ETPL SNP -001
Lifetime and Energy Hole Evolution Analysis in Data-Gathering Wireless Sensor Networks
Network lifetime is a crucial performance metric to evaluate data-gathering wireless sensor networks (WSNs) where battery-powered sensor nodes periodically sense the environment and forward collected samples to a sink node. In this paper, we propose an analytic model to estimate the entire network lifetime from network initialization until it is completely disabled, and determine the boundary of energy hole in a data-gathering WSN. Specifically, we theoretically estimate the traffic load, energy consumption, and lifetime of sensor nodes during the entire network lifetime. Furthermore, we investigate the temporal and spatial evolution of energy hole and apply our analytical results to WSN routing in order to balance the energy consumption and improve the network lifetime. Extensive simulation results are provided to demonstrate the validity of the proposed analytic model in estimating the network lifetime and energy hosle evolution process.
ETPL SNP - 002
Dynamic Spectrum Allocation for the Downlink of OFDMA-Based Hybrid-Access Cognitive Femtocell Networks
The cognitive femtocell has emerged as an exciting technology to solve the indoor coverage problem in future cellular networks. Recently, several technical issues for the cognitive femtocell have been studied, e.g., spectrum sharing and interference mitigation. However, the incentive method that is very important for practical hybrid access cognitive femtocell deployment has not been well investigated. In this paper, we propose a new dynamic spectrum allocation method for the hybrid access cognitive femtocell. In the proposed method, the macro base station (BS) allocates a portion of subchannels to the femto access point (FAP) to spur the FAP to serve the macro users (MUs). Then, the FAP allocates the subchannels and power to maximize the femtocell network utility, whereas the throughput of the served MUs is guaranteed. Moreover, we formulate the corresponding resource allocation problem as a sum-utility maximization problem and propose an optimization method to solve it via the dual decomposition method. Simulation results show that both the wireless service provider and the femtocell could benefit from the proposed method.
ETPL SNP -003
Distributed Topology Control with Lifetime Extension Based on NonCooperative Game for Wireless Sensor Networks
In a large and complex distributed sensor network, the individual sensor directly communicates only with its neighboring sensors. Despite being restricted to such local communications, the network itself should be self-organizing to maintain certain desirable properties, such as network connectivity and lifetime maximization. Topology control is a technique to determine the optimal transmit parameters for each sensor, such that the network topology has the best possible network performance. In this paper, we investigate a dynamic topology control scheme to improve the network lifetime for wireless sensor networks in the presence of selfish sensors. A non-cooperative game aided topology control approach is developed for designing energy-efficient and energy balanced network topologies dynamically. Each sensor in the topology control game tries to minimize its unwillingness for constructing a connected network according to its residual energy and transmit power. We prove the existence of Nash equilibrium (NE) and demonstrate that the NE is Pareto optimal as well. Specifically, a fully distributed algorithm-topology control with lifetime extension (TCLE)-is proposed to construct dynamic network topologies. The topologies derived by TCLE algorithm can improve the network lifetime significantly as compared with existing algorithms. Simulations demonstrate the efficiency of our TCLE algorithm.
ETPL SNP - 004
On the Capacity of the Intensity-Modulation Direct-Detection Optical Broadcast Channel
The capacity of the intensity-modulation direct-detection optical broadcast channel (OBC) is investigated, under both average and peak intensity constraints. An outer bound on the capacity region is derived by adapting Bergmans' approach to the OBC. Inner bounds are derived by using superposition coding with either truncated-Gaussian (TG) distributions or discrete distributions. While the discrete distribution achieves higher rates, the TG distribution leads to a simpler representation of the achievable rate region. At high signal-to-noise ratio (SNR), it is shown that the TG distribution is nearly optimal. It achieves the symmetric-capacity within a constant gap (independent of SNR), which approaches half a bit as the number of users grows. It also achieves the capacity region within a constant gap. At low SNR, it is shown that on-off keying (OOK) with time-division multiple-access (TDMA) is optimal. This is interesting in practice since both OOK and TDMA have low complexity. At moderate SNR (typically [0, 8] dB), a discrete distribution with a small alphabet size achieves fairly good performance.
ETPL SNP -005
Modified MUSIC Algorithm for DOA Estimation with Nystrรถm Approximation
Multiple signal classification (MUSIC) can be seen as one of the most popular solutions to the direction-of-arrival estimation problem in array signal processing. Traditionally, this method utilizes the whole array observations to construct the noise subspace. In this letter, based on the randomly chosen sensors outputs, we exploit the Nystrรถm method to approximate the noise subspace, and develop a low-complexity modified MUSIC version for far-field sources localization. Computer simulations confirm that the novel algorithm using only one-fourth sensors outputs provides almost the same estimation performance as its traditional version.
ETPL SNP - 006
New Beam forming and Relay Selection for Two-Way Decode-andForward Relay Networks
Multiple access broadcasting (MABC) is a spectral efficient protocol in a two-way relay channel (TWRC). The drawback of this protocol in decode-and-forward (DF) mode is decoding complexity at the relay side. Erroneous decoding at the relay can lead to error propagation that degrades the performance of all relay networks operating in the DF mode. In this paper, a maximum likelihood (ML) detector at the multiple-antenna relay is used, and it is proved that this decoding rule can achieve full diversity order at the multiple access (MAC) phase of the MABC protocol. Then, a new beam forming algorithm named as channel alignment is proposed, and it is shown that it achieves full diversity order. A new relay selection algorithm is proposed, and a tight upper bound for the bit error rate (BER) of this scheme is derived. It is proved that it achieves full diversity order. The analytical results and BER performance of the proposed schemes are investigated and compared through simulations.
ETPL SNP -007
Phase-Rotation-Aided Relay Selection in Two-Way Decode-and-Forward Relay Networks
This paper proposes a relay selection (RS) scheme that aims to improve the end-to-end symbol error rate (SER) performance of a two-way relay network (TWRN). The TWRN consists of two singleantenna sources and multiple relays employing a decode-and-forward (DF) protocol. It is shown that the SER performance is determined by the minimum decision distance (DD) observed in the TWRN. However, the minimum DD is likely to be made arbitrarily small by channel fading. To tackle this problem, a phase rotation (PR)-aided RS scheme is proposed to enlarge the minimum DD, which, in turn, improves the SER performance. The proposed PR-based scheme rotates the phases of the transmitted symbols of one source and of the selected relay according to the channel state information (CSI), aiming for increasing all DDs to be above a desired bound. The lower bound is further optimized by using a MaxMin-RS criterion associated with the channel gains. It is demonstrated that the PRaided MaxMin-RS approach achieves full diversity gain and improved array gain. Furthermore, compared with the existing DF-based schemes, the proposed scheme allows more flexible relay antenna configurations.
ETPL SNP - 008
Energy-Efficient Optimal Power Allocation for Fading Cognitive Radio Channels: Ergodic Capacity, Outage Capacity, and Minimum-Rate Capacity
Green communications is an inevitable trend for future communication network design, especially for a cognitive radio network. Power allocation strategies are of crucial importance for green cognitive radio networks. However, energy-efficient power allocation strategies in green cognitive radio networks have not been fully studied. Energy efficiency maximization problems are analyzed in delayinsensitive cognitive radio, delay-sensitive cognitive radio, and simultaneously delay-insensitive and delay-sensitive cognitive radio, where a secondary user coexists with a primary user and the channels are fading. Using fractional programming and convex optimization techniques, energy-efficient optimal power allocation strategies are proposed subject to constraints on the average interference power, along with the peak/average transmit power. It is shown that the secondary user can achieve energy efficiency gains under the average transmit power constraint, in contrast to the peak transmit power constraint. Simulation results show that the fading of the channel between the primary user transmitter and the secondary user receiver and the fading of the channel between the secondary user transmitter and the primary user receiver are favorable to the secondary user with respect to the energy efficiency maximization of the secondary user, whereas the fading of the channel between the secondary user transmitter and the secondary user receiver is unfavorable to the secondary user.
ETPL SNP - 009
Throughput Analysis and Optimization of Wireless-Powered Multiple Antenna Full-Duplex Relay Systems
We consider a full-duplex (FD) decode-and-forward system in which the time-switching protocol is employed by the multiantenna relay to receive energy from the source and transmit information to the destination. The instantaneous throughput is maximized by optimizing receive and transmit beamformers at the relay and the time-split parameter. We study both optimum and suboptimum schemes. The reformulated problem in the optimum scheme achieves closed-form solutions in terms of transmit beamformer for some scenarios. In other scenarios, the optimization problem is formulated as a semidefinite relaxation problem and a rank-one optimum solution is always guaranteed. In the suboptimum schemes, the beamformers are obtained using maximum ratio combining, zero-forcing, and maximum ratio transmission. When beamformers have closed-form solutions, the achievable instantaneous and delay-constrained throughput are analytically characterized. Our results reveal that beamforming increases both the energy harvesting and loop interference suppression capabilities at the FD relay. Moreover, simulation results demonstrate that the choice of the linear processing scheme as well as the time-split plays a critical role in determining the FD gains.
ETPL SNP - 010
A Robust Coverage Scheme for UWSNs Using the Spline Function
Wireless sensor technologies have been in development for a long time. Many wireless sensor technology studies have been conducted on improving device performance. Huge technology resources were recently found under the ocean. Previous research methods cannot mapping the underwater environment directly. Underwater wireless sensor networks are being developed for ocean resources deep water exploration. However, little agreement has been reached on an appropriate underwater dedicated distribution model. We focus on accurately depicting 3-D underwater sensor placement based on the coverage issue. Therefore, we design a novel distribution model using the spline function for more accurate underwater wireless sensor placement.
ETPL SNP - 011
Outage Analysis of Co-Operative Two-Path Relay Channels
In this paper, we consider a two-path relay channel (TPRC) with the assistance of two decode-andforward relays alternatively. Upon successfully decoding a source packet, a relay proceeds to forward the decoded packet to the destination, which brings an interference to the other relay. Owing to this inter-relay interference, the decoding result at one relay in the current time slot depends on the decoding result at the other relay in the previous time slot. Exploiting this single-slot memory, the decoding performance of the relays is analyzed using a Markov chain. Furthermore, since the relay transmission is one slot behind the source transmission, the neighboring source packets received at the destination interfere with one another. Then depending on whether a packet is subject to the residual interference from its previous packet, the decoding performance of the destination can be similarly analyzed using a Markov chain. Thus we can obtain the overall outage probability of TPRC in closed-form expressions. Simulation results are provided to demonstrate the performance of the considered TPRC, where the effects of various parameters are evaluated. By comparisons with existing works, a reasonably good performance is achieved for TPRC with only a single-slot delay.
ETPL SNP - 012
Analytical Tractability of Hexagonal Network Model with Random User Location
Explicit derivation of interferences in hexagonal wireless networks has been widely considered intractable and requires extensive computations with system level simulations. In this paper, we fundamentally tackle this problem and explicitly evaluate the downlink interference-to-signal ratio (ISR) for any mobile location m in a hexagonal wireless network, whether composed of omnidirectional or tri-sectorized sites. The explicit formula of ISR is a very convergent series on m and involves the use of Gauss hypergeometric and Hurwitz Riemann zeta functions. Besides, we establish simple identities that well approximate this convergent series and turn out quite useful compared to other approximations in literature. The derived expression of ISR is easily extended to any frequency reuse pattern. Moreover, it is also exploited in the derivation of an explicit form of SINR distribution for any arbitrary distribution of mobile user locations, reflecting the spatial traffic density in the network. Knowing explicitly about interferences and SINR distribution is very useful information in capacity and coverage planning of wireless cellular networks and particularly for macro-cells' layer that forms almost a regular point pattern.
ETPL SNP - 013
Cognitive Wireless Powered Network: Spectrum Sharing Models and Throughput Maximization.
The recent advance in radio-frequency (RF) wireless energy transfer (WET) has motivated the study of wireless powered communication network (WPCN) in which distributed wireless devices are powered via dedicated WET by the hybrid access-point (H-AP) in the downlink (DL) for uplink (UL) wireless information transmission (WIT). In this paper, by utilizing the cognitive radio (CR) technique, we study a new type of CR enabled secondary WPCN, called cognitive WPCN, under spectrum sharing with the primary wireless communication system. In particular, we consider a cognitive WPCN, consisting of one single H-AP with constant power supply and distributed wireless powered users, shares the same spectrum for its DL WET and UL WIT with an existing primary communication link, where the WPCN's WET/WIT and the primary link's WIT may interfere with each other. Under this new setup, we propose two coexisting models for spectrum sharing of the two systems, namely underlay and overlay-based cognitive WPCNs, depending on different types of knowledge on the primary user transmission available for the cognitive WPCN. For each model, we maximize the sumthroughput of the cognitive WPCN by optimizing its transmission under different constraints applied to protect the primary user transmission. Analysis and simulation results are provided to compare the sum-throughput of the cognitive WPCN versus the achievable rate of the primary user under two proposed coexisting models. It is shown that the overlay based cognitive WPCN outperforms the underlay based counterpart, thanks to its fully co-operative WET/WIT design with the primary WIT, while also requiring higher complexity for implementation.
ETPL SNP - 014
Relay-Based Spectrum Sharing With Secondary Users Powered by Wireless Energy Harvesting
Spectrum sharing and energy harvesting are promising techniques to improve the bandwidth and energy efficiencies to meet the ever-growing demand of wireless data transmissions. In this paper, we propose an efficient relay-based spectrum sharing protocol in the cognitive radio network, where the secondary user (SU) can implicitly harvest the radio frequency (RF) energy from the primary user (PU) transmissions. Using the harvested energy, the SU can assist the PU transmission to exchange for the opportunity of spectrum access. Both the Alamouti coding and the superposition coding techniques are adopted by the transmitters to facilitate the primary data relaying and the secondary data transmission simultaneously. The joint decoding and the interference cancelation techniques are adopted by the receivers to retrieve the desired signals. The more power allocated for the primary data relaying, the higher throughput can be achieved for the PU, while the less throughput is available for the SU with less energy remained. The optimal power allocation is numerically determined by maximizing the SU throughput while guaranteeing the PU throughput. Numerical results show that our protocol can greatly improve the system throughput and the impacts of various system settings are revealed for the network deployment.
ETPL SNP - 015
Adaptive Buffer-Aided Distributed Space-Time Coding for Cooperative Wireless Networks
This work proposes adaptive buffer-aided distributed space-time coding schemes and algorithms with feedback for wireless networks equipped with buffer-aided relays. The proposed schemes employ a maximum likelihood receiver at the destination, and adjustable codes subject to a power constraint with an amplify-and-forward cooperative strategy at the relays. The adjustable codes are part of the proposed space-time coding schemes and the codes are sent back to relays after being updated at the destination via feedback channels. Each relay is equipped with a buffer and is capable of storing blocks of received symbols and forwarding the data to the destination if selected. Different antenna configurations and wireless channels, such as static block fading channels, are considered. The effects of using buffer-aided relays to improve the bit error rate (BER) performance are also studied. Adjustable relay selection and optimization algorithms that exploit the extra degrees of freedom of relays equipped with buffers are developed to improve the BER performance. We also analyze the pairwise error probability and diversity of the system when using the proposed schemes and algorithms in a cooperative network. Simulation results show that the proposed schemes and algorithms obtain performance gains over previously reported techniques.
ETPL SNP - 016
On Outage Probability for Two-Way Relay Networks with Stochastic Energy Harvesting
In this paper, we propose an optimal relay transmission policy by using a stochastic energy harvesting (EH) model for the EH two-way relay network, wherein the relay is solar-powered and equipped with a finite-sized battery. In this policy, the long-term average outage probability is minimized by adapting the relay transmission power to the wireless channel states, battery energy amount, and causal solar energy states. The designed problem is formulated as a Markov decision process (MDP) framework, and conditional outage probabilities for both decode-and-forward (DF) and amplify-and-forward (AF) cooperation protocols are adopted as the reward functions. We uncover a monotonic and bounded differential structure for the expected total discounted reward, and prove that such an optimal transmission policy has a threshold structure with respect to the battery energy amount in sufficiently high SNRs. Finally, the outage probability performance is analyzed and an interesting saturated structure for the outage performance is revealed, i.e., the expected outage probability converges to the battery empty probability in high SNR regimes, instead of going to zero. Furthermore, we propose a saturation-free condition that can guarantee a zero outage probability in high SNRs. Computer simulations confirm our theoretical analysis and show that our proposed optimal transmission policy outperforms other compared policies.
ETPL SNP - 017
Scheduling and Resource Allocation in Downlink Multiuser MIMOOFDMA Systems
Multiuser MIMO (MU-MIMO) in general, and block diagonalization (BD) in particular, are playing a prominent role toward the achievement of higher spectral efficiencies in modern OFDMA-based wireless networks. The utilization of such techniques necessarily has implications in the scheduling and resource allocation processes taking care of assigning subcarriers, power, and transmission modes to the different users. In this paper, a framework for channel- and queue-aware scheduling and resource allocation for BD-based MU-MIMO-OFDMA wireless networks is introduced. In particular, using an SNR-based abstraction of the physical layer, the proposed design is able to cater for different BD-MUMIMO processing schemes [co-ordinated Tx-Rx (CTR) or receive antenna selection (RAS)], uniform or adaptive power allocation (UPA/APA), continuous or discrete rate allocation (CRA/DRA), and many different scheduling rules. Additionally, the different strategies are complemented by a new greedy user/stream selection algorithm that is shown to perform very close to the optimal user/stream selection policy at a much lower complexity. Results using system parameters typically found in 4G networks reveal that, in most cases, low-complexity solutions (RAS-, UPA-based) achieve a performance close to the one attained by their more complex counterparts (CTR-, APA-based).
ETPL SNP - 018
User Association and Interference Management in Massive MIMO HetNets
Two key traits of 5G cellular networks are much higher base station (BS) densities-especially in the case of low-power BSs-and the use of massive MIMO at these BSs. This paper explores how massive MIMO can be used to jointly maximize the offloading gains and minimize the interference challenges arising from adding small cells. We consider two interference management approaches: joint transmission (JT) with local precoding, where users are served simultaneously by multiple BSs without requiring channel state information exchanges among cooperating BSs, and resource blanking, where some macro BS resources are left blank to reduce the interference in the small cell downlink. A key advantage offered by massive MIMO is channel hardening, which enables to predict instantaneous rates a priori. This allows us to develop a unified framework, where resource allocation is cast as a network utility maximization (NUM) problem, and to demonstrate large gains in cell-edge rates based on the NUM solution. We propose an efficient dual subgradient based algorithm, which converges towards the NUM solution. A scheduling scheme is also proposed to approach the NUM solution. Simulations illustrate more than 2x rate gain for 10th percentile users vs. an optimal association without interference management.
ETPL SNP - 019
Throughput Performance Optimization of Super Dense Wireless Networks With the Renewal Access Protocol
As a promising solution for handling super dense wireless networks, wireless local area networks (WLANs) have been intensively considered due to their wide availability. However, the contentionbased MAC protocol in WLANs should be modified because of its inefficiency. To this end, we consider a recently proposed novel MAC protocol called the renewal access protocol (RAP). With the RAP, we analyze two strategies for resolving collisions efficiently and achieving optimal throughput performance in super dense WLANs: strategies without and with grouping. First, we analyze the asymptotic behavior of the RAP itself (i.e., without grouping) as the number of terminals goes to infinity. We show that the RAP can achieve optimal throughput even in super dense WLANs and the relevant optimal access probability can be derived in a closed form. Second, we propose a grouping strategy in the RAP called the grouped RAP (G-RAP). While a grouping strategy in the IEEE 802.11ah standard is based on time division, our G-RAP is based on transmission attempts. So the G-RAP does not waste channel resources. We show that the G-RAP achieves the optimal network throughput for any group structure if terminals use the optimal access probability that we derive. Our analytical results are validated by simulation.
ETPL SNP - 020
An optimal power control algorithm for STDMA MAC protocols in multihop wireless networks
Multihop spatial time division multiple access (STDMA) medium access control (MAC) protocols constitute an important building block of wireless networks. There are not many practical power control algorithms that can optimally tradeoff power consumption against transmission rates with a reasonable computational complexity. In this paper, we introduce an energy-efficient distributed power control algorithm for STDMA MAC protocols. The motivation for this study is two fold, namely, maximizing the spatial reuse of the system resources and maximizing power efficiency. We develop a mathematical formulation for maximizing spatial reuse and power efficiency under discrete SINR and rate constrains. After proving that power is a convex function of data rates in our problem, we demonstrate that our problem in simultaneous transmission environments can be reduced to a linear programming (LP) problem. Then, we solve this LP problem using dynamic programming (DP). Finally, based on our proposed solution, we propose a low complexity optimal power control (OPC) algorithm which can be generically embedded within any existing STDMA MAC protocol. Through analytical and experimental studies, we show that our power control algorithm cannot only significantly improve the throughput, power consumption, and delay performance of STDMA MAC protocols compared to their baseline alternatives, but also outperform existing STDMA algorithms.
ETPL SNP - 021
Maximizing the Sum Rate in Cellular Networks Using Multiconvex Optimization
In this paper, we propose a novel algorithm to maximize the sum-rate in interference-limited scenarios where each user decodes its own message with the presence of unknown interferences and noise. The problem of adapting the transmit and receive filters of the users to maximize the sum-rate with a transmit power constraint is nonconvex. Our novel approach is to formulate the sum-rate maximization problem as an equivalent multiconvex optimization problem by adding two sets of auxiliary variables. An iterative algorithm, which alternatingly adjusts the system variables and the auxiliary variables is proposed to solve the multiconvex optimization problem and we show that the algorithm converges to a stationary point. The proposed algorithm is applied to a downlink cellular scenario consisting of several cells each of which contains a base station serving several mobile stations. We examine the two cases, with or without several half-duplex amplify-and-forward relays assisting the transmission. A sum power constraint at the base stations and at the relays are assumed. The applicability of our approach to the individual power constraints case is also shown. Finally, we show that the proposed multiconvex formulation of the sum-rate maximization problem is applicable to many other wireless systems in which the estimated data symbols are multiaffine functions of the system variables.
ETPL SNP - 022
A Randomized Space-Time Spreading Scheme for Massive MIMO Channels
We consider a wireless transmission scheme based on randomized space-time spreading (STS) systems over massive multiple-input multiple-output (MIMO) channels. In the systems, the signals are spread by spreading matrices over time and antenna domains at the transmitter. We propose that the spreading matrices are generated from binary pseudo-noise (PN) and mutual quasi-orthogonal sequences, by partitioning each of the sequences into subsequences treated as real and imagination parts of rows or columns of a spreading matrix. We give a likelihood ascent search (LAS) detector for the STS systems and analyze its computational complexity. The number of multiplication and division operations for the LAS detector does not depend on its iterative process and the number of chips in the bit period. We use Monte Carlo method to solve the bit error rates (BERs) of the STS systems and to count numbers of evaluating bits in the LAS detectors. We choose the system parameters, such as the number of chips in the bit period and the transmission bit rates, according to BER performance and/or the numbers of evaluating bits attained from Monte-Carlo method. With the spreading matrices, the detection, and the suitable parameters, the STS systems achieve BERs near to their single-bit performance, which is the BER of a STS system with a single bit spread by orthonormal sequences at each transmitting antenna. We also compare our systems with V-BLAST-like spatial multiplexing systems with BPSK signals to show the improvement of the BER performance.
ETPL SNP - 023
Antenna Selection for Reliable MIMO-OFDM Interference Alignment Systems: Measurement-Based Evaluation
Interference alignment (IA) is a promising transmission technology enabling, essentially, the maximum achievable degrees of freedom (DOF) in K-user multiple-input-multiple-output (MIMO) interference channels. The ideal DOF of IA systems have been obtained using independent MIMO channels, which is, usually rarely observed in reality, particularly in indoor environments. Therefore, the data sum rate and symbol error-rate of IA are dramatically degraded in real-world scenarios since the correlation between MIMO channels decreases the signal-to-noise ratio (SNR) of the received signal after alignment. For this reason, an acceptable sum rate of IA in real MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM) interference channels was obtained in the literature by modifying the distance between network nodes and the separation between the antennas within each node to minimize the spatial correlation. In this paper, we propose to apply transmit antenna selection to MIMO-OFDM IA systems either through bulk or per-subcarrier selection, aiming at improving the sum-rate and/or error-rate performance under real-world channel circumstances, while keeping the minimum spatial antenna separation of 0.5 wavelengths within each node. Two selection criteria are considered: maximum sum rate (Max-SR) and minimum error rate (Min-ER). To avoid subcarrier imbalance across the antennas of each user, which is caused by per-subcarrier selection, a constrained per-subcarrier antenna selection is operated. Furthermore, a suboptimal antenna selection algorithm is proposed to reduce the computational complexity of the optimal algorithm. An experimental validation of MIMOOFDM IA with antenna selection in an indoor wireless network scenario is presented. The experimental results are compared with deterministic channels that are synthesized using hybrid electromagnetic (EM) ray-tracing models. Our performance evaluation shows that the practical feasibility of MIMO-OFDM IA systems is signific- ntly increased by antenna selection in real-world scenarios.
ETPL SNP - 024
Interference Alignment Improves the Capacity of OFDM Systems
Multiuser orthogonal frequency-division multiplexing (OFDM) and multiple-output multiple-output (MIMO) have been widely adopted to enhance the system throughput and combat the detrimental effects of wireless channels. Interference alignment has been proposed to exploit interference to enable concurrent transmissions of multiple signals. In this paper, we investigate how to combine these techniques to further enhance the system throughput. We first reveal the unique characteristics and challenges brought about by using interference alignment in diagonal channels. We then derive a performance bound for the multiuser (MIMO) OFDM interference alignment system under practical constraints and show how to achieve this bound with a decomposition approach. The superior performance of the proposed scheme is validated with simulations.
ETPL SNP - 025
Impact of User Identities and Access Conditions on Downlink Performance in Closed Small-Cell Networks
This paper investigates the effect of various operation parameters on the downlink user performance in overlaid small-cell networks. The case study considers closed-access small cells (e.g., femtocells), wherein only active authorized user equipment (UE) can be served, each of which is allocated a single downlink channel at a time. On the other hand, the macrocell base station can unconditionally serve macrocell UEs that exist inside its coverage space. The available channels can be shared simultaneously in the macrocell network and the femtocell network. Moreover, a channel can be reused only at the macrocell base station. The analysis provides quantitative approaches to model UE identities, their likelihoods of being active, and their likelihoods of producing interference, considering UE classifications, locations, and access capabilities. Moreover, it develops models for various interference sources observed from effective interference femtocells, considering femtocells capacities and operation conditions. The associated formulations to describe a desired UE performance and the impact of the number of available channels and the adopted channel assignment approach are thoroughly investigated. The results are generally presented for any channel models of interference sources and the desired source of the served UE. Moreover, specific channel models are then adopted, for which generalized closed-form analytical results for the desired UE outage probability performance are obtained. Numerical and simulation results are presented to further clarify the main outcomes of the developed analysis.
ETPL SNP - 026
Dual-Layered MIMO Transmission for Increased Bandwidth Efficiency
A dual-layered downlink transmission scheme is proposed for intrinsically amalgamating multipleinput-multiple-output (MIMO) spatial multiplexing (SMX) with spatial modulation (SM). The proposed scheme employs a classic SMX transmission that is known to offer superior bandwidth efficiency (BE) compared with SM. We exploit receive-antenna-based SM (RSM) on top of this transmission as an enhancement of the BE. The RSM here is applied to the combined spatial and powerlevel domain not by activating and deactivating the RAs but rather by choosing between two power levels {P1, P2} for the received symbols in these antennas. In other words, the combination of symbols received at a power level P1 carries information in the spatial domain in the same manner as the combination of nonzero elements in the receive symbol vector carries information in the RSM transmission. This allows for the coexistence of RSM with SMX, and the results show increased BE for the proposed scheme compared with both SMX and SM. To characterize the proposed scheme, we carry out a mathematical analysis of its performance, and we use this to optimize the ratio between P1 and P2 for attaining the minimum error rates. Our analytical and simulation results demonstrate significant BE gains for the proposed scheme compared with conventional SMX and SM.
ETPL SNP - 027
Robust Equalizer for Multicell Massive MIMO Uplink with Channel Model Uncertainty
We study the robust linear equalizer for the uplink of massive multiple-input-multiple-output (MIMO) systems with multicell pilot reuse. We use the worst-case approach for robust design to combat pilot contamination. When the number of base station (BS) antennas is large, we build a novel model to indicate the relationship between the instantaneous channel matrix and the imperfect channel estimation in the presence of channel model uncertainty. Based on this model, we formulate the robust equalizer design problem into a min-max problem. Furthermore, we transform the min-max problem into an unconstrained one, and the optimality conditions are derived. With the resulting optimality conditions, two iterative algorithms and a simple approximation method are proposed to compute the optimal robust equalizers. Simulations are adopted to evaluate the performance of the proposed algorithms and the approximation method. Compared with the conventional equalizers, the proposed robust equalizers achieve a better bit error rate (BER) performance, particularly in the regime of high signal-to-noise ratio (SNR), where pilot contamination is significant.
ETPL SNP - 028
EM-Based Phase Noise Estimation in Vector OFDM Systems Using Linear MMSE Receivers
Vector orthogonal frequency-division multiplexing (V-OFDM) for single-transmit-antenna systems is a generalization of OFDM where single-carrier frequency-domain equalization and OFDM are just two special cases. Phase noise in a V-OFDM system leads to a common vector block phase error (CVBPE) and an intervector block carrier interference effect. Severe performance degradation may occur if these two effects are not estimated and compensated well. In this paper, blind and semiblind phase noise estimation and compensation in a V-OFDM system is investigated by using the expectationmaximization (EM) algorithm. This is motivated by the fact that the conventional frequency-domain phase noise suppression schemes based on pilot-aided common phase error (CPE) or CVBPE estimation and compensation are not spectrally efficient as the vector block size is increased. Two novel schemes are proposed: One estimates the CVBPE only, and the other estimates the entire phase noise sequence in the time domain. General closed-form formulas for the maximization step of the EM algorithm for the two schemes are derived, and their computational complexity values are analyzed. The performances of the two schemes are investigated by using linear-minimum-mean-square-error (LMMSE) receivers. Simulations show that the two proposed schemes are very effective in estimating and compensating for phase noise in V-OFDM systems. It turns out that the second proposed scheme not only outperforms the traditional CPE or CVBPE schemes but is computationally efficient as well when applied to V-OFDM systems.
ETPL SNP - 029
Stochastic Delay Analysis for Train Control Services in Next-Generation High-Speed Railway Communications System
The communication delay of train control services has a great impact on the track utilization and speed profile of high-speed trains. This paper undertakes stochastic delay analysis of train control services over a high-speed railway fading channel using stochastic network calculus. The mobility model of high-speed railway communications system is formulated as a semi-Markov process. Accordingly, the instantaneous data rate of the wireless channel is characterized by a semi-Markov modulated process, which takes into account the channel variations due to both large- and small-scale fading effects. The stochastic service curve of high-speed railway communications system is derived based on the semiMarkov modulated process. Based on the analytical approach of stochastic network calculus, the stochastic upper delay bounds of train control services are derived with both the moment generating function method and the complementary cumulative distribution function method. The analytical results of the two methods are compared and validated by simulation.