Analysis and Optimization of Random Caching in Large-Scale Wireless Networks with Multiple Receive Antennas

To improve signal-to-interference ratio (SIR) and make better use of file diversity provided by random caching, we consider two types of linear receivers, i.e., maximal ratio combining (MRC) receiver and partial zero forcing (PZF) receiver, at users in a large-scale cache-enabled single-input multi-output network. First, for each receiver, by utilizing tools from stochastic geometry, we derive a tractable expression and a tight upper bound for the successful transmission probability (STP). In the case of the MRC receiver, we also derive a closed-form expression for the asymptotic outage probability in the low SIR threshold regime. Then, for each receiver, we maximize the STP. In the case of the MRC receiver, we consider the maximization of the tight upper bound on the STP by optimizing the caching probabilities, which is a non-convex problem. We obtain a stationary point, by solving an equivalent difference of convex programming problem using concave-convex procedure. We also obtain a closed-form asymptotically optimal solution in the low SIR threshold regime. In the case of the PZF receiver, we consider the maximization of the tight upper bound on the STP by optimizing the caching probabilities and the degrees of freedom allocation (for boosting signal power and canceling interference), which is a mixed discrete-continuous problem. Based on structural properties, we obtain a low-complexity near optimal solution by using an alternating optimization approach. The analysis and optimization results reveal the impact of antenna resource at users on random caching.

Efficient dissemination of videos is an important problem for mobile telecom carriers. In this paper, to facilitate massive video dissemination, we study joint caching and multicasting for multi-quality videos encoded using two video encoding techniques, namely, scalable video coding (SVC) and HEVC or H.264 as in dynamic adaptive streaming over HTTP (DASH) respectively, in a large-scale wireless network. First, for each type of video, we propose a random caching and multicasting scheme, carefully reflecting the relationship between layers of an SVC-based video or descriptions of a DASH-based video. Then, for each type of video, we derive tractable expressions for the successful transmission probability in the general and high user density regions, respectively, utilizing tools from stochastic geometry. The analytical results reveal that in the high user density region, the marginal increase of the successful transmission probability with respect to the caching probability of a video with a certain quality reduces when the caching probability increases. Next, for each type of video, we consider the maximization of the successful transmission probability in the high user density region, which is a convex problem with an exceedingly large number of optimization variables. We propose a two-stage optimization method to obtain a low-complexity near-optimal solution by solving a relaxed convex problem and a related packing problem. The optimization results reveal the impact of the caching gain of a layer for an SVC-based video or a description for a DASH-based video on its caching probability. Finally, we show that the proposed solutions for SVC-based and DASH-based videos achieve significant performance gains over baseline schemes in the general and high user density regions, and demonstrate their respective operating regions, using numerical results based on real video sequences.

Wirelessly powered backscatter communication (WP-BackCom) enables battery-free Internet of Things (IoT) nodes to passively modulate and backscatter information on the energy signals transmitted by power beacons (PBs) and to harvest energy for realizing energy self-sustainability. It has been deemed a promising solution for the large-scale deployment of IoT nodes. In this paper, we exploit stochastic geometry (SG) to develop a tractable framework to evaluate the successful transmission probability in WP-BackCom while considering the imperfect successive interference cancellation (SIC) at each gateway (GW) and the non-linear energy harvesting (EH) model and energy-causality constraint at each backscatter user (BU). The successful transmission probability is defined as the probability for the event that not only the BU can harvest sufficient power from PBs for sustaining its operation but also the backscattered information can be successfully decoded by the GW. We derive the active probability into a closed form and then obtain the successful transmission probability based on the random spectrum access (RSA) policy. The closed-form expression for the successful transmission probability is derived under three special cases. We also devise a closed-form expression for the sub-optimal reflection coefficient to obtain a sub-optimal successful transmission probability. The analysis reveals that the sub-optimal reflection coefficient increases with the SIC coefficient. Numerical simulations validate the correctness of the above theoretical derivations and examine the impacts of various parameters on the successful transmission probability.

We develop an analytical framework to derive the meta distribution and moments of the conditional success probability (CSP), which is defined as success probability for a given realization of the transmitters, in large-scale co-channel uplink and downlink non-orthogonal multiple access (NOMA) networks with one NOMA cluster per cell. The moments of CSP translate to various network performance metrics such as the standard success or signal-to-interference ratio (SIR) coverage probability (which is the 1-st moment), the mean local delay (which is the −1st moment in a static network setting), and the meta distribution (which is the complementary cumulative distribution function of the success or SIR coverage probability and can be approximated by using the 1st and 2nd moments). For the uplink NOMA network, to make the framework tractable, we propose two point process models for the spatial locations of the inter-cell interferers by utilizing the base station (BS)/user pair correlation function. We validate the proposed models by comparing the second moment measure of each model with that of the actual point process for the inter-cluster (or inter-cell) interferers obtained via simulations. For downlink NOMA, we derive closed-form solutions for the moments of the CSP, success (or coverage) probability, mean local delay, and meta distribution for the users. As an application of the developed analytical framework, we use the closed-form expressions to optimize the power allocations for downlink NOMA users in order to maximize the success probability of a given NOMA user with and without latency constraints. Closed-form optimal solutions for the transmit powers are obtained for two-user NOMA scenario. We note that maximizing the success probability with latency constraints can significantly impact the optimal power solutions for low SIR thresholds and favor orthogonal multiple access.

The per user carrier-to-interference ratio (CINR) enhancement in the reverse link (mobile to base station) of a CDMA communications system is analyzed using different antenna array spatial combining algorithms: optimum combining (OC) versus maximal ratio combining (MRC) in a multi-rate (combined voice and data users) multi-antenna scenario. Many low data voice users and a single dominant high data user are used to achieve a high degree of colored spatial interference in the analysis. The ratio of the CINR for OC versus MRC is directly analyzed, ie, Z=CINR/sub OC//CINR/sub MRC/ instead of separate analysis of each CINR term: CINR/sub OC/ and CINR/sub MRC/ with later comparison. Exact solutions are derived for the statistics of a per user CINR/sub OC//CINIR/sub MRC/ improvement, as a function of the high-level interference power to background noise, and is compared with CDMA reverse link Monte Carlo simulations.

On the successful transmission probability of cooperative cognitive radio ad hoc networks

Caching and multicasting at base stations are two promising approaches to support massive content delivery over wireless networks. However, existing analysis and designs do not fully explore and exploit the potential advantages of the two approaches. In this paper, we consider the analysis and optimization of caching and multicasting in a large-scale cache-enabled wireless network. We propose a random caching and multicasting scheme with a design parameter. By carefully handling different types of interferers and adopting appropriate approximations, we derive a tractable expression for the successful transmission probability in the general region, utilizing tools from stochastic geometry. We also obtain a closed-form expression for the successful transmission probability in the high signal-to-noise ratio (SNR) and user density region. Then, we consider the successful transmission probability maximization, which is a very complex non-convex problem in general. Using optimization techniques, we develop an iterative numerical algorithm to obtain a local optimal caching and multicasting design in the general region. To reduce complexity and maintain superior performance, we also derive an asymptotically optimal caching and multicasting design in the asymptotic region, based on a two-step optimization framework. Finally, numerical simulations show that the asymptotically optimal design achieves a significant gain in successful transmission probability over some baseline schemes in the general region.

Heterogeneous cellular networks (HCNs) constitute a necessary step in the evolution of cellular networks. In this paper, we apply the signal-to-interference ratio (SIR) meta distribution framework for a refined SIR performance analysis of HCNs, focusing on K-tier heterogeneous cellular networks based on the homogeneous independent Poisson point process (HIP) model, with range expansion bias (offloading bias) in each tier. Expressions for the b-th moment of the conditional success probability for both the entire network and each tier are derived, based on which the exact meta distributions and the beta approximations are evaluated and compared. Key performance metrics including the mean success probability, the variance of the conditional success probability, the mean local delay and the asymptotic SIR gains of each tier are obtained. The results show that the biases are detrimental to the overall mean success probability of the whole network and that the b-th moment curve (versus the SIR threshold) of the conditional success probability of each tier can be excellently approximated by the horizontal shifted versions of the first moment curve of the single-tier PPP network. We also provide lower bounds for the region of the active probabilities of the base stations to keep the mean local delay of each tier finite.

This paper considers the uplink of a single-cell large-scale multiuser multiple-input multiple-output (MU-MIMO) system. The transmitted data is detected by linear receivers at the base station (BS), that is, maximum ratio combining (MRC), zero-forcing (ZF) and minimum mean square error (MMSE). New non-asymptotic outage expressions that are valid for any number of BS antennas are derived. It is shown that the MMSE scheme always achieves the best outage performance, and the ZF scheme outperforms the MRC scheme in the high signal-to-noise-ratio (SNR) regime, while the opposite holds in the low SNR regime. We also demonstrate that when the number of BS antennas is very large and the number of users is fixed, the asymptotic outage probability tends to zero, providing that the channel state information (CSI) is perfect. However, if both the number of BS antennas and the number of users grow large, it would be a different matter. Extensive numerical results are presented to verify the theoretical analysis.

Prior results on performance analysis for cognitive relay networks mainly involve perfect channel state information (CSI), which is not readily available. Thus, the effects of outdated CSI on the performance of a multi-antenna multi-relay cognitive radio system are investigated in this work. To exploit the benefits of multiple antennas, collaborative zero-forcing beamforming at the secondary source is proposed to enhance the system performance under the outdated CSI. At the destination, the maximum ratio combining (MRC) diversity scheme is adopted. The Nth best relay selection strategy is applied before the secondary data transmission process. Closed-form expressions for the exact and asymptotic outage probabilities are derived for the secondary user over the Rayleigh fading in the first hop and Nakagami-m fading in the second hop with and without feedback delay. These analytical results can reveal the system diversity order and coding gain. Monte Carlo simulations are carried out to verify the correctness of our analysis. These new analytical results can reveal insights into the characteristics of the proposed system over the outdated fading channels, and can provide useful design criteria for relay-assisted spectrum sharing networks.

In this paper we consider a multi relay Decode and Forward (DF) relay network assisted by Hybrid automatic repeat request (HARQ) in a Rayleigh block fading environment. The system uses an incremental relaying strategy in which the best relay is selected to cooperate with source. A Space-Time Block coding (STB) is used for cooperation between source and selected relay to transmit the data to the destination. Relays and destination use maximum ratio combining (MRC) technique to decode the sent message using previously received versions. We derive a closed-form expression of asymptotic outage probability at high Signal-to-Noise Ratio (SNR) regime. We also derive the average delay and throughput in a delay constrained application. The derivation method is based on the Laplace transform, which proves to be a very effective analytical tool when combined with the properties of the special functions. In addition, we investigate the optimum power allocation strategy to minimize the outage probability and consequently maximize the average throughput perceived by the end user. The simulation results show that the obtained analytical bound for the outage probability is very tight at high SNR regime. In addition the proposed power allocation scheme clearly outperforms the equal power allocation.

Exact outage probability analysis for equal-gain combining (EGC) over lognormal fading channels results in multi-fold integrals, and traditional asymptotic analysis techniques cannot work for lognormal fading channels due to the channels' infinite diversity order. In this work, we derive a closed-form asymptotic outage probability expression for dual-branch EGC over correlated lognormal fading channels with different statistics. The new result reveals insights into the long-standing problem of asymptotic analysis for correlated lognormal fading channels, paving the way for analysis on more general channel models. The result also provides an efficient way to evaluate the performance of dual-branch EGC over correlated and nonidentically distributed lognormal channels at high signal-to-noise ratio.

Existing asymptotic analysis techniques fail to provide closed-form asymptotic outage probability expressions for lognormal fading channels due to the fact that lognormal fading channel distributions have an infinite diversity order. In this work, we develop a new analytical technique to study the asymptotic outage probability of maximum-ratio combining and equalgain combining over independent lognormal fading channels. The derived closed-form asymptotic expressions, which can be expressed in terms of the well-known Marcum-Q function, are accurate in high signal-to-noise ratio (SNR) regimes. The results reveal insights into the long-standing problem of asymptotic analyses for diversity systems over lognormal fading channels, and can help circumvent the time-consuming Monte Carlo simulation and numerical integration in large SNR region.

This paper investigates the impact of the polarization on the achievable throughput and the probability of successful transmission in the cellular network architectures. A channel link model is proposed in the specific case of Rayleigh-faded communication links. More precisely, we propose a closed-form expression for the link probability of success with respect to the topology of the deployment and the channel characteristics. The per-node throughput is analyzed and the gain achieved by using two different polarization modes is discussed. It turns out that, for uniform random placement of the nodes in a scenario where two cellular networks are deployed on a same location, the diversity of polarization ensures that the networks can be operate as if they were disjoint.

Antenna diversity techniques are used in wireless systems to combat the effects of fading. Signals from multiple receiver antennas are combined to achieve an improved average SNR. maximal ratio combining (MRC) technique is known to give a better SNR gain than Selection Combining (SC) technique. This improved performance of MRC comes at the cost of multiple receiver chains which implies increased receiver complexity and cost. In this paper we compare SC with MRC for three antennas in terms of receiver area and power cost. We show that for the same bit-error rate (BER) performance, SC requires roughly 60% lesser area and 40% lesser power consumption.