Showing papers on "Channel state information published in 2008"

Guaranteeing Secrecy using Artificial Noise

Abstract: The broadcast nature of the wireless medium makes the communication over this medium vulnerable to eavesdropping. This paper considers the problem of secret communication between two nodes, over a fading wireless medium, in the presence of a passive eavesdropper. The assumption used is that the transmitter and its helpers (amplifying relays) have more antennas than the eavesdropper. The transmitter ensures secrecy of communication by utilizing some of the available power to produce 'artificial noise', such that only the eavesdropper's channel is degraded. Two scenarios are considered, one where the transmitter has multiple transmit antennas, and the other where amplifying relays simulate the effect of multiple antennas. The channel state information (CSI) is assumed to be publicly known, and hence, the secrecy of communication is independent of the secrecy of CSI.

An overview of limited feedback in wireless communication systems

Abstract: It is now well known that employing channel adaptive signaling in wireless communication systems can yield large improvements in almost any performance metric. Unfortunately, many kinds of channel adaptive techniques have been deemed impractical in the past because of the problem of obtaining channel knowledge at the transmitter. The transmitter in many systems (such as those using frequency division duplexing) can not leverage techniques such as training to obtain channel state information. Over the last few years, research has repeatedly shown that allowing the receiver to send a small number of information bits about the channel conditions to the transmitter can allow near optimal channel adaptation. These practical systems, which are commonly referred to as limited or finite-rate feedback systems, supply benefits nearly identical to unrealizable perfect transmitter channel knowledge systems when they are judiciously designed. In this tutorial, we provide a broad look at the field of limited feedback wireless communications. We review work in systems using various combinations of single antenna, multiple antenna, narrowband, broadband, single-user, and multiuser technology. We also provide a synopsis of the role of limited feedback in the standardization of next generation wireless systems.

On the Secrecy Capacity of Fading Channels

Abstract: We consider the secure transmission of information over an ergodic fading channel in the presence of an eavesdropper. Our eavesdropper can be viewed as the wireless counterpart of Wyner's wiretapper. The secrecy capacity of such a system is characterized under the assumption of asymptotically long coherence intervals. We first consider the full channel state information (CSI) case, where the transmitter has access to the channel gains of the legitimate receiver and the eavesdropper. The secrecy capacity under this full CSI assumption serves as an upper bound for the secrecy capacity when only the CSI of the legitimate receiver is known at the transmitter, which is characterized next. In each scenario, the perfect secrecy capacity is obtained along with the optimal power and rate allocation strategies. We then propose a low-complexity on/off power allocation strategy that achieves near-optimal performance with only the main channel CSI. More specifically, this scheme is shown to be asymptotically optimal as the average signal-to-noise ratio (SNR) goes to infinity, and interestingly, is shown to attain the secrecy capacity under the full CSI assumption. Overall, channel fading has a positive impact on the secrecy capacity and rate adaptation, based on the main channel CSI, is critical in facilitating secure communications over slow fading channels.

Secure Communication Over Fading Channels

Abstract: The fading broadcast channel with confidential messages (BCC) is investigated, where a source node has common information for two receivers (receivers 1 and 2), and has confidential information intended only for receiver 1. The confidential information needs to be kept as secret as possible from receiver 2. The broadcast channel from the source node to receivers 1 and 2 is corrupted by multiplicative fading gain coefficients in addition to additive Gaussian noise terms. The channel state information (CSI) is assumed to be known at both the transmitter and the receivers. The parallel BCC with independent subchannels is first studied, which serves as an information-theoretic model for the fading BCC. The secrecy capacity region of the parallel BCC is established, which gives the secrecy capacity region of the parallel BCC with degraded subchannels. The secrecy capacity region is then established for the parallel Gaussian BCC, and the optimal source power allocations that achieve the boundary of the secrecy capacity region are derived. In particular, the secrecy capacity region is established for the basic Gaussian BCC. The secrecy capacity results are then applied to study the fading BCC. The ergodic performance is first studied. The ergodic secrecy capacity region and the optimal power allocations that achieve the boundary of this region are derived. The outage performance is then studied, where a long-term power constraint is assumed. The power allocation is derived that minimizes the outage probability where either the target rate of the common message or the target rate of the confidential message is not achieved. The power allocation is also derived that minimizes the outage probability where the target rate of the confidential message is not achieved subject to the constraint that the target rate of the common message must be achieved for all channel states.

Cooperative communications with relay-selection: when to cooperate and whom to cooperate with?

Abstract: In this paper; we propose a new cooperative communication protocol, which achieves higher bandwidth efficiency while guaranteeing the same diversity order as that of the conventional cooperative schemes. The proposed scheme considers relay selection via the available partial channel state information (CSI) at the source and the relays. In particular, we discuss the multi-node decode-and-forward cooperative scenarios, where arbitrary N relays are available. The source determines when it needs to cooperate with one relay only, and which relay to cooperate with in case of cooperation, i.e., "When to cooperate?" and "Whom to cooperate with?". An optimal relay is the one which has the maximum instantaneous scaled harmonic mean functionof its source-relay and relay-destination channel gains. For the symmetric scenario, we derive an approximate expression of the bandwidth efficiency and obtain an upper bound on the symbol error rate (SER) performance. We show that full diversity is guaranteed and that a significant increase of the bandwidth efficiency is achieved. Moreover, we present the tradeoff between the achievable bandwidth efficiency and the corresponding SER. Finally, the obtained analytical results are verified through computer simulations.

Distributed Beamforming for Relay Networks Based on Second-Order Statistics of the Channel State Information

Abstract: In this paper, the problem of distributed beamforming is considered for a wireless network which consists of a transmitter, a receiver, and relay nodes. For such a network, assuming that the second-order statistics of the channel coefficients are available, we study two different beamforming design approaches. As the first approach, we design the beamformer through minimization of the total transmit power subject to the receiver quality of service constraint. We show that this approach yields a closed-form solution. In the second approach, the beamforming weights are obtained through maximizing the receiver signal-to-noise ratio (SNR) subject to two different types of power constraints, namely the total transmit power constraint and individual relay power constraints. We show that the total power constraint leads to a closed-form solution while the individual relay power constraints result in a quadratic programming optimization problem. The later optimization problem does not have a closed-form solution. However, it is shown that using semidefinite relaxation, this problem can be turned into a convex feasibility semidefinite programming (SDP), and therefore, can be efficiently solved using interior point methods. Furthermore, we develop a simplified, thus suboptimal, technique which is computationally more efficient than the SDP approach. In fact, the simplified algorithm provides the beamforming weight vector in a closed form. Our numerical examples show that as the uncertainty in the channel state information is increased, satisfying the quality of service constraint becomes harder, i.e., it takes more power to satisfy these constraints. Also our simulation results show that when compared to the SDP-based method, our simplified technique suffers a 2-dB loss in SNR for low to moderate values of transmit power.

Energy-Efficient Cooperative Relaying over Fading Channels with Simple Relay Selection

Abstract: We consider a cooperative wireless network where a set of nodes cooperate to relay in parallel the information from a source to a destination using a decode-and-forward approach. The source broadcasts the data to the relays, some or all of which cooperatively beamform to forward the data to the destination. We generalize the standard approaches for cooperative communications in two key respects: (i) we explicitly model and factor in the cost of acquiring channel state information (CSI), and (ii) we consider more general selection rules for the relays and compute the optimal one among them. In particular, we consider simple relay selection and outage criteria that exploit the inherent diversity of relay networks and satisfy a mandated outage constraint. These criteria include as special cases several relay selection criteria proposed in the literature. We obtain expressions for the total energy consumption for general relay selection and outage criteria for the non-homogeneous case, in which different relay links have different mean channel power gains, and the homogeneous case, in which the relay links statistics are identical. We characterize the structure of the optimal transmission scheme. Numerical results show that the cost of training and feedback of CSI is significant. The optimal strategy is to use a varying subset (and number) of relay nodes to cooperatively beamform at any given time. Depending on the relative location of the relays, the source, and the destination, numerical computations show energy savings of about 16% when an optimal relay selection rule is used. We also study the impact of shadowing correlation on the energy consumption for a cooperative relay network.

Secure Broadcasting Over Fading Channels

Abstract: We study a problem of broadcasting confidential messages to multiple receivers under an information-theoretic secrecy constraint. Two scenarios are considered: 1) all receivers are to obtain a common message; and 2) each receiver is to obtain an independent message. Moreover, two models are considered: parallel channels and fast-fading channels. For the case of reversely degraded parallel channels, one eavesdropper, and an arbitrary number of legitimate receivers, we determine the secrecy capacity for transmitting a common message, and the secrecy sum-capacity for transmitting independent messages. For the case of fast-fading channels, we assume that the channel state information of the legitimate receivers is known to all the terminals, while that of the eavesdropper is known only to itself. We show that, using a suitable binning strategy, a common message can be reliably and securely transmitted at a rate independent of the number of receivers. We also show that a simple opportunistic transmission strategy is optimal for the reliable and secure transmission of independent messages in the limit of large number of receivers.

Multicell downlink capacity with coordinated processing

Abstract: We study the potential benefits of base-station (BS) cooperation for downlink transmission in multicell networks. Based on a modified Wyner-type model with users clustered at the cell-edges, we analyze the dirty-paper-coding (DPC) precoder and several linear precoding schemes, including cophasing, zero-forcing (ZF), and MMSE precoders. For the nonfading scenario with random phases, we obtain analytical performance expressions for each scheme. In particular, we characterize the high signal-to-noise ratio (SNR) performance gap between the DPC and ZF precoders in large networks, which indicates a singularity problem in certain network settings. Moreover, we demonstrate that the MMSE precoder does not completely resolve the singularity problem. However, by incorporating path gain fading, we numerically show that the singularity problem can be eased by linear precoding techniques aided with multiuser selection. By extending our network model to include cell-interior users, we determine the capacity regions of the two classes of users for various cooperative strategies. In addition to an outer bound and a baseline scheme, we also consider several locally cooperative transmission approaches. The resulting capacity regions show the tradeoff between the performance improvement and the requirement for BS cooperation, signal processing complexity, and channel state information at the transmitter (CSIT).

Statistically Robust Design of Linear MIMO Transceivers

Abstract: The treatment of channel state information (CSI) is critical in the design of MIMO systems. Accurate CSI at the transmitter is often not possible or may require high feedback rates. Herein, we consider the robust design of linear MIMO transceivers with perfect CSI either at the transmitter or at both sides of the link. The framework considers the design problem where the imperfect CSI consists of the channel mean and covariance matrix or, equivalently, the channel estimate and the estimation error covariance matrix. The robust transceiver design is based on a general cost function of the average MSEs as well as a design with individual MSE based constraints. In particular, a lower bound of the average MSE matrix is explored for the design when only the CSI at the transmitter is imperfect. Under different CSI conditions, the proposed robust transceivers exhibit a similar structure to the transceiver designs for perfect CSI, but with a different equivalent channel and/or noise covariance matrix.

Beamforming in mimo systems

Abstract: A beamforming method comprises transmitting a training sequence from a transmitter array employing a set of beamforming vectors from a beamforming codebook. A receive array employs a combining codebook to acquire channel state information from the received transmissions, and estimates a preferred beamforming vector and a preferred combining vector. At least the preferred beamforming vector (and, optionally, the preferred combining vector) is transmitted back to the transmitter array.

Grassmannian beamforming for MIMO amplify-and-forward relaying

Abstract: We consider the problem of beamforming codebook design for limited feedback half-duplex multiple-input multiple output (MIMO) amplify-and-forward (AF) relay system. In the first part of the paper, the direct link between the source and the destination is ignored. Assuming perfect channel state information (CSI), we show that the source and the relay should map their signals to the dominant right singular vectors of the source-relay and relay-destination channels. For the limited feedback scenario, we prove the appropriateness of Grassmannian codebooks as the source and relay beamforming codebooks based on the distributions of the optimal source and relay beamforming vectors. In the second part of the paper, the direct link is considered in the problem model. Assuming perfect CSI, we derive the optimization problem that identifies the optimal source beamforming vector and show that the solution to this problem is uniformly distributed on the unit sphere for independent and identically distributed (i.i.d) Rayleigh channels. For the limited feedback scenario, we justify the appropriateness of Grassmannian codebooks for quantizing the optimal source beamforming vector based on its distribution. Finally, a modified quantization scheme is presented, which introduces a negligible penalty in the system performance but significantly reduces the required number of feedback bits.

Semi-Distributed User Relaying Algorithm for Amplify-and-Forward Wireless Relay Networks

Abstract: In this paper, designing an effective user relaying algorithm, in terms of relay node selection and power allocation, is discussed for amplify-and-forward wireless relay networks. The objective is to simplify the application of user relaying in practical wireless communication networks so that the system capacity can be improved with low computational complexity and system overhead. Beginning with the derivation of a tight threshold-based sufficient condition on the feasibility of a relay node, i.e., ensuring that user relaying via the node can achieve a larger channel capacity than direct transmission, a semi-distributed user relaying algorithm is proposed. In the proposed algorithm, each relay node can make decision on its feasibility individually, and the ultimate decision on the relay node selection among multiple feasible ones is made in a centralized manner. Since there is no need on exchanging channel state information among different network nodes, the proposed algorithm is simple for implementation and suitable for practical applications, which have stringent constraints on system overhead. By comparing with the centralized user relaying algorithm, which requires global channel state information of the whole network, the proposed semi-distributed algorithm can provide comparable system capacity, but has significantly reduced computational complexity.

Robust Cognitive Beamforming With Partial Channel State Information

Abstract: This paper considers a spectrum sharing based cognitive radio (CR) communication system, which consists of a secondary user (SU) having multiple transmit antennas and a single receive antenna and a primary user (PU) having a single receive antenna. The channel state information (CSI) on the link of the SU is assumed to be perfectly known at the SU transmitter (SU-Tx). However, due to loose cooperation between the SU and the PU, only partial CSI of the link between the SU-Tx and the PU is available at the SU-Tx. With the partial CSI and a prescribed transmit power constraint, our design objective is to determine the transmit signal covariance matrix that maximizes the rate of the SU while keeping the interference power to the PU below a threshold for all the possible channel realization within an uncertainty set. This problem, termed the robust cognitive beamforming problem, can be naturally formulated as a semi-infinite programming (SIP) problem with infinitely many constraints. This problem is first transformed into the second order cone programming (SOCP) problem and then solved via a standard interior point algorithm. Then, an analytical solution with much reduced complexity is developed from a geometric perspective. It is shown that both algorithms obtain the same optimal solution. Simulation examples are presented to validate the effectiveness of the proposed algorithms.

Optimal Downlink OFDMA Resource Allocation with Linear Complexity to Maximize Ergodic Rates

Abstract: OFDMA resource allocation assigns subcarriers and power, and possibly data rates, to each user. Previous research efforts to optimize OFDMA resource allocation with respect to communication performance have focused on formulations considering only instantaneous per-symbol rate maximization, and on solutions using suboptimal heuristic algorithms. This paper intends to fill gaps in the literature through two key contributions. First, we formulate continuous and discrete ergodic weighted sum rate maximization in OFDMA assuming the availability of perfect channel state information (CSI). Our formulations exploit time, frequency, and multi-user diversity, while enforcing various notions of fairness through weighting factors for each user. Second, we derive algorithms based on a dual optimization framework that solve the OFDMA ergodic rate maximization problem with O(MK) complexity per OFDMA symbol for M users and K subcarriers, while achieving data rates shown to be at least 99.9999% of the optimal rate in simulations based on realistic parameters. Hence, this paper attempts to demonstrate that OFDMA resource allocation problems are not computationally prohibitive to solve optimally, even when considering ergodic rates.

Secure wireless communications via cooperation

Abstract: The feasibility of physical-layer-based security approaches for wireless communications in the presence of one or more eavesdroppers is hampered by channel conditions In this paper, cooperation is investigated as an approach to overcome this problem and improve the performance of secure communications In particular, a decode-and-forward (DF) based cooperative protocol is considered, and the objective is to design the system for secrecy capacity maximization or transmit power minimization System design for the DF-based cooperative protocol is first studied by assuming the availability of global channel state information (CSI) For the case of one eavesdropper, an iterative scheme is proposed to obtain the optimal solution for the problem of transmit power minimization For the case of multiple eavesdroppers, the problem of secrecy capacity maximization or transmit power minimization is in general intractable Suboptimal system design is proposed by adding an additional constraint, ie, the complete nulling of signals at all eavesdroppers, which yields simple closed-form solutions for the aforementioned two problems Then, the impact of imperfect CSI of eavesdroppers on system design is studied, in which the ergodic secrecy capacity is of interest

On transceiver design and channel quantization for downlink multiuser MIMO systems with limited feedback

Abstract: We consider a MIMO broadcast channel where both the transmitter and receivers are equipped with multiple antennas. Channel state information at the transmitter (CSIT) is obtained through limited (i.e., finite-bandwidth) feedback from the receivers that index a set of precoding vectors contained in a predefined codebook. We propose a novel transceiver architecture based on zero-forcing beamforming and linear receiver combining. The receiver combining and quantization for CSIT feedback are jointly designed in order to maximize the expected SINR for each user. We provide an analytic characterization of the achievable throughput in the case of many users and show how additional receive antennas or higher multiuser diversity can reduce the required feedback rate to achieve a target throughput.We also propose a design methodology for generating codebooks tailored for arbitrary spatial correlation statistics. The resulting codebooks have a tree structure that can be utilized in time-correlated MIMO channels to significantly reduce feedback overhead. Simulation results show the effectiveness of the overall transceiver design strategy and codebook design methodology compared to prior techniques in a variety of correlation environments.

Secure Wireless Communications via Cooperation

Abstract: The feasibility of physical-layer-based security approaches for wireless communications in the presence of one or more eavesdroppers is hampered by channel conditions. In this paper, cooperation is investigated as an approach to overcome this problem and improve the performance of secure communications. In particular, a decode-and-forward (DF) based cooperative protocol is considered, and the objective is to design the system for secrecy capacity maximization or transmit power minimization. System design for the DF-based cooperative protocol is first studied by assuming the availability of global channel state information (CSI). For the case of one eavesdropper, an iterative scheme is proposed to obtain the optimal solution for the problem of transmit power minimization. For the case of multiple eavesdroppers, the problem of secrecy capacity maximization or transmit power minimization is in general intractable. Suboptimal system design is proposed by adding an additional constraint, i.e., the complete nulling of signals at all eavesdroppers, which yields simple closed-form solutions for the aforementioned two problems. Then, the impact of imperfect CSI of eavesdroppers on system design is studied, in which the ergodic secrecy capacity is of interest.

On the Design of Linear Transceivers for Multiuser Systems with Channel Uncertainty

Abstract: We consider the design of linear transceivers for multiuser communication systems in the presence of uncertain channel state information (CSI), with an emphasis on downlink systems with a single antenna at each receiver. For systems with uplink-downlink reciprocity, we consider a stochastic model for the channel uncertainty, and we propose an efficient algorithm for the joint design of the linear preceding matrix at the base station and the equalizing gains at the receivers so as to minimize the average mean-square-error (MSE) over the channel uncertainty. The design is based on a generalization, derived herein, of the MSE duality between the broadcast and multiple access channels (MAC) to scenarios with uncertain CSI, and on a convex formulation for the design of robust transceivers for the dual MAC. For systems in which quantized channel feedback is employed, we consider a deterministically-bounded model for the channel uncertainty, and we study the design of robust downlink transceivers that minimize the worst- case MSE over all admissible channels. While we show that the design problem is NP-hard, we also propose an iterative local optimization algorithm that is based on efficiently-solvable convex conic formulations. Our framework is quite flexible, and can incorporate different bounded uncertainty models as well as a variety of power constraints. In particular, we study a "system-wide" uncertainty model, and although the resulting design problem is still NP hard, it does result in a significantly simpler iterative local design algorithm than the "per-user" uncertainty model. Our approaches to the minimax design for the downlink can be extended to the uplink, and we provide explicit formulations for the resulting uplink designs. Simulation results indicate that the proposed approaches to robust linear transceiver design can significantly reduce the sensitivity of the downlink to uncertain CSI, and can provide improved performance over that of existing robust designs.

Distributed Power Allocation Strategies for Parallel Relay Networks

Abstract: We consider a source-destination pair assisted by parallel regenerative decode-and-forward relays operating in orthogonal channels. We investigate distributed power allocation strategies for this system with limited channel state information at the source and the relay nodes. We first propose a distributed decision mechanism for each relay to individually make its decision on whether to forward the source data. The decision mechanism calls for each relay that is able to decode the information from the source to compare its relay-to-destination channel gain with a given threshold. We identify the optimum distributed power allocation strategy that minimizes the total transmit power while providing a target signal-to-noise ratio at the destination with a target outage probability. The strategy dictates the optimum choices for the source power as well as the threshold value at the relays. Next, we consider two simpler distributed power allocation strategies, namely the passive source model where the source power and the relay threshold are fixed, and the single relay model where only one relay is allowed to forward the source data. These models are motivated by limitations on the available channel state information as well as ease of implementation as compared to the optimum distributed strategy. Simulation results are presented to demonstrate the performance of the proposed distributed power allocation schemes. Specifically, we observe significant power savings with proposed methods as compared to random relay selection.

Optimal Power Control over Fading Cognitive Radio Channel by Exploiting Primary User CSI

Abstract: This paper is concerned with spectrum sharing for wireless communication, where a secondary or cognitive radio (CR) link communicates over the same bandwidth that has been assigned to an existing primary radio (PR) link. It is assumed that the CR transmitter has perfect channel state information (CSI) on the channels from it to both the PR and CR receivers (as usually assumed in the literature), as well as the channel from the PR transmitter to PR receiver (a new assumption made). With known PR CSI, we study the optimal power control for the CR fading channel to maximize its ergodic capacity subject to the CR's transmit power constraint as well as the constraint on the maximum ergodic capacity loss of the PR link due to the CR transmission. It is shown that the new power-control policy performs better than the conventional one that does not depend on the primary user CSI, but is based on the average interference-power constraint at the PR receiver, in terms of both the PR and CR channel ergodic capacities.

Distributed power allocation strategies for parallel relay networks

Abstract: We consider a source-destination pair assisted by parallel regenerative decode-and-forward relays operating in orthogonal channels. We investigate distributed power allocation strategies for this system with limited channel state information at the source and the relay nodes. We first propose a distributed decision mechanism for each relay to individually make its decision on whether to forward the source data. The decision mechanism calls for each relay that is able to decode the information from the source to compare its relay-to-destination channel gain with a given threshold. We identify the optimum distributed power allocation strategy that minimizes the total transmit power while providing a target signal-to-noise ratio at the destination with a target outage probability. The strategy dictates the optimum choices for the source power as well as the threshold value at the relays. Next, we consider two simpler distributed power allocation strategies, namely the passive source model where the source power and the relay threshold are fixed, and the single relay model where only one relay is allowed to forward the source data. These models are motivated by limitations on the available channel state information as well as ease of implementation as compared to the optimum distributed strategy. Simulation results are presented to demonstrate the performance of the proposed distributed power allocation schemes. Specifically, we observe significant power savings with proposed methods as compared to random relay selection.

Multiple antenna MMSE based downlink precoding with quantized feedback or channel mismatch

Abstract: In this paper, we consider the downlink of a multiuser wireless communication system with multiple antennas at the base station and users each with a single receive antenna. It is known that when channel state information (CSI) is available at the transmitter a large performance gain can be achieved. In a system employing time-division duplexing (TDD), CSI can be obtained at the base station if there is reciprocity between the forward and reverse channels. CSI can also be conveyed from the users to the base station via a limited-rate feedback channel in a frequency-division duplexing (FDD) system. In any case, channel estimation errors are inevitable due to the presence of background noise in the estimated signal and due to the finite number of feedback bits used in a limited-rate feedback system model. In this paper, we first consider the general case when partial CSI is available at the transmitter. We derive an MMSE based precoding technique that considers channel estimation errors as an integral part of the system design. Using rate-distortion theory and the generalized Lloyd vector quantization algorithm, we then specialize our results for the more practical limited-rate feedback system model. Compared to previously proposed precoding techniques such as channel inversion and regularized channel inversion, it is shown that the proposed precoding technique significantly improves the average bit error rate (BER) in the system. Furthermore, the performance of the proposed technique is investigated in the high signal-tonoise ratio (SNR) regime. It is shown that the proposed technique suffers from a ceiling effect that asymptotically limits the system performance.

Smart regenerative relays for link-adaptive cooperative communications

Abstract: Without being necessary to pack multiple antennas per terminal, cooperation among distributed single-antenna nodes offers resilience to shadowing and can, in principle, enhance the performance of wireless communication networks by exploiting the available space diversity. Enabling the latter however, calls for practically implementable protocols to cope with errors at relay nodes so that simple receiver processing can collect the diversity at the destination. To this end, we derive in this paper a class of strategies whereby decoded bits at relay nodes are scaled in power before being forwarded to the destination. The scale is adapted to the signal-to-noise-ratio (SNR) of the source-relay and the intended relay-destination links. With maximum ratio combining (MRC) at the destination, we prove that such link-adaptive regeneration (LAR) strategies effect the maximum possible diversity while requiring simple channel state information that can be pragmatically acquired at the relay. In addition, LAR exhibits robustness to quantization and feedback errors and leads to efficient use of power both at relay as well as destination nodes. Analysis and corroborating simulations demonstrate that LAR relays are attractive across the practical SNR range; they are universally applicable to multibranch and multi-hop uncoded or coded settings regardless of the underlying constellation; and outperform existing alternatives in terms of error performance, complexity and bandwidth efficiency.

Cooperative Multiple-Access Encoding With States Available at One Transmitter

Abstract: We generalize the Gel'fand-Pinsker model to encompass the setup of a memoryless multiple-access channel (MAC). According to this setup, only one of the encoders knows the state of the channel (noncausally), which is also unknown to the receiver. Two independent messages are transmitted: a common message and a message transmitted by the informed encoder. We find explicit characterizations of the capacity region with both noncausal and causal state information. Further, we study the noise-free binary case, and we also apply the general formula to the Gaussian case with noncausal channel state information, under an individual power constraint as well as a sum power constraint. In this case, the capacity region is achievable by a generalized writing-on-dirty-paper scheme.

Lifetime maximization for amplify-and-forward cooperative networks

Abstract: Joint relay-selection and power-allocation strategies are devised to prolong the lifetime of amplify-and-forward (AF) cooperative networks. Lifetime is defined as the time duration within which the desired signal-to-noise ratio (SNR) at the destination is met with a certain probability. Based on selective relaying, we propose three strategies that take into account the local channel state information (CSI) and the local residual energy information (REI) at each relay to prolong the network lifetime. With a finite number of power levels, the energy dissipation process can be modeled as a finite-state Markov chain and the optimal lifetime maximization strategy can be derived using dynamic programming. We demonstrate that the network lifetime can be extended considerably by exploiting both CSI and REI via numerical simulation. The performance of the proposed strategies that utilize only local CSI and REI is shown to be comparable to that of the optimal strategy that demands global CSI and REI.

Iterative Carrier Frequency Offset and Channel Estimation for Underwater Acoustic OFDM Systems

Abstract: This paper presents a practical low-density parity-check (LDPC) coded OFDM system designed for the underwater acoustic channel with its attendant sparse multipath channel and Doppler effects. The carrier frequency offset (CFO) and channel state information (CSI) are assumed unavailable to both to the transmitter and the receiver. Several different receiver structures are considered, all of which perform CFO/channel estimation, detection and decoding in an iterative manner. The convergence behavior of the iterative receivers and their asymptotic performance are evaluated using the extrinsic information transfer (EXIT) chart method. OFDM receiver performance is further evaluated through simulations and field tests in shallow water.

Distributed beamforming and power allocation for cooperative networks

Abstract: Cooperative diversity systems rely on using relay nodes to relay copies of transmitted information to the destination such that each copy experiences different channel fading, hence increasing the diversity of the system. However, without proper processing of the message at the relays, the performance of the cooperative system may not necessarily perform better than direct transmission systems. In this paper, we proposed a distributed beamforming and power allocation algorithm which substantially improves the diversity of the system with only very limited feedback from the destination node. We also derive outage probability as well as study the outage behavior of this scheme.

Spatial Interference Cancellation for Multi-Antenna Mobile Ad Hoc Networks

Abstract: Interference between nodes is a critical impairment in mobile ad hoc networks (MANETs). This paper studies the role of multiple antennas in mitigating such interference. Specifically, a network is studied in which receivers apply zero-forcing beamforming to cancel the strongest interferers. Assuming a network with Poisson distributed transmitters and independent Rayleigh fading channels, the transmission capacity is derived, which gives the maximum number of successful transmissions per unit area. Mathematical tools from stochastic geometry are applied to obtain the asymptotic transmission capacity scaling and characterize the impact of inaccurate channel state information (CSI). It is shown that, if each node cancels L interferers, the transmission capacity decreases as the outage probability to the power of 1/(L+1) as the outage probability vanishes. For fixed outage probability, as L grows, the transmission capacity increases as L to the power of (1-2/alpha) where alpha is the path-loss exponent. Moreover, CSI inaccuracy is shown to have no effect on the transmission capacity scaling as the outage probability vanishes, provided that the CSI training sequence has an appropriate length, which we derived. Numerical results suggest that canceling merely one interferer by each node increases the transmission capacity by an order of magnitude or more, even when the CSI is imperfect.

Fixed-Complexity Soft MIMO Detection via Partial Marginalization

Abstract: This paper presents a new approach to soft demodulation for MIMO channels. The proposed method is an approximation to the exact a posteriori probability-per-bit computer. The main idea is to marginalize the posterior density for the received data exactly over the subset of the transmitted bits that are received with the lower signal-to-noise-ratio (SNR), and marginalize this density approximately over the remaining bits. Unlike the exact demodulator, whose complexity is huge due to the need for enumerating all possible combinations of transmitted constellation points, the proposed method has very low complexity. The algorithm has a fully parallel structure, suitable for implementation in parallel hardware. Additionally, its complexity is fixed, which makes it suitable for pipelined implementation. We also show how the method can be extended to the situation when the receiver has only partial channel state information, and how it can be modified to take soft-input into account. Numerical examples illustrate its performance on slowly fading 4 times 4 and 6 times 6 complex MIMO channels.