Impact Of Channel State Information Research Articles

A novel multicarrier index keying‐aided non‐orthogonal multiple access systems in presence of uncertain channel state information

SummaryThis paper investigates the performance of novel multicarrier index keying‐aided non‐orthogonal multiple access (MCIK‐NOMA) system. Unlike the classical scheme, the proposed system sends the information through both index domain and constellation domain symbols thereby increases the spectral efficiency. The impact of channel state information (CSI) uncertainty on the system's performance is investigated. More specifically, the performance of MCIK‐NOMA under three different CSI conditions is analyzed: perfect CSI, MMSE‐based variable CSI, and fixed CSI uncertainty. This paper also discusses the optimum power difference needed for the successful separation of symbols at the SIC receiver by alternating the power ratio in the proposed system. The influence of selecting different active subcarriers and modulation techniques on the system's performance is studied in detail. The simulation results show that the proposed system achieves better BER and spectral efficiency and outperforms the existing systems.

Robust and Secure Sum-Rate Maximization for Multiuser MISO Downlink Systems With Self-Sustainable IRS

This paper investigates robust and secure multiuser multiple-input single-output (MISO) downlink communications assisted by a self-sustainable intelligent reflection surface (IRS), which can simultaneously reflect and harvest energy from the received signals. We study the joint design of beamformers at an access point (AP) and the phase shifts as well as the energy harvesting schedule at the IRS for maximizing the system sum-rate. The design is formulated as a non-convex optimization problem taking into account the wireless energy harvesting capability of IRS elements, secure communications, and the robustness against the impact of channel state information (CSI) imperfection. Subsequently, we propose a computationally-efficient iterative algorithm to obtain a suboptimal solution to the design problem. In each iteration, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {S}$ </tex-math></inline-formula> -procedure and the successive convex approximation are adopted to handle the intermediate optimization problem. Our simulation results unveil that: 1) there is a non-trivial trade-off between the system sum-rate and the self-sustainability of the IRS; 2) the performance gain achieved by the proposed scheme is saturated with a large number of energy harvesting IRS elements; 3) an IRS equipped with small bit-resolution discrete phase shifters is sufficient to achieve a considerable system sum-rate of the ideal case with continuous phase shifts.

Memory-Based Codes for Uniform Illumination in MIMO VLC

Light emitting diode (LED) based indoor multiple input multiple output visible light communication system has LEDs placed at various positions in the room which are simultaneously used for illumination and communications. In such a system, there should be no human perceivable fluctuations in the intensity of the individual LEDs to avoid user discomfort. In order to achieve the uniformity in illumination, we propose codes under the constraints of constant total transmit power per symbol and constant average transmit power for each individual LED. We show the performance of the proposed codes in terms of various metrics like bit error rate (BER), consistency in illumination, and spectral efficiency with suitable expressions. We also numerically analyze the impact of channel state information (CSI) on BER performance by assuming perfect CSI is not always available but periodically updated at the receiver.

Information freshness over a Markov channel: The effect of channel state information

We consider a communication problem in which a source desires to maintain the freshness of the information updates it sends to a destination, over a channel that varies according to a Markov chain. Freshness is quantified in terms of the age metric (unlike the familiar delay metric), which refers to the difference between the current time and the time of generation of the most recently received update. We then address the impact of channel state information (CSI) on information freshness. Using CSI, transmissions can be adapted to current channel conditions to improve system performance. The following cases are considered: unknown CSI, perfect CSI, erroneous CSI, and delayed CSI.

Wireless Powered Dual-Hop Multi-Antenna Relaying Systems: Impact of CSI and Antenna Correlation

This paper investigates the impact of the channel state information (CSI) and antenna correlation at the multi-antenna relay on the performance of wireless powered dual-hop amplify-and-forward relaying systems. Depending on the available CSI at the relay, two different scenarios are considered, namely, instantaneous CSI and statistical CSI where the relay has access only to the antenna correlation matrix. Adopting the power-splitting architecture, we present a detailed performance study for both cases. Closed-form analytical expressions are derived for the outage probability and ergodic capacity. In addition, simple high signal-to-noise ratio (SNR) outage approximations are obtained. Our results show that, antenna correlation itself does not affect the achievable diversity order, the availability of CSI at the relay determines the achievable diversity order. Full diversity order can be achieved with instantaneous CSI, while only a diversity order of one can be achieved with statistical CSI. In addition, the transmit antenna correlation and receive antenna correlation exhibit different impacts on the ergodic capacity. Moreover, the impact of antenna correlation on the ergodic capacity also depends heavily on the available CSI and operating SNR.

Impact of CSI Knowledge on the Codebook-Based Hybrid Beamforming in Massive MIMO

Hybrid beamforming, which consists of an RF precoder and a baseband precoder, has been proposed to reduce the number of RF chains at the massive multiple input multiple output (MIMO) base station (BS). This paper studies the impact of channel state information (CSI) on the capacity of massive MIMO systems with codebook-based hybrid beamforming , where the RF precoder is selected from a finite size codebook. Two types of CSI at the BS (CSIT) are commonly assumed: full instantaneous CSIT and hybrid CSIT (channel statistics plus the low-dimensional effective channel matrix). With full instantaneous CSIT, both the RF and baseband precoders are adaptive to the full instantaneous CSI at the fast timescale. With hybrid CSIT, the RF precoder is adaptive to channel statistics only, and the baseband precoder is adaptive to the instantaneous effective channel, yielding lower implementation complexity by sacrificing some capacity. We derive asymptotic sum capacity expressions under these two types of CSIT. We find that, in codebook-based hybrid beamforming systems, exploiting the full instantaneous CSIT can only achieve a marginal SNR gain and hybrid CSIT is sufficient to achieve the first-order gain provided by the massive MIMO for most of the cases. We also propose fast and slow timescale RF precoding algorithms, which asymptotically achieve the capacity under full instantaneous CSIT and hybrid CSIT, respectively.

Optimal Binary Power Control for Underlay CR With Different Interference Constraints and Impact of Channel Estimation Errors

Adapting the power of secondary users (SUs) while adhering to constraints on the interference caused to primary receivers (PRxs) is a critical issue in underlay cognitive radio (CR). This adaptation is driven by the interference and transmit power constraints imposed on the secondary transmitter (STx). Its performance also depends on the quality of channel state information (CSI) available at the STx of the links from the STx to the secondary receiver and to the PRxs. For a system in which an STx is subject to an average interference constraint or an interference outage probability constraint at each of the PRxs, we derive novel symbol error probability (SEP)-optimal, practically motivated binary transmit power control policies. As a reference, we also present the corresponding SEP-optimal continuous transmit power control policies for one PRx. We then analyze the robustness of the optimal policies when the STx knows noisy channel estimates of the links between the SU and the PRxs. Altogether, our work develops a holistic understanding of the critical role played by different transmit and interference constraints in driving power control in underlay CR and the impact of CSI on its performance.

Impact of Channel Estimation Error on the Performance of Amplify-and-Forward Two-Way Relaying

In this paper, the impact of channel-state information (CSI) estimation error on the performance of an amplify-and-forward two-way multiple relay network has been investigated. In contrast to the existing literature, which assumes perfect self-interference cancellation, we consider imperfect self-interference cancellation at both sources that exchange information through multiple relays, and maximal-ratio combining is then applied to improve the decision statistics under imperfect signal detection. We derive the effective signal-to-noise ratio (SNR) subject to noisy channel estimation, and based on this SNR, the system outage probability is given. In addition, we derive the closed-form expression of the average system bit error rate (BER) and the asymptotic expressions for both outage probability and BER. Furthermore, instead of employing all relays, we examine the impact of imperfect CSI on a single relay selection (RS) scheme. To mitigate the negative impact of imperfect CSI, we show that power allocation (PA), by minimizing either the outage probability or the BER, can suitably be cast as the geometric-programming problem. Numerical results validate the correctness of the derived expressions and show that the adaptive-PA scheme outperforms the equal-PA scheme under the aggregated effect of imperfect CSI.

Impact of CSI on Radio Resource Management Techniques for the OFDMA downlink

Adaptive resource allocation can drastically increase the throughput of an Orthogonal Frequency Division Multiple Access (OFDMA) system when the Channel State Information (CSI) is accurately known. Unfortunately, in practice, perfect CSI is rarely possible. In this paper, we consider adaptive sub-carrier assignment for downlink multiuser OFDMA systems, where the transmitter has no knowledge of the instantaneous channel realizations. The problem we address is maximizing the sum-capacity of the system subject to user Quality of Service (QoS) requirements. A heuristic algorithm presented in \cite{Zhang06} is modified in order to provide an enhanced sub-optimal solution. Numerical results show that resources can be adaptively allocated using statistical CSI (SCSI) and that such an approach allows for an important number of user QoS requirements to be met. Comparisons between the instantaneous CSI (ICSI) and SCSI based resource allocation schemes demonstrate that their performance difference is highly dependent on the number of active users present in the cell, the QoS constraint, and the transmit power.

The impact of CSI and power allocation on relay channel capacity and cooperation strategies

Capacity gains from transmitter and receiver cooperation are compared in a relay network where the cooperating nodes are close together. Under quasi-static phase fading, when all nodes have equal average transmit power along with full channel state information (CSI), it is shown that transmitter cooperation outperforms receiver cooperation, whereas the opposite is true when power is optimally allocated among the cooperating nodes but only CSI at the receiver (CSIR) is available. When the nodes have equal power with CSIR only, cooperative schemes are shown to offer no capacity improvement over non-cooperation under the same network power constraint. When the system is under optimal power allocation with full CSI, the decode-and-forward transmitter cooperation rate is close to its cut-set capacity upper bound, and outperforms compress-and-forward receiver cooperation. Under fast Rayleigh fading in the high SNR regime, similar conclusions follow. Cooperative systems provide resilience to fading in channel magnitudes; however, capacity becomes more sensitive to power allocation, and the cooperating nodes need to be closer together for the decode-and-forward scheme to be capacity-achieving. Moreover, to realize capacity improvement, full CSI is necessary in transmitter cooperation, while in receiver cooperation optimal power allocation is essential.

On the Performance of Opportunistic Cooperative Wireless Networks

The aim of this paper is to study the impact of channel state information on the design of cooperative transmission protocols. This is motivated by the fact that the performance gain achieved by cooperative diversity comes at the price of the extra bandwidth resource consumption. Several opportunistic relaying strategies are developed to fully utilize the different types of a priori channel information. The analytical and numerical results demonstrate that the use of such a priori information increases the spectral efficiency of cooperative diversity, especially at low signal-to-noise ratio.

Decentralized Inference Over Multiple-Access Channels

The problem of decentralized inference over multiple-access fading channels is considered from a joint source-channel coding perspective. In our setting, spatially distributed wireless sensor nodes collect observation data about a hidden source and communicate relevant statistics to a receiver node that generates the desired inference (estimation or detection) about unknown source parameters. We assume a homogeneous sensor signal field in which information about the source parameters is distributed in space (across sensors) and time in an independent and identically distributed (i.i.d.) manner. Our study characterizes the asymptotic performance of an identical source-channel mapping for i.i.d. sensor observation data in which the same encoder is used at all the nodes. This scheme generalizes many existing methods including uncoded transmission and type-based multiple access. Sufficient conditions are obtained under which our identical mapping approach achieves the genie-aided scaling law (in the number of nodes) associated with a noiseless channel, even when the nodes transmit with asymptotically vanishing power. Our analysis also elucidates the critical impact of channel state information on the achievable performance. In particular, it identifies scenarios in which identical mapping fails and a simple nonidentical mapping scheme is shown to improve performance. Numerical examples are provided to illustrate the theoretical principles derived in the paper.