Showing papers on "Channel state information published in 2015"

Fairness for Non-Orthogonal Multiple Access in 5G Systems

Abstract: In non-orthogonal multiple access (NOMA) downlink, multiple data flows are superimposed in the power domain and user decoding is based on successive interference cancellation. NOMA’s performance highly depends on the power split among the data flows and the associated power allocation (PA) problem. In this letter, we study NOMA from a fairness standpoint and we investigate PA techniques that ensure fairness for the downlink users under i) instantaneous channel state information (CSI) at the transmitter, and ii) average CSI. Although the formulated problems are non-convex, we have developed low-complexity polynomial algorithms that yield the optimal solution in both cases considered.

Fairness for Non-Orthogonal Multiple Access in 5G Systems

Abstract: In non-orthogonal multiple access (NOMA) downlink, multiple data flows are superimposed in the power domain and user decoding is based on successive interference cancellation. NOMA's performance highly depends on the power split among the data flows and the associated power allocation (PA) problem. In this letter, we study NOMA from a fairness standpoint and we investigate PA techniques that ensure fairness for the downlink users under i) instantaneous channel state information (CSI) at the transmitter, and ii) average CSI. Although the formulated problems are non-convex, we have developed low-complexity polynomial algorithms that yield the optimal solution in both cases considered.

Capacity Analysis of One-Bit Quantized MIMO Systems With Transmitter Channel State Information

Abstract: With bandwidths on the order of a gigahertz in emerging wireless systems, high-resolution analog-to-digital convertors (ADCs) become a power consumption bottleneck. One solution is to employ low resolution one-bit ADCs. In this paper, we analyze the flat fading multiple-input multiple-output (MIMO) channel with one-bit ADCs. Channel state information is assumed to be known at both the transmitter and receiver. For the multiple-input single-output channel, we derive the exact channel capacity. For the single-input multiple-output and MIMO channel, the capacity at infinite signal-to-noise ratio (SNR) is found. We also derive upper bound at finite SNR, which is tight when the channel has full row rank. In addition, we propose an efficient method to design the input symbols to approach the capacity achieving solution. We incorporate millimeter wave channel characteristics and find the bounds on the infinite SNR capacity. The results show how the number of paths and number of receive antennas impact the capacity.

On the Ergodic Capacity of MIMO NOMA Systems

Abstract: Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access technique for 5G networks due to its superior spectral efficiency. In this letter, the ergodic capacity maximization problem is first studied for the Rayleigh fading multiple-input multiple-output (MIMO) NOMA systems with statistical channel state information at the transmitter (CSIT). We propose both optimal and low complexity suboptimal power allocation schemes to maximize the ergodic capacity of MIMO NOMA system with total transmit power constraint and minimum rate constraint of the weak user. Numerical results show that the proposed NOMA schemes significantly outperform the traditional orthogonal multiple access scheme.

Beam Division Multiple Access Transmission for Massive MIMO Communications

Abstract: We study multicarrier multiuser multiple-input multiple-output (MU-MIMO) systems, in which the base station employs an asymptotically large number of antennas. We analyze a fully correlated channel matrix and provide a beam domain channel model, where the channel gains are independent of sub-carriers. For this model, we first derive a closed-form upper bound on the achievable ergodic sum-rate, based on which, we develop asymptotically necessary and sufficient conditions for optimal downlink transmission that require only statistical channel state information at the transmitter. Furthermore, we propose a beam division multiple access (BDMA) transmission scheme that simultaneously serves multiple users via different beams. By selecting users within non-overlapping beams, the MU-MIMO channels can be equivalently decomposed into multiple single-user MIMO channels; this scheme significantly reduces the overhead of channel estimation, as well as, the processing complexity at transceivers. For BDMA transmission, we work out an optimal pilot design criterion to minimize the mean square error (MSE) and provide optimal pilot sequences by utilizing the Zadoff-Chu sequences. Simulations demonstrate the near-optimal performance of BDMA transmission and the advantages of the proposed pilot sequences.

Exploiting Known Interference as Green Signal Power for Downlink Beamforming Optimization

Abstract: We propose a data-aided transmit beamforming scheme for the multi-user multiple-input-single-output (MISO) downlink channel. While conventional beamforming schemes aim at the minimization of the transmit power subject to suppressing interference to guarantee quality of service (QoS) constraints, here we use the knowledge of both data and channel state information (CSI) at the transmitter to exploit, rather than suppress, constructive interference. More specifically, we design a new precoding scheme for the MISO downlink that minimizes the transmit power for generic phase shift keying (PSK) modulated signals. The proposed precoder reduces the transmit power compared to conventional schemes, by adapting the QoS constraints to accommodate constructive interference as a source of useful signal power. By exploiting the power of constructively interfering symbols, the proposed scheme achieves the required QoS at lower transmit power. We extend this concept to the signal to interference plus noise ratio (SINR) balancing problem, where higher SINR values compared to the conventional SINR balancing optimization are achieved for given transmit power budgets. In addition, we derive equivalent virtual multicast formulations for both optimizations, both of which provide insights of the optimal solution and facilitate the design of a more efficient solver. Finally, we propose a robust beamforming technique to deal with imperfect CSI, that also reduces the transmit power over conventional techniques, while guaranteeing the required QoS. Our simulation and analysis show significant power savings for small scale MISO downlink channels with the proposed data-aided optimization compared to conventional beamforming optimization.

DeepFi: Deep learning for indoor fingerprinting using channel state information

Abstract: With the fast growing demand of location-based services in indoor environments, indoor positioning based on fingerprinting has attracted a lot of interest due to its high accuracy. In this paper, we present a novel deep learning based indoor fingerprinting system using Channel State Information (CSI), which is termed DeepFi. Based on three hypotheses on CSI, the DeepFi system architecture includes an off-line training phase and an on-line localization phase. In the off-line training phase, deep learning is utilized to train all the weights as fingerprints. Moreover, a greedy learning algorithm is used to train all the weights layer-by-layer to reduce complexity. In the on-line localization phase, we use a probabilistic method based on the radial basis function to obtain the estimated location. Experimental results are presented to confirm that DeepFi can effectively reduce location error compared with three existing methods in two representative indoor environments.

Wireless-Powered Relays in Cooperative Communications: Time-Switching Relaying Protocols and Throughput Analysis

Abstract: We consider wireless-powered amplify-and-forward and decode-and-forward relaying in cooperative communications, where an energy constrained relay node first harvests energy through the received radio-frequency signal from the source and then uses the harvested energy to forward the source information to the destination node. We propose time-switching based energy harvesting (EH) and information transmission (IT) protocols with two modes of EH at the relay. For continuous time EH, the EH time can be any percentage of the total transmission block time. For discrete time EH, the whole transmission block is either used for EH or IT. The proposed protocols are attractive because they do not require channel state information at the transmitter side and enable relay transmission with preset fixed transmission power. We derive analytical expressions of the achievable throughput for the proposed protocols. The derived expressions are verified by comparison with simulations and allow the system performance to be determined as a function of the system parameters. Finally, we show that the proposed protocols outperform the existing fixed time duration EH protocols in the literature, since they intelligently track the level of the harvested energy to switch between EH and IT in an online fashion, allowing efficient use of resources.

Optimized Training Design for Wireless Energy Transfer

Abstract: Radio-frequency (RF) enabled wireless energy trans- fer (WET), as a promising solution to provide cost-effective and reliable power supplies for energy-constrained wireless networks, has drawn growing interests recently. To overcome the significant propagation loss over distance, employing multi-antennas at the energy transmitter (ET) to more efficiently direct wireless energy to desired energy receivers (ERs), termed energy beamforming ,i s an essential technique for enabling WET. However, the achievable gain of energy beamforming crucially depends on the available channel state information (CSI) at the ET, which needs to be acquired practically. In this paper, we study the design of an efficient channel acquisition method for a point-to-point multiple- input multiple-output (MIMO) WET system by exploiting the channel reciprocity, i.e., the ET estimates the CSI via dedicated reverse-link training from the ER. Considering the limited energy availability at the ER, the training strategy should be carefully designed so that the channel can be estimated with sufficient accuracy, and yet without consuming excessive energy at the ER. To this end, we propose to maximize the net harvested energy at the ER, which is the average harvested energy offset by that used for channel training. An optimization problem is formulated for the training design over MIMO Rician fading channels, including the subset of ER antennas to be trained, as well as the training time and power allocated. Closed-form solutions are obtained for some special scenarios, based on which useful insights are drawn on when training should be employed to improve the net transferred energy in MIMO WET systems.

Differential Spatial Modulation

Abstract: Spatial modulation (SM) is a newly emerging multiple-input–multiple-output technique that activates only a single antenna for transmission at any time instant and uses the index of the active antenna as an additional information-carrying mechanism. However, by its nature, SM decoding is coherent in that channel state information (CSI) is required at the receiver. In fact, coherent SM decoding can be very complex due to the heavily entangled channel estimation and symbol detection. In this correspondence, a differential SM scheme that completely bypasses any CSI at the transmitter or receiver, while preserving the single active transmit antenna property, is developed. The proposed scheme can be applied to any constant energy constellation such as phase-shift keying (PSK) and to systems with arbitrary numbers of transmit and receive antennas. Simulation results are presented under various system configurations. With the same spectral efficiency, the proposed scheme is capable of paying no more than 3 dB of signal-to-noise ratio penalty compared with coherent SM and outperforming the single-antenna differential PSK and differential space–time coding schemes.

Radio access for ultra-reliable and low-latency 5G communications

Abstract: Fifth generation wireless networks are currently being developed to handle a wide range of new use cases. One important emerging area is ultra-reliable communication with guaranteed low latencies well beyond what current wireless technologies can provide. In this paper, we explore the viability of using wireless communication for low-latency, high-reliability communication in an example scenario of factory automation, and outline important design choices for such a system. We show that it is possible to achieve very low error rates and latencies over a radio channel, also when considering fast fading signal and interference, channel estimation errors, and antenna correlation. The most important tool to ensure high reliability is diversity, and low latency is achieved by using short transmission intervals without retransmissions, which, however, introduces a natural restriction on coverage area.

Constructive Multiuser Interference in Symbol Level Precoding for the MISO Downlink Channel

Abstract: This paper investigates the problem of interference among the simultaneous multiuser transmissions in the downlink of multiple-antenna systems Using symbol-level precoding, a new approach to exploit the multiuser interference is discussed The concept of exploiting the interference between spatial multiuser transmissions by jointly utilizing data information (DI) and channel state information (CSI), in order to design symbol-level precoders, is proposed To this end, the interference between data streams is transformed under certain conditions into useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions We propose a maximum ratio transmission (MRT) based algorithm that jointly exploits DI and CSI to glean the benefits from constructive multiuser interference Subsequently, a relation between the constructive interference downlink transmission and physical layer multicasting is established In this context, novel constructive interference precoding techniques that tackle the transmit power minimization (min-power) with individual SINR constraints at each user's receivers is proposed Furthermore, fairness through maximizing the weighted minimum SINR (max-min SINR) of the users is addressed by finding the link between the min power and max min SINR problems Moreover, heuristic precoding techniques are proposed to tackle the weighted sum rate problem Finally, extensive numerical results show that the proposed schemes outperform other state of the art techniques

Multicast Multigroup Precoding and User Scheduling for Frame-Based Satellite Communications

Abstract: The present work focuses on the forward link of a broadband multibeam satellite system that aggressively reuses the user link frequency resources. Two fundamental practical challenges, namely the need to frame multiple users per transmission and the per-antenna transmit power limitations, are addressed. To this end, the so-called frame-based precoding problem is optimally solved using the principles of physical layer multicasting to multiple co-channel groups under per-antenna constraints. In this context, a novel optimization problem that aims at maximizing the system sum rate under individual power constraints is proposed. Added to that, the formulation is further extended to include availability constraints. As a result, the high gains of the sum rate optimal design are traded off to satisfy the stringent availability requirements of satellite systems. Moreover, the throughput maximization with a granular spectral efficiency versus SINR function, is formulated and solved. Finally, a multicast-aware user scheduling policy, based on the channel state information, is developed. Thus, substantial multiuser diversity gains are gleaned. Numerical results over a realistic simulation environment exhibit as much as 30% gains over conventional systems, even for 7 users per frame, without modifying the framing structure of legacy communication standards.

Achievable Rates of FDD Massive MIMO Systems With Spatial Channel Correlation

Abstract: It is well known that the performance of frequency-division-duplex (FDD) massive MIMO systems with i.i.d. channels is disappointing compared with that of time-division-duplex (TDD) systems, due to the prohibitively large overhead for acquiring channel state information at the transmitter (CSIT). In this paper, we investigate the achievable rates of FDD massive MIMO systems with spatially correlated channels, considering the CSIT acquisition dimensionality loss, the imperfection of CSIT and the regularized-zero-forcing linear precoder. The achievable rates are optimized by judiciously designing the downlink channel training sequences and user CSIT feedback codebooks, exploiting the multiuser spatial channel correlation. We compare our achievable rates with TDD massive MIMO systems, i.i.d. FDD systems, and the joint spatial division and multiplexing (JSDM) scheme, by deriving the deterministic equivalents of the achievable rates, based on the one-ring model and the Laplacian model. It is shown that, based on the proposed eigenspace channel estimation schemes, the rate-gap between FDD systems and TDD systems is significantly narrowed, even approached under moderate number of base station antennas. Compared to the JSDM scheme, our proposal achieves dimensionality-reduction channel estimation without channel pre-projection, and higher throughput for moderate number of antennas and moderate to large channel coherence block length, though at higher computational complexity.

Wireless Information and Energy Transfer for Two-Hop Non-Regenerative MIMO-OFDM Relay Networks

Abstract: This paper investigates the simultaneous wireless information and energy transfer for the non-regenerative multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) relaying system. By considering two practical receiver architectures, we present two protocols, time switching-based relaying (TSR) and power splitting-based relaying (PSR). To explore the system performance limits, we formulate two optimization problems to maximize the end-to-end achievable information rate with the full channel state information (CSI) assumption. Since both problems are non-convex and have no known solution method, we firstly derive some explicit results by theoretical analysis and then design effective algorithms for them. Numerical results show that the performances of both protocols are greatly affected by the relay position. Specifically, PSR and TSR show very different behaviors to the variation of relay position. The achievable information rate of PSR monotonically decreases when the relay moves from the source towards the destination, but for TSR, the performance is relatively worse when the relay is placed in the middle of the source and the destination. This is the first time such a phenomenon has been observed. In addition, it is also shown that PSR always outperforms TSR in such a MIMO-OFDM relaying system. Moreover, the effects of the number of antennas and the number of subcarriers are also discussed.

Performance of an amplify-and-forward dual-hop asymmetric RF–FSO communication system

Abstract: In this work, the performance and the capacity analysis of a fixed-gain amplify-and-forward (AF)-based dual-hop asymmetric radio frequency–free space optical (RF–FSO) communication system is performed. The RF link experiences Nakagami-m fading and the FSO link experiences Gamma–Gamma turbulence. For this mixed RF–FSO cooperative system, novel and finite power series-based mathematical expressions for the cumulative distribution function, probability density function, and moment generating function of the end-to-end signal-to-noise ratio are derived. Using these channel statistics new finite power series-based analytical expressions are obtained for the outage probability, the average bit error rate (BER) for various binary and M-ary modulation techniques, and the average channel capacity of the considered system. The same analysis is also performed for the scenario when the FSO link undergoes significant pointing errors along with the Gamma–Gamma distributed turbulence. As a special case analytical expressions for the outage probability, BER, and channel capacity are also presented for a dual-hop asymmetric RF–FSO system where the RF link is Rayleigh distributed. Simulation results validate the proposed mathematical analysis. The effects of fading, turbulence, and pointing error are studied on the outage probability, average BER, and the channel capacity.

On the Security of Cognitive Radio Networks

Abstract: Cognitive radio has emerged as an essential recipe for future high-capacity, high-coverage multitier hierarchical networks. Securing data transmission in these networks is of the utmost importance. In this paper, we consider the cognitive wiretap channel and propose multiple antennas to secure the transmission at the physical layer, where the eavesdropper overhears the transmission from the secondary transmitter to the secondary receiver. The secondary receiver and the eavesdropper are equipped with multiple antennas, and passive eavesdropping is considered where the channel state information (CSI) of the eavesdropper's channel is not available at the secondary transmitter. We present new closed-form expressions for the exact and asymptotic secrecy outage probability. Our results reveal the impact of the primary network on the secondary network in the presence of a multiantenna wiretap channel.

One-bit massive MIMO: Channel estimation and high-order modulations

Abstract: We investigate the information-theoretic throughout achievable on a fading communication link when the receiver is equipped with one-bit analog-to-digital converters (ADCs). The analysis is conducted for the setting where neither the transmitter nor the receiver have a priori information on the realization of the fading channels. This means that channel-state information needs to be acquired at the receiver on the basis of the one-bit quantized channel outputs. We show that least-squares (LS) channel estimation combined with joint pilot and data processing is capacity achieving in the single-user, single-receive-antenna case. We also investigate the achievable uplink throughput in a massive multiple-input multiple-output system where each element of the antenna array at the receiver base-station feeds a one-bit ADC. We show that LS channel estimation and maximum-ratio combining are sufficient to support both multiuser operation and the use of high-order constellations. This holds in spite of the severe non-linearity introduced by the one-bit ADCs.

Relay Selection for Simultaneous Information Transmission and Wireless Energy Transfer: A Tradeoff Perspective

Abstract: In certain applications, relay terminals can be employed to simultaneously deliver information and energy to a designated receiver and a set of radio frequency (RF) energy harvesters, respectively. In such scenarios, the relay that is preferable for information transmission does not necessarily coincide with the relay that is preferable for energy transfer, since the corresponding channels fade independently. Relay selection thus entails a tradeoff between the efficiency of the information transmission to the receiver and the amount of energy transferred to the energy harvesters. The study of this tradeoff is the subject on which this work mainly focuses. Specifically, we investigate the dependence of the ergodic capacity and the outage probability of the information transmission to the receiver on the amount of energy transferred to the RF energy harvesters. We propose a relay selection policy that yields the optimal tradeoff in a maximum capacity/minimum outage probability sense, for a given energy transfer constraint. We also propose two suboptimal relay selection methods that apply to scenarios with limited availability of channel state information. Additionally, we propose a suboptimal scheme which approximates the optimal scheme for the special case of two relays and facilitates performance analysis. Interesting insights on the aforementioned tradeoffs are unveiled.

Joint Optimization of Precoder and Equalizer in MIMO VLC Systems

Abstract: Recently, visible light communication (VLC) has attracted much attention as a possible candidate technology to meet the ever growing demand in wireless data. However, current low-cost white LED has limited modulation bandwidth, which limits the throughput of the VLC. Optical MIMO can provide spatial diversity and thus achieve high data rate. Traditional multiple-input multiple-output (MIMO) techniques used in wireless communications cannot be directly applied to VLC. This paper studies the precoder and equalizer design of optical wireless MIMO system for VLC. First, we propose a MIMO VLC system, which can effectively support the flickering/dimming control and other VLC-specific requirements. Second, besides the transceiver design with perfect channel state information, we also take into account channel uncertainties for joint optimization in the MIMO VLC system. Numerical results show that the proposed MIMO solution for VLC is robust to combat the influence caused by the channel estimation imperfection. By taking into account the channel estimation errors, the proposed joint optimization method demonstrates the bit error rate (BER) improvements in the scenario of imperfect channel estimation.

Large-Scale MIMO Relaying Techniques for Physical Layer Security: AF or DF?

Abstract: In this paper, we consider a large scale multiple input multiple output (LS-MIMO) relaying system, where an information source sends the message to its intended destination aided by an LS-MIMO relay, while a passive eavesdropper tries to intercept the information forwarded by the relay. The advantage of a large scale antenna array is exploited to improve spectral efficiency and enhance wireless security. In particular, the challenging issue incurred by short-distance interception is well addressed. Under very practical assumptions, i.e., no eavesdropper channel state information (CSI) and imperfect legitimate CSI at the relay, this paper gives a thorough secrecy performance analysis and comparison of two classic relaying techniques, i.e., amplify-and-forward (AF) and decode-and-forward (DF). Furthermore, asymptotical analysis is carried out to provide clear insights on the secrecy performance for such an LS-MIMO relaying system. We show that under large transmit powers, AF is a better choice than DF from the perspectives of both secrecy performance and implementation complexity, and prove that there exits an optimal transmit power at medium regime that maximizes the secrecy outage capacity.

Power Control in D2D-Based Vehicular Communication Networks

Abstract: This paper studies how to efficiently apply device-to-device (D2D) communications underlaying a cellular system to support vehicle-to-vehicle (V2V) connection (termed D2D-V). By considering the geographic features of the D2D-V system, we propose a D2D-V grouping, reuse channel selection (RS), and power control (PC) framework to achieve the optimal performance of the D2D-V system, in terms of either maximized sum rate or maximized minimally achievable rate. First, in a full channel state information (CSI) scenario, we apply difference of two convex functions (D.C.) programming to obtain the optimal PC. However, because the CSI between some terminals is hard to obtain and some interference can be appropriately inhibited by taking advantage of the vehicles' geographic features, we make a series of simplifications to the PC problem to reduce the requirement of full CSI, the dependence of centralized control, and the computational complexity. The suitable conditions of each simplification are elaborated. Each step of our simplifications are shown as a certain tradeoff between performance and complexity. Furthermore, we provide an investigation into the service quality that one vehicle can achieve when it passes through the covered segment of the highway and propose the location–service curve to portray this. We use numerical simulations to verify the accuracy and feasibility of each step of our suboptimal PC and specific features embedded in the location–service curve.

Secure MISO Wiretap Channels With Multiantenna Passive Eavesdropper: Artificial Noise vs. Artificial Fast Fading

Abstract: The artificial noise (AN) scheme is an efficient strategy for enhancing the secrecy rate of a multiple-input–single-output channel in the presence of a passive eavesdropper, whose channel state information is unavailable. Recently, a randomized beamforming scheme has been proposed for deteriorating the eavesdropper's bit-error-rate performance via corrupting its receiving signal by time-varying multiplicative noise. However, the secrecy rate of such a scheme has not been well addressed yet. In this paper, we name it the artificial fast fading (AFF) scheme and provide a comprehensive secrecy rate analysis for it. We show that with this scheme, the eavesdropper will face a noncoherent Ricean fading single-input–multiple-output channel. Although the closed-form secrecy rate is difficult to obtain, we derive an exact expression for the single-antenna-eavesdropper case and a lower bound for the multiantenna-eavesdropper case, both of which can be numerically calculated conveniently. Furthermore, we compare the AFF scheme with the AN scheme and show that their respective superiorities to each other depend on the number of antennas that the transmitter and the eavesdropper possessed, i.e., when the eavesdropper has more antennas than the transmitter does, the AFF scheme achieves a larger secrecy rate; otherwise, the AN scheme outperforms. Motivated by this observation, we propose a hybrid AN-AFF scheme and investigate the power allocation problem, which achieves better secrecy performance further.

Secure Transmission in MIMO Wiretap Channels Using General-Order Transmit Antenna Selection With Outdated CSI

Abstract: In this paper, we propose general-order transmit antenna selection to enhance the secrecy performance of multiple-input–multiple-output multieavesdropper channels with outdated channel state information (CSI) at the transmitter. To evaluate the effect of the outdated CSI on the secure transmission of the system, we investigate the secrecy performance for two practical scenarios, i.e., Scenarios I and II, where the eavesdropper's CSI is not available at the transmitter and is available at the transmitter, respectively. For Scenario I, we derive exact and asymptotic closed-form expressions for the secrecy outage probability in Nakagami- $m$ fading channels. In addition, we also derive the probability of nonzero secrecy capacity and the $\varepsilon$ -outage secrecy capacity, respectively. Simple asymptotic expressions for the secrecy outage probability reveal that the secrecy diversity order is reduced when the CSI is outdated at the transmitter, and it is independent of the number of antennas at each eavesdropper $N_\textrm{E} $ , the fading parameter of the eavesdropper's channel $m_\textrm{E}$ , and the number of eavesdroppers $M$ . For Scenario II, we make a comprehensive analysis of the average secrecy capacity obtained by the system. Specifically, new closed-form expressions for the exact and asymptotic average secrecy capacity are derived, which are valid for general systems with an arbitrary number of antennas, number of eavesdroppers, and fading severity parameters. Resorting to these results, we also determine a high signal-to-noise ratio power offset to explicitly quantify the impact of the main channel and the eavesdropper's channel on the average secrecy capacity.

Antenna Grouping Based Feedback Compression for FDD-Based Massive MIMO Systems

Abstract: Recent works on massive multiple-input multiple-output (MIMO) have shown that a potential breakthrough in capacity gains can be achieved by deploying a very large number of antennas at the base station. In order to achieve the performance that massive MIMO systems promise, accurate transmit-side channel state information (CSI) should be available at the base station. While transmit-side CSI can be obtained by employing channel reciprocity in time division duplexing (TDD) systems, explicit feedback of CSI from the user terminal to the base station is needed for frequency division duplexing (FDD) systems. In this paper, we propose an antenna grouping based feedback reduction technique for FDD-based massive MIMO systems. The proposed algorithm, dubbed antenna group beamforming (AGB), maps multiple correlated antenna elements to a single representative value using predesigned patterns. The proposed method modifies the feedback packet by introducing the concept of a header to select a suitable group pattern and a payload to quantize the reduced dimension channel vector. Simulation results show that the proposed method achieves significant feedback overhead reduction over conventional approach performing the vector quantization of whole channel vector under the same target sum rate requirement.

Sum-Rate and Power Scaling of Massive MIMO Systems With Channel Aging

Abstract: This paper investigates the achievable sum-rate of massive multiple-input multiple-output (MIMO) systems in the presence of channel aging. For the uplink, by assuming that the base station (BS) deploys maximum ratio combining (MRC) or zero-forcing (ZF) receivers, we present tight closed-form lower bounds on the achievable sum-rate for both receivers with aged channel state information (CSI). In addition, the benefit of implementing channel prediction methods on the sum-rate is examined, and closed-form sum-rate lower bounds are derived. Moreover, the impact of channel aging and channel prediction on the power scaling law is characterized. Extension to the downlink scenario and multicell scenario is also considered. It is found that, for a system with/without channel prediction, the transmit power of each user can be scaled down at most by $1/\sqrt{M}$ (where $M$ is the number of BS antennas), which indicates that aged CSI does not degrade the power scaling law, and channel prediction does not enhance the power scaling law; instead, these phenomena affect the achievable sum-rate by degrading or enhancing the effective signal to interference and noise ratio, respectively.

Acquisition of channel state information in heterogeneous cloud radio access networks: challenges and research directions

Abstract: As an emerging system architecture, heterogeneous cloud radio access networks (H-CRANs) can improve system capacity, enlarge coverage, and enhance energy/spectral efficiency. Meanwhile, this newborn architecture also brings many open problems for traditional topics, including synchronization, channel estimation, and data detection. In this article, we present a comprehensive analysis on obtaining CSI in H-CRANs. Specifically, we recognize seven challenges in channel estimation that are caused by a large number of channel parameters, heterogeneity of access nodes in H-CRANs, and the time delays among different nodes. Several research directions for handling these challenges are also proposed, for example, array signal processing and channel compression can eliminate the number of channel estimates, while channel prediction and modification for high-speed railway communications and adaptive downlink array from uplink measurements excel in overcoming the non-reciprocity in channel parameters.

Opportunistic Control Over Shared Wireless Channels

Abstract: We consider a wireless control architecture with multiple control loops over a shared wireless medium. A scheduler observes the random channel conditions that each control system experiences over the shared medium and opportunistically selects systems to transmit at a set of non-overlapping frequencies. The transmit power of each system also adapts to channel conditions and determines the probability of successfully receiving and closing the loop. We formulate the optimal design of channel-aware scheduling and power allocation that minimize the total power consumption while meeting control performance requirements for all systems. In particular, it is required that for each control system a given Lyapunov function decreases at a specified rate in expectation over the random channel conditions. We develop an offline algorithm to find the optimal communication design, as well as an online protocol which selects scheduling and power variables based on a random observed channel sequence and converges almost surely to the optimal operating point. Simulations illustrate the power savings of our approach compared to other non-channel-aware schemes.

Mixed RF/FSO Relaying With Outdated Channel State Information

Abstract: We investigate the outage probability and the average bit error rate (BER) performance of a dual-hop amplify-and-forward (AF) relaying system, composed of a mixed radio frequency (RF)/free-space optical (FSO) link, when simultaneously outdated channel state information (CSI) is assumed at the relay and there is a misalignment between transmitter and receiver apertures in FSO link. In contrast to the majority of works on CSI-assisted AF relays, in this paper, we assume that the estimated CSI is outdated, when the relay amplifies the transmitted signal. The RF link experiences Rayleigh fading, while the FSO link is under the influence of atmospheric turbulence, modeled by the Gamma-Gamma distribution. Novel analytical expressions for the outage probability and the average BER are derived in a power series form, which in some special cases are simplified to offer engineering insight into the effects of important transceiver and channel parameters on the system performance. Numerical and simulation results show that there is an optimal value of the transmitter beam waist, which minimizes the overall outage probability. This optimal value strongly depends on the pointing errors standard deviation. Furthermore, the outage probability varies for several orders of magnitude depending on the transmitter beam waist.

Opportunistic Relay Selection for Secrecy Enhancement in Cooperative Networks

Abstract: In this paper, we present a comprehensive investigation on the secrecy performance of opportunistic relay selection systems employing the decode-and-forward protocol over Rayleigh fading channels. Considering a practical setting where direct link between the source node (Alice) and the destination node (Bob) is available, we study the secrecy performance of three different diversity combining schemes, namely, maximum ratio combining (MRC), distributed selection combining (DSC), and distributed switch-and-stay combining (DSSC). Throughout the analysis, we consider two different scenarios based on the availability of the eavesdropper's channel state information (CSI), i.e., Scenario A , where the eavesdropper's CSI is not available at Alice and the relay, and Scenario B , where Alice and the relay have knowledge about the eavesdropper's CSI. For Scenario A , we derive exact closed-form expressions for secrecy outage probability and simple asymptotic approximations for the secrecy outage probability, which enable the characterization of the achievable secrecy diversity order and coding gains. For Scenario B , we derive closed-form expressions for the achievable secrecy rates. For both scenarios, we investigate the impact of feedback delay (outdated CSI) on the secrecy performance wherein exact and asymptotic secrecy outage probability and closed-form expressions of the secrecy achievable rates are obtained. Our analytical findings suggest that both the MRC and DSC schemes achieve the maximum diversity order of $K+1$ where $K$ is the number of relays. In addition, the feedback delay has a significant impact on the achievable secrecy performance by reducing the achievable diversity order to two.