Showing papers on "Dirty paper coding published in 2014"

Cooperative Non-Orthogonal Multiple Access in Heterogeneous Networks

Abstract: In order to address the ever increasing high capacity demands, next generation wireless networks are required to revolutionize the infrastructure design and air interface technologies. In this paper, we introduce a cooperative non-orthogonal multiple access (NOMA) technique with successive interference cancellation (SIC) in wireless heterogeneous networks. Aiming to improve the system capacity, the cooperative NOMA scheme exploits both NOMA and dirty paper coding (DPC), based on which a resource scheduling optimization problem is formulated. The optimization problem is a combinatorial mixed-integer non-linear problem. A genetic algorithm is used to solve the problem with a low computational complexity. Simulation results show that the proposed cooperative NOMA scheme can significantly improve the network capacity.

Sum-Rate Maximization in the Multicell MIMO Broadcast Channel With Interference Coordination

Abstract: This paper studies the precoding designs to maximize the weighted sum-rate (WSR) in a multicell multiple-input multiple-output (MIMO) broadcast channel (BC). We consider a multicell network under universal frequency reuse with multiple mobile stations (MS) per cell. With interference coordination (IC) between the multiple cells, the base-station (BS) at each cell only transmits information signals to the MSs within its cell using the dirty paper coding (DPC) technique, while coordinating the inter-cell interference (ICI) induced to other cells. The main focus of this work is to jointly optimize the encoding covariance matrices across the BSs in order to maximize the network-wide WSR. Since this optimization problem is shown to be nonconvex, obtaining its globally optimal solution is highly complicated. To address this problem, we consider two low-complexity solution approaches with distributed implementation to obtain at least locally optimal solutions. In the first approach, by applying a successive convex approximation technique, the original nonconvex problem is decomposed into a sequence of simpler problems, which can be solved optimally and separately at each BS. In the second approach, the WSR problem is solved via an equivalent problem of weighted sum mean squared error minimization. Both solution approaches will unfold the control signaling among the coordinated BSs to allow their distributed implementation. Simulation results confirm the convergence of the proposed algorithms, as well as their superior performances over schemes with linear precoding or no interference coordination among the BSs.

On the Capacity of the Two-User Gaussian Causal Cognitive Interference Channel

Abstract: This paper considers the two-user Gaussian causal cognitive interference channel (GCCIC), which consists of two source-destination pairs that share the same channel and where one full-duplex cognitive source can causally learn the message of the primary source through a noisy link. The GCCIC is an interference channel with unilateral source cooperation that better models practical cognitive radio networks than the commonly used model which assumes that one source has perfect noncausal knowledge of the other source's message. First, the sum-capacity of the symmetric GCCIC is determined to within a constant gap. Then, the insights gained from the study of the symmetric GCCIC are extended to more general cases. In particular, the whole capacity region of the Gaussian Z-channel, i.e., when there is no interference from the primary user, and of the Gaussian S-channel, i.e., when there is no interference from the secondary user, are both characterized to within 2 bits. The fully connected general, i.e., no-symmetric, GCCIC is also considered and its capacity region is characterized to within 2 bits when, roughly speaking, the interference is not weak at both receivers. The parameter regimes where the GCCIC is equivalent, in terms of generalized degrees-of-freedom, to the noncooperative interference channel (i.e., unilateral causal cooperation is not useful), to the non-causal cognitive interference channel (i.e., causal cooperation attains the ultimate limit of cognitive radio technology), and to bilateral source cooperation are identified. These comparisons shed light into the parameter regimes and network topologies that in practice might provide an unbounded throughput gain compared to currently available (non cognitive) technologies.

The impact of phase fading on the dirty paper coding channel

Abstract: The impact of phase fading and side information on the classic Costa's dirty paper coding channel is studied. A variation of this model is considered in which the channel state is affected by a phase fading sequence which is known at the receiver but not at the transmitter. Although the capacity of this channel has been established, it is expressed as the solution of the maximization which cannot be easily determined. To circumvent such difficulty, we derive alternative inner and outer bounds to capacity and determine a regime in which the two expressions are to within a finite distance. We consider two distributions of the phase fading process: circular binomial and circular uniform. For circular binomial fading we show that binning with Gaussian signaling approaches capacity, as in the channel without phase fading. When fading is circular uniform, instead, binning with Gaussian signaling is no longer effective and novel interference avoidance strategies are developed for this case.

A New Watermarking Scheme Based on Antipodal Binary Dirty Paper Coding

Abstract: We investigate the performance of a watermarking system in which the encoder is forced to use a binning strategy based on antipodal binary-valued sequences. The use of antipodal binary random binning has several advantages, including the possibility of relying on simple and effective binary code constructions and the ease with which this kind of schemes can cope with amplitude scaling. By relying on a novel binning strategy, we derive a lower bound of the Gelfand-Pinsker capacity of the watermark channel when the encoder is forced to use an antipodal binary auxiliary random variable, showing that for low to moderate bit-rates, the bound coincides with Costa’s capacity. We exploit the properties of the new binning strategy, to develop a practical watermarking system and show that the new scheme outperforms previous constructions, exhibiting very good performance also in the presence of gain attack. Preliminary results on audio signals show that the new scheme retains its good performance also when used for the watermarking of real multimedia data.

Writing on dirty flash memory

Abstract: The most important challenge in the scaling down of flash memory is its increased inter-cell interference (ICI). If side information about ICI is known to the encoder, the flash memory channel can be viewed as similar to Costa's “writing on dirty paper (dirty paper coding).” We first explain why flash memories are dirty due to ICI. We then show that “dirty flash memory” can be changed into “memory with defective cells” model by using only one pre-read operation. The asymmetry between write and erase operations in flash memory plays an important role in this change. Based on the “memory with defective cells” model, we show that additive encoding can significantly improve the probability of decoding failure by using the side information.

Energy Efficiency of Hybrid Cellular With Heterogeneous QoS Provisions

Abstract: In this letter, we consider a hybrid broadcast and unicast cellular network ( hybrid cellular for short) with heterogeneous quality of service (QoS) constraints in the low-power regime. In particular, we consider the unicast user with delay constraint and the broadcast user with outage constraint. The transmission energy efficiency of the dirty paper coding (DPC) and time division multiple access (TDMA) schemes are analyzed and compared from information theoretic point of view. Specifically, the minimum energy per bit and the wideband slope region are derived in closed forms. While both DPC and TDMA schemes require the same minimum energy per bit, DPC outperforms TDMA with regard to the wideband slope region. We also obtain the critical points for both schemes beyond which the wideband slope decreases for both unicast and broadcast users. Finally, we show how the heterogeneous QoS constraints affect the energy efficiency in hybrid cellular.

The Impact of Phase Fading on the Dirty Paper Channel.

Abstract: The impact of phase fading on the classical Costa dirty paper coding channel is studied. We consider a variation of this channel model in which the amplitude of the interference sequence is known at the transmitter while its phase is known at the receiver. Although the capacity of this channel has already been established, it is expressed using an auxiliary random variable and as the solution of a maximization problem. To circumvent the difficulty evaluating capacity, we derive alternative inner and outer bounds and show that the two expressions are to within a finite distance. This provide an approximate characterization of the capacity which depends only on the channel parameters. We consider, in particular, two distributions of the phase fading: circular binomial and circular uniform. The first distribution models the scenario in which the transmitter has a minimal uncertainty over the phase of the interference while the second distribution models complete uncertainty. For circular binomial fading, we show that binning with Gaussian signaling still approaches capacity, as in the channel without phase fading. In the case of circular uniform fading, instead, binning with Gaussian signaling is no longer effective and novel interference avoidance strategies are developed to approach capacity.

Dirty paper coding with partial channel state information

Abstract: In this paper we study the effect of partial channel state information (CSI) on the performance of dirty paper coding (DPC) schemes. We derive a novel lower bound that shows that the effect of the CSI is upper bounded by the effect of an additive white Gaussian noise with an appropriate variance. The bound is proved using a constructive proof that shows that the predicted rates are achievable using high dimensional lattice modulo precoding schemes. Simulation results demonstrate the usefulness of the bound. The derived bound is useful for the characterization of the interference mitigation performance in partial CSI scenarios such as FDD networks with finite rate feedback, uplink downlink capacity balancing in cooperative cellular networks, etc'.

Joint network and dirty-paper coding for multi-way relay networks with pairwise information exchange

Abstract: In this paper we study two-stage decode-and-forward coding schemes for relaying with multi-pair information exchange. A joint network and dirty-paper coding (JNDPC) scheme is proposed to serve as a basic element for coding in the broadcast stage. The JNDPC scheme embeds network coding into dirty-paper coding, which allows interference cancelation while fully utilizing the user side information. By using JNDPC, we propose a novel successive network coding (SNC) scheme where the interference to each pair of users are canceled simultaneously. The SNC scheme consists of two layers. The first layer consists of JNDPC to cancel interference at the encoder. In the second layer, JNDPC is sequentially organized to facilitate successive decoding at the decoders. The SNC scheme has a fixed decoding order and hence suffers a rate loss for users. With JNDPC, we then propose a rate-splitting SNC scheme which, together with SNC, outperform the state of the art schemes. For the multiple access stage, a full decode multiple access scheme and a functional decode multiple access scheme are presented. The achievable regions of all proposed broadcast and multiple stage coding schemes are established.

Trellis shaping based dirty paper coding scheme for the overlay cognitive radio channel

Abstract: In this paper, we propose a dirty paper coding (DPC) scheme that uses trellis shaping for the overlay cognitive radio channel, where a cognitive user and a primary user transmit concurrently in the same spectrum. Interference of the primary user is assumed to be known at the cognitive transmitter non-causally. Based on this knowledge, the shaping code selection, as a key feature of the proposal, is introduced which enables the constellation to be self adaptively changed. The performance of our proposed scheme is compared using simulations with that based on the conventional trellis shaping and it achieves excellent tradeoff between performance and complexity.

Spectrum-sharing broadcast channels using fountain codes: energy, delay and throughput

Abstract: In this study, the authors develop a transmission protocol for cognitive radio networks, whereby fountain codes are exploited in the broadcast channels and secondary users help with the broadcast from the base station (BS) to primary users (PUs). With fountain codes, the BS broadcasts to the secondary transmitter (ST) as well as PUs simultaneously, and stops broadcasting once the ST has received sufficient codeword to decode the original information reliably. Then, the ST will resume the broadcasting to PUs until all of them can decode the original information successfully. While broadcasting, the ST transmits information over its own link, that is, to the secondary receiver, based on dirty paper coding technique. As such, the energy expenditure at the BS is reduced and, moreover, secondary links have more opportunities to access the licensed spectrum band. To evaluate the performance of the developed scheme, they analyse its energy expenditure, broadcast time as well as the throughput over secondary links, and achieve the corresponding closed-form expressions. Compared with the traditional broadcast protocol without the secondary's help, illustrative numerical results substantiate the validity of the author's derivations, which also demonstrate the efficiency of the developed scheme both on the energy savings and on the spectrum utilisation.

Capacity Region of MISO Broadcast Channel for Simultaneous Wireless Information and Power Transfer

Abstract: This paper studies a multiple-input single-output (MISO) broadcast channel (BC) featuring simultaneous wireless information and power transfer (SWIPT), where a multi-antenna access point (AP) delivers both information and energy via radio signals to multiple single-antenna receivers simultaneously, and each receiver implements either information decoding (ID) or energy harvesting (EH). In particular, pseudo-random sequences that are {\it a priori} known and therefore can be cancelled at each ID receiver is used as the energy signals, and the information-theoretically optimal dirty paper coding (DPC) is employed for the information transmission. We characterize the capacity region for ID receivers under given energy requirements for EH receivers, by solving a sequence of weighted sum-rate (WSR) maximization (WSRMax) problems subject to a maximum sum-power constraint for the AP, and a set of minimum harvested power constraints for individual EH receivers. The problem corresponds to a new form of WSRMax problem in MISO-BC with combined maximum and minimum linear transmit covariance constraints (MaxLTCCs and MinLTCCs), which differs from the celebrated capacity region characterization problem for MISO-BC under a set of MaxLTCCs only and is challenging to solve. By extending the general BC-multiple access channel (MAC) duality, which is only applicable to WSRMax problems with MaxLTCCs, and applying the ellipsoid method, we propose an efficient algorithm to solve this problem globally optimally. Furthermore, we also propose two suboptimal algorithms with lower complexity by assuming that the information and energy signals are designed separately. Finally, numerical results are provided to validate our proposed algorithms.

On the dispersion of dirty paper coding.

Abstract: Reference EPFL-CONF-203555 URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6875240 Record created on 2014-11-25, modified on 2017-05-10

Energy-efficient delay-tolerant communication: Revisiting optimality of superposition coding in broadcast channels

Abstract: Communication can consume a significant fraction of the energy for many simple sensor devices for which battery life is an important consideration in deployment. Battery power is consumed not only by transmit power amplifier but also in the radio frequency circuits and digital processors during transmission and reception. When communication requirements are bursty, many devices incorporate a ‘sleep’ state where the circuit power consumption is also reduced by turning circuits off. Delaying transmission can allow devices to sleep more and conserve energy. We consider the optimal tradeoff between receiver energy consumption and average throughput, and derive insights on multi-user downlink communication. We reformulate the problem with generalized power constraints on the transmitter's and the receiver's power consumption: depending on their states, either transmit/receive or sleep, they consume different amounts of power. We show how these changes of power constraints affect average spectral efficiency. In Gaussian broadcast channels, taking into account the receivers' power constraints, we show that multi-user transmission schemes, previously proven to be optimal for maximizing spectral efficiency, such as superposition coding and dirty paper coding (DPC) are not always optimal. We characterize the condition, under which these schemes remain optimal, in terms of receivers' power constraints. These models are suited for machine-to-machine (M2M) communications and wireless sensor networks where 1) transmitters and/or receivers are battery-powered devices, 2) their locations are static once deployed, and 3) their data characteristic is not delay-sensitive.

Dirty paper coding and decoding method based on joint lattice forming technology in cognitive network

Abstract: The invention provides a dirty paper coding and decoding method based on a joint lattice forming technology in a cognitive network, and the method is applicable to the occasion that a main network has only one main user and a cognitive wireless network has multiple secondary users. The method includes the specific steps that to guarantee that a signal to noise ratio of a main user receiving end is not changed, secondary user sending ends forward a sending signal of the main user while the secondary user sending ends send the corresponding signals through multiple transmitting antennas of the secondary user sending ends; grouping is conducted on signals transmitted to all secondary user receiving ends through the secondary user sending ends, channel coding and joint lattice forming coding are conduced respectively, and then a coding bit sequence is mapped into a symbol sequence and zero-forcing dirty paper coding is conducted so as to eliminate interference of other users; signals sent out by the main user are overlapped and then transmitted to multiple secondary user receiving ends through a channel by means of multiple transmitting antennas of a main user sending end so as to improve secondary user receiving performance. A traditional channel convolutional decoding method, namely signal restoring, is adopted for the secondary user receiving ends respectively. The method is simple in operation steps, lower in calculation complexity and high in practicability.

A Lower Bound on the Data Rate of Dirty Paper Coding in General Noise and Interference

Abstract: Dirty paper coding (DPC) allows a transmitter to send information to a receiver in the presence of interference that is known (non-causally) to the transmitter. The original version of DPC was derived for the case where the noise and the interference are statistically independent Gaussian random sequences. More recent works extended this approach to the case where the noise and the interference are mutually independent and at least one of them is Gaussian. In this letter we further extend the DPC scheme by relaxing the Gaussian and statistical independence assumptions. We provide lower bounds on the achievable data rates in a DPC setting for the case of possibly dependent noise, interference and input signals. Also, the interference and noise terms are allowed to have arbitrary probability distributions. The bounds are relatively simple, are phrased in terms of second-order statistics, and are tight when the actual noise distribution is close to Gaussian.

On the Achievable Rate of MIMO Cognitive Radio Network with Multiple Secondary Users

Abstract: This paper investigates the achievable rate of MIMO cognitive radio network when one primary user (PU) and multiple secondary users (SU) are present, where the latter adopt dirty paper coding (DPC) to cancel the interference of PU's transmission at their receivers. Perfect channel state information is assumed at receivers, while only the statistic information of channels are known at the transmitters. We formulate an optimization problem to maximize the achievable rate of the system under the constraints of power limits of each transmitter, where the requirement of not affecting PU's transmission rate is also incorporated. An algorithm is proposed to jointly determine the inflation factors in DPC method and the input covariance matrix of each SU. Simulations show that the proposed problem achieves better achievable rate when compared with the existing results without compromising PU's transmission rate.

A Practical Dirty Paper Coding Scheme Based on LDPC Codes

Abstract: In this paper, we present a practical Dirty Paper Coding (DPC) scheme using sum codes based on LDPC codes. While a typical sum-code-based DPC scheme uses a constrained decoder as part of the encoding operation, such an approach fails in the case of LDPC codes since the constrained decoder based on a standard LDPC decoder tends to get stuck at highly suboptimal points in typical scenarios. We get around this difficulty via a simple code construction method based on bit- mapping or permutation. Examples included in this paper show that compared to standard communication schemes the proposed DPC scheme yields substantial savings in terms of the

The modulo loss in lattice dirty-paper coding

Abstract: Lattice decoding of a lattice-shaped codebook is a simple alternative for ML decoding, and it is equivalent to ML decoding after modulo-lattice reduction of the channel output. For good (high-dimensional) lattices, this modulo operation is information lossless in the presence of AWGN. At a finite shaping dimension, however, the lattice decoder is inferior to direct ML decoding from the channel output. The “modulo loss” is particularly large at low SNR, and it gets up to 4dB for scalar shaping. We consider the effect of a known interference (i.e., a dirty-paper channel) on the gap between the two decoders. We show that in the limit of a strong interference, the modulo output becomes a sufficient statistic for decoding the input. Thus, in the strong-interference regime, ML decoding suffers the same “modulo loss” as lattice decoding.

Coordinated Tomlinson-Harashima precoding design algorithms for overloaded multi-user MIMO systems

Abstract: Tomlinson-Harashima precoding (THP) is a nonlinear processing technique employed at the transmit side to implement the concept of dirty paper coding (DPC). The application of THP is restricted by the dimensionality constraint that the number of transmit antennas has to be greater or equal to the total number of receive antennas. In this paper, we propose an iterative coordinate THP algorithm for overloaded scenarios in which the total number of receive antennas is larger than the number of transmit antennas. The proposed algorithm is implemented on two types of THP structures, the decentralized THP (dTHP) with diagonal weighted filters at the receivers of the users, and the centralized THP (cTHP) with diagonal weighted filter at the transmitter. Simulation results show that a significantly better bit error rate (BER) and sum-rate performances can be achieved by the proposed iterative coordinate THP algorithm as compared to previously reported techniques.

Dirty-paper coding techniques for compound MISO broadcast channels: ca DoF analysis

Abstract: This work investigates optimal Degrees of Freedom (DoF) achieving schemes for the MISO Compound Broadcast Channels (BC) where a source is equipped with M antennas, and communicates with 2 single antennas receivers. We develop a modified Dirty Paper Coding scheme that yields the optimal DoF for some Compound MISO BCs in the complex field. This coding scheme offers a “non-linear” alternative to interference alignment at the receivers which yields higher rates in the finite ranges of power. For asymptotic power regimes, it allows for fractional DoF of 1/2, while being of simple formulation and straightforward application to secondary transmissions in Compound Cognitive networks.

Two-way writing on dirty paper in the presence of noise-dependent interference

Abstract: In this paper, we characterize the capacity regions of the Gaussian doubly dirty two-way channel (DD-TWC) in the presence of noise-dependent interference as well as input-dependent interference, and thereby we quantify the impact of such dependencies on the capacity region of the Gaussian DD-TWC. We also show that for the Gaussian DD-TWC with noise/input-dependent interference, adaptation (the use of formerly received signals in encoding process) is useless from a capacity point of view. The above-mentioned claims are proved by obtaining a capacity outer bound in the adaptive mode which is coincided with capacity inner bound derived in the non-adaptive mode.

Improving the Performance of the Zero-Forcing Multiuser MISO Downlink Precoder through User Grouping

Abstract: We consider the Multiple Input Single Output (MISO) Gaussian Broadcast channel with $N_t$ antennas at the base station (BS) and $N_u$ single-antenna users in the downlink. We propose a novel user grouping precoder which improves the sum rate performance of the Zero-Forcing (ZF) precoder specially when the channel is ill-conditioned. The proposed precoder partitions all the users into small groups of equal size. Downlink beamforming is then done in such a way that, at each user's receiver the interference from the signal intended for users not in its group is nulled out. Intra-group interference still remains, and is cancelled through successive interference pre-subtraction at the BS using Dirty Paper Coding (DPC). The proposed user grouping method is different from user selection, since it is a method for precoding of information to the selected (scheduled) users, and not for selecting which users are to be scheduled. Through analysis and simulations, the proposed user grouping based precoder is shown to achieve significant improvement in the achievable sum rate when compared to the ZF precoder. When users are paired (i.e., each group has two users), the complexity of the proposed precoder is $O(N_u^3) + O(N_u^2 N_t)$ which is the same as that of the ZF precoder.

On bounds and capacity of Cognitive Multiple Access Z-Interference Channel

Abstract: In this paper, we introduce the Cognitive Multiple Access Z Interference Channel (CMAZIC) where there are two secondary user (SU) transmitters and one SU receiver and one primary user (PU) transceiver pair. Both the SUs are aware of the PU message non causally. There is interference only from the PU transmitter to the SU receiver but not vice versa. We study the Discrete Memoryless CMAZIC (DM-CMAZIC) and provide achievable rate regions with and without superposition coding at the PU transmitter and with Gelfand Pinsker coding against the interference of the PU at both the SU transmitters. For the Gaussian case we show that the inner bound without superposition coding is capacity achieving when appropriate Dirty paper coding is performed at the SU transmitters.

Energy efficiency maximization in downlink multiuser MIMO systems: An asymptotic analysis approach

Abstract: With tremendous power shortage and raising voice of greener energy usage, energy efficiency (EE) maximization in MIMO systems has received much attention in next generation wireless communications. Within recent years, there has been a lot of great work on power allocation and antenna selection in order to maximize EE under holistic power models. However, it is not a trivial work to derive a closed-form solution for energy efficiency optimization. In this paper, an asymptotic approach is adopted to obtain the analytical solutions of the EE optimal transmission schemes, as well as its performance limits. More specifically, we are interested in the capacity achieving dirty paper coding (DPC) and practical low-complexity zeroforcing beamforming (ZFBF), where EE is optimized with and without total power constraint. Closed-form formulas are given to determine the EE optimal number of antennas and transmit power. The proposed asymptotic analysis matches well with the numerical results when the number of users is moderately large, i.e., over 30.

Flat fading channel estimation based on Dirty Paper Coding

Abstract: Channel estimation is a transversal problem in signal processing (for example, it is used in digital communications, image restoration, digital forensics, acoustics, etc.). Among channel estimation algorithms, pilot-based estimation techniques stand out as being among the most frequently used. These techniques devote part of the total available power, which is usually limited, to send pilot signals that are used later to estimate the channel. The frequent need to send pilot signals in order to be able to track the channel variations, which lowers the information rate, becomes as one of their major drawbacks. Recently, the idea of concurrently sending a known training sequence with the information-bearing signal (also known as host) by means of arithmetically adding both sequences was proposed. These techniques are usually referred as superimposed training techniques. By implementing this idea, there is no drop in the information rate; however, part of the power available to send the information must be used by the added superimposed sequence thus causing a power loss in the information-bearing sequence. In addition, the original signal interferes with the pilot sequence of the superimposed training techniques, causing a decrease in the estimate performance, which is measured in terms of mean square error between the estimation and the actual channel gain. To tackle this issue, some solutions have been provided that use part of the power to partial cancel the host-interference. In this thesis, we have found a connection between superimposed training and digital watermarking. Indeed, this partially cancellation of the host of pilot sequences, known as PDD was independently proposed in digital watermarking, where is called ISS. We propose to obtain full cancellation of host-interference for estimation by applying the DPC paradigm that successfully was used in digital watermarking with several implementations (e.g., SCS, DC-DM, etc.). Specifically in this thesis, first we focus on the study of the flat fading channel estimation based on dirty paper coding for the case of real valued signals. Due to its interesting asymptotic properties, we design our estimation technique using MLE. In order to do that, the pdf of the random variables modeling the involved signals is required; in general, those pdfs are hard to handle mathematically and, as a consequence, so is the MLE cost function. Therefore, we have proposed a set of approximations of the pdf whose accuracy is validated in the cases for which they have been designed. In addition, a modification of the technique whenever the variances of the original signal and the channel noise are unknown is presented. In addition, this thesis proposes how to make full use of the Spread-Transform (an established concept of digital watermarking) to estimate the channel gain. In addition, a theoretical study is introduced following an estimation theory perspective, which indicates that asymptotically our scheme is not only not harmed by the host but it helps for estimation, and an information theory perspective, whose results determine that the induced structure of the transmitted signal helps the estimation of the gain of the channel. Both analyses show an improvement on the estimation performance of our technique with respect to Spread-Spectrum and PDD. The computational and time requirements needed to implement MLE, even using our pdf approximations, are not affordable in many applications. To tackle this, we introduce a set of MLE-based practical algorithms for estimation, designed with computational and temporal constraints. These algorithms take advantage of the statistical and deterministic properties of the problem. Several performance tests, measuring the accuracy of our algorithm, indicate that it outperforms other existing techniques whenever the structure of the sent signal becomes patent, and requires much shorter computational time than other existing DPC-based estimation techniques. With the aim of gaining insight into the wide range of practical uses of our algorithms, this thesis presents a set of applications of the proposed technique. For example, we use our algorithms to make dirty paper coding watermarking robust to gain attacks. By using both synthetic signals and real images, the obtained results validate the efficacy of our techniques in dealing with such attacks. We also show, in a flat fading channel communications scenario, how to equalize the gain estimated with our algorithms. The results show that our techniques improve the performance with respect to equalizing techniques based either on the second moment estimation or on superimposed training. Finally, we also propose how to adapt our estimation algorithm to the case of complex signals and complex gains, whose performance indicates that host also helps in the estimation.

Joint beamforming and transmit design for the non-regenerative MIMO broadcast relay channel

Abstract: In this paper, we consider a multiple-input multiple-output (MIMO) broadcast relay channel (BRC), in which the communication of a multi-antenna base station (BS) with several multi-antenna mobile stations (MS) is assisted by a fixed half-duplex multi-antenna relay station (RS). Applying dirty paper coding (DPC) at the BS and beamforming at the RS, we jointly optimize the transmit covariance matrices at the BS and the beamforming matrix at the RS by maximizing the system sum rate, which is a nonconvex problem. To solve this problem, we resort to the more tractable sum rate maximization in the dual multiple access relay channel (MARC), which is still a nonconvex difference of convex functions (DC) programming problem. We develop an iterative algorithm, termed alternating matrix polynomial time DC (POTDC) algorithm, based on an alternating optimization of the beamforming matrix and the transmit covariance matrices. The resulting covariance matrices for the MARC are then mapped to the desired BRC covariance matrices. The sum rate performance of the proposed algorithm is demonstrated by simulations.

MIMO-based achievable rate on cognitive radio network with multiple primary users

Abstract: In this paper, a cognitive radio network with multiple licensed users is considered. A dirty paper coding (DPC) based cooperation scheme for the Gaussian multiple-in-multiple-out (MIMO) cognitive radio network (CRN) with partial transmitter side information is studied. The problem of maximizing the sum-rate of MIMO CRN with multiple primary users over the transmitter covariance matrices, which is formulated as an optimization problem, is dealt with. Such an optimization, which needs to be performed jointly with the inflator factors under the DPC-based strategy, is solved by an iterative suboptimal solutions. Simulation results show that the proposed scheme is able to greatly improve the achievable rate performance in CRN.