical-layer performances, such as error probability and channel capacity, using again the language of Fox's H-functions. This work serves to develop a unifying framework to characterize V2V communication in a doubly stochastic VANET by averaging both the small- and large-scale fading effects as well as the (random) distance-dependent path losses.

Channel Quality Approximation Based on Shadow Fading Model in GEO Mobile Satellite System

CQI(Channel Quality Indicator) is an essential indicator for AMC(Adaptive Modulation and Coding) technique in LTE. Due to the long delay of GEO satellite channel, CQI prediction is necessary to ensure effective AMC. This paper proposes the approximation from real CQI data containing small scale fading to that containing only large scale fading to do prediction. The concrete correlation features and the difference between the approximation and the original data are all analyzed. Simulation is done for confirmation. It shows that the approximate large scale CQI data is feasible and rational for prediction and ensuring AMC efficiency.

Performance evaluation of receive-diversity free-space optical communications over correlated Gamma–Gamma fading channels

The efficacy of spatial diversity in practical free-space optical communication systems is impaired by the fading correlation among the underlying subchannels. We consider in this paper the generation of correlated Gamma-Gamma random variables in view of evaluating the system outage probability and bit-error-rate under the condition of correlated fading. Considering the case of receive-diversity systems with intensity modulation and direct detection, we propose a set of criteria for setting the correlation coefficients on the small- and large-scale fading components based on scintillation theory. We verify these criteria using wave-optics simulations and further show through Monte Carlo simulations that we can effectively neglect the correlation corresponding to the small-scale turbulence in most practical systems, irrespective of the specific turbulence conditions. This has not been clarified before, to the best of our knowledge. We then present some numerical results to illustrate the effect of fading correlation on the system performance. Our conclusions can be generalized to the cases of multiple-beam and multiple-beam multiple-aperture systems.

Modeling Heterogeneous Network Interference Using Poisson Point Processes

Cellular systems are becoming more heterogeneous with the introduction of low power nodes including femtocells, relays, and distributed antennas. Unfortunately, the resulting interference environment is also becoming more complicated, making evaluation of different communication strategies challenging in both analysis and simulation. Leveraging recent applications of stochastic geometry to analyze cellular systems, this paper proposes to analyze downlink performance in a fixed-size cell, which is inscribed within a weighted Voronoi cell in a Poisson field of interferers. A nearest out-of-cell interferer, out-of-cell interferers outside a guard region, and cross-tier interferers are included in the interference calculations. Bounding the interference power as a function of distance from the cell center, the total interference is characterized through its Laplace transform. An equivalent marked process is proposed for the out-of-cell interference under additional assumptions. To facilitate simplified calculations, the interference distribution is approximated using the Gamma distribution with second order moment matching. The Gamma approximation simplifies calculation of the success probability and average rate, incorporates small-scale and large-scale fading, and works with co-tier and cross-tier interference. Simulations show that the proposed model provides a flexible way to characterize outage probability and rate as a function of the distance to the cell edge.

Adaptive precoding and power allocation in distributed antenna systems with limited feedback

AbstractThis paper introduces the limited feedback precoding into the distributed antenna system and proposes to adapt the predetermined orthogonal space time block codes to the available channel state information at the transmitter. The optimal representation of precoding information, namely the precoder, with least bits therefore becomes the key problem. Inspired by the characteristics of the distributed antenna system, we focus our work on the precoder construction, adaptable in response to the large and small scale fading, such that the symbol error probability is significantly reduced over that of a fixed, non‐adaptive, independent and identically distributed precoder codebook design. Furthermore, a suboptimal power‐loading strategy is presented by minimizing the derived tight upper bound on the average pairwise error probability of the precoded orthogonal space time block codes, which approaches the optimal performance asymptotically without additional channel knowledge other than the available feedback information. We prove that the proposed precoded orthogonal space time transmission scheme can achieve full diversity order. In particular, the robustness of our proposed transmission scheme to channel estimation error and feedback delay is respectively investigated in some detail, and numerical results show that it obviously improves the link reliability and obtains substantial gains even with few bits of feedback in comparison with conventional antenna selection scheme. Copyright © 2013 John Wiley & Sons, Ltd.

Performance Evaluation of WiMAX networks through Large Scale Fading Channel Conditions

WiMAX is an effective metropolitan area broadband access technology, supplying wireless coverage over an area of several kilometers with high data rates. WiMAX technology has introduced WiMAX broadband to provide an alternative to the high cost of broadband connection through cable or DSL. In this paper, simulative investigations have been done for the WiMAX network using different path loss models. Investigations have been done in terms of performance metrics such as path loss, throughput and delay. Considering VoIP as major application, extensive results of different path loss models have been indicated which will help the network engineers in planning and design. General Terms WiMAX network, Path loss models.

이종 네트워크를 위한 Almost Blank Subframes의 성능 분석

이종 네트워크 환경에서 이종셀 간 간섭 제어를 위해 Almost Blank Subframes (ABS)이 제안 되었다. ABS에서는 서브프레임에 대한 자원 할당을 하지 않음으로써 동일 채널 간섭을 줄일 수 있다. 기존 연구에서는 ABS 기술의 성능 평가를 위한 수학적 모델링이 제안되지 않았다. 본 논문에서는 ABS 기술에 대한 수학적 모델을 제시하였다. 분석을 위한 가정에서 OFDMA 기반의 다중 반송파 (multi carrier) 시스템을 가정하였고, large-scale 페이딩을 가정하였다. 성능 평가로써 effective SINR에 대한 누적분포함수를 나타낸다. 시뮬레이션과 분석에 대한 결과 비교를 통해 수학적 모델에 대한 정확도를 보인다. In heterogeneous networks, the almost blank subframes (ABS) for inter-cell interference coordination (ICIC), which can be protected from the CCI due to unutilized subframes (i.e., ABS) is proposed. However, the analytical model for ABS-based systems has not been fully studied yet. In this paper, we derive a new analytical model to evaluate the performance of ABS-based systems. In an analytic model, we assume that each carrier in multicarrier systems, such as in OFDMA, is subject to large-scale fading, which is independent of other carriers. As a performance measure, we present the cumulative distribution function (CDF) for the effective SINR. We show the accuracy of the analytical model via simulation results.

Single-user MIMO versus multi-user MIMO in distributed antenna systems with limited feedback

This article investigates the performance of cellular networks employing distributed antennas in addition to the central antennas of the base station. Distributed antennas are likely to be implemented using remote radio units, which is enabled by a low latency and high bandwidth dedicated link to the base station. This facilitates coherent transmission from potentially all available antennas at the same time. Such distributed antenna system (DAS) is an effective way to deal with path loss and large-scale fading in cellular systems. DAS can apply precoding across multiple transmission points to implement single-user MIMO (SU-MIMO) and multi-user MIMO (MU-MIMO) transmission. The throughput performance of various SU-MIMO and MU-MIMO transmission strategies is investigated in this article, employing a Long-Term evolution (LTE) standard compliant simulation framework. The previously theoretically established cell-capacity improvement of MU-MIMO in comparison to SU-MIMO in DASs is confirmed under the practical constraints imposed by the LTE standard, even under the assumption of imperfect channel state information (CSI) at the base station. Because practical systems will use quantized feedback, the performance of different CSI feedback algorithms for DASs is investigated. It is shown that significant gains in the CSI quantization accuracy and in the throughput of especially MU-MIMO systems can be achieved with relatively simple quantization codebook constructions that exploit the available temporal correlation and channel gain differences.

Sum Rate Analysis of ZF Receivers in Distributed MIMO Systems

The performance of single-cell distributed multiple-input multiple-output (D-MIMO) systems is not only affected by small-scale Rayleigh fading but also from large-scale fading and path-loss. In this paper, we elaborate on the sum rate of D-MIMO systems employing linear zero-forcing receivers, accounting for both large and small-scale fading effects, as well as spatial correlation at the transmit side. In particular, we consider the classical lognormal model and propose closed-form upper and lower bounds on the achievable sum rate. Using these bounds as a starting point, we pursue a "large-system" analysis and provide asymptotic expressions when the number of antennas at the base station (BS) grow large, and when the number of antennas at both ends grow large with a fixed and finite ratio. A detailed characterization in the asymptotically high and low signal to noise ratio regimes is also provided. An interesting observation from our results is that in order to maximize the sum rate, the RPs should be placed at unequal distances to the BS when they experience the same level of shadowing. The resulting closed-form expressions are compared with the corresponding results on MIMO optimal receivers.

Modeling of Communication-Based Train Control (CBTC) Radio Channel With Leaky Waveguide

In urban rail transit systems using communication-based train control (CBTC), leaky waveguide has been used as the propagation medium for the viaduct scenarios, as it can provide better performance and stronger anti-interference ability than free space. Based on the measurements of leaky waveguide, a model of CBTC radio channel with leaky waveguide is proposed in this letter. Our model shows that the large-scale fading is linear, and the path-loss exponent can be approximated by the transmission loss of leaky waveguide. The small-scale fading follows Log-normal distribution. In addition, the corresponding parameters of Log-normal distribution are also determined from the measurement results.