Showing papers on "Dirty paper coding published in 2017"
19 Mar 2017
TL;DR: NOMA cooperative scheme achieves an overall better outage performance than NOMA TDMA scheme and the theoretical analysis matches the simulation results very well.
Abstract: In this paper two different non-orthogonal multiple access (NOMA) relay schemes are analyzed, namely NOMA cooperative scheme and NOMA TDMA scheme. Both schemes apply NOMA in the first stage by sending NOMA superimposed signals to relays. Relays then forward the messages to two UEs in the second stage. In the second stage of NOMA cooperative scheme, two relays form a cooperative pair to simultaneously transmit the decoded signals to their respective recipients. Dirty paper coding is used as precoding to cancel out inter-user interference. The second stage of NOMA TDMA scheme uses TDMA to send to two users in two separate time slots. The outage probability is analyzed for both schemes and the impact of error propagation in the NOMA successive interference cancellation is analyzed and evaluated. Performance study shows that the theoretical analysis matches the simulation results very well. NOMA cooperative scheme achieves an overall better outage performance than NOMA TDMA scheme.
20 citations
TL;DR: In this article, a lattice coding and decoding scheme for the dirty paper channel was proposed, whose decision regions are independent of the channel realizations and whose achievable rates are within a constant gap to capacity for all signal and dirt powers.
Abstract: A multiple-input multiple-output (MIMO) version of the dirty paper channel is studied, where the channel input and the dirt experience the same fading process, and the fading channel state is known at the receiver. This represents settings where signal and interference sources are co-located, such as in the broadcast channel. First, a variant of Costa’s dirty paper coding is presented, whose achievable rates are within a constant gap to capacity for all signal and dirt powers. In addition, a lattice coding and decoding scheme is proposed, whose decision regions are independent of the channel realizations. Under Rayleigh fading, the gap to capacity of the lattice coding scheme vanishes with the number of receive antennas, even at finite Signal-to-Noise Ratio (SNR). Thus, although the capacity of the fading dirty paper channel remains unknown, this paper shows it is not far from its dirt-free counterpart. The insights from the dirty paper channel directly lead to transmission strategies for the two-user MIMO broadcast channel, where the transmitter emits a superposition of desired and undesired (dirt) signals with respect to each receiver. The performance of the lattice coding scheme is analyzed under different fading dynamics for the two users, showing that high-dimensional lattices achieve rates close to capacity.
14 citations
TL;DR: Theoretical and simulation results confirm that, in addition to supporting the normal transmission, the achievable secrecy rates of the proposed schemes can be close to that of the traditional AN scheme, which supports only the secure transmission of one user.
Abstract: This paper studies the secure transmission in a multiuser broadcast channel where only the statistical channel state information of the eavesdropper is available. We propose to apply secret dirty-paper coding (S-DPC) in this scenario to support the secure transmission of one user and the normal (unclassified) transmission of the other users. By adopting the S-DPC and encoding the secret message in the first place, all the information-bearing signals of the normal transmission are treated as noise by potential eavesdroppers and thus provide secrecy for the secure transmission. In this way, the proposed approach exploits the intrinsic secrecy of multiuser broadcasting and can serve as an energy-efficient alternative to the traditional artificial noise (AN) scheme. To evaluate the secrecy performance of this approach and compare it with the AN scheme, we propose two S-DPC-based secure transmission schemes for maximizing the secrecy rate under constraints on the secrecy outage probability (SOP) and the normal transmission rates. The first scheme directly optimizes the covariance matrices of the transmit signals, and a novel approximation of the intractable SOP constraint is derived to facilitate the optimization. The second scheme combines zero-forcing dirty-paper coding and AN, and the optimization involves only power allocation. We establish efficient numerical algorithms to solve the optimization problems for both schemes. Theoretical and simulation results confirm that, in addition to supporting the normal transmission, the achievable secrecy rates of the proposed schemes can be close to that of the traditional AN scheme, which supports only the secure transmission of one user.
13 citations
TL;DR: This paper examines superposition signaling for the general multiple-input multiple-output broadcast Gaussian interference networks and proposes a computationally efficient path-following procedure, which requires only a convex quadratic program for each iteration but ensures convergence at least to a locally optimal solution.
Abstract: It is known that superposition signaling in Gaussian interference networks is capable of improving the achievable rate region. However, the problem of maximizing the rate gain offered by superposition signaling is computationally prohibitive, even in the simplest case of two-user single-input single-output interference networks. This paper examines superposition signaling for the general multiple-input multiple-output broadcast Gaussian interference networks. The problem of maximizing either the sum rate or the minimal user’s rate under superposition signaling and dirty paper coding is solved by a computationally efficient path-following procedure, which requires only a convex quadratic program for each iteration but ensures convergence at least to a locally optimal solution. Numerical results demonstrate the substantial performance advantage of the proposed approach.
12 citations
TL;DR: In this paper, a generalized zero-forcing (GZF) precoder was proposed for multiuser multiple-input-single-output (MISO) broadcasting channels, where only the entries along the main diagonal and the first lower-diagonals can take nonzero values.
Abstract: In this paper, we consider precoder designs for multiuser multiple-input-single-output broadcasting channels. Instead of using a traditional linear zero-forcing (ZF) precoder, we propose a generalized ZF (GZF) precoder in conjunction with successive dirty-paper coding (DPC) for data transmissions, namely, the GZF-DP precoder, where the suffix “DP” stands for “dirty-paper.” The GZF-DP precoder is designed to generate a band-shaped and lower triangular effective channel ${F}$ , such that only the entries along the main diagonal and the $
u $ first lower-diagonals can take non-zero values. Utilizing the successive DPC, the known non-causal inter-user interferences from the other (up to) $
u $ users are canceled through successive encoding. We analyze optimal GZF-DP precoder designs both for sum-rate and minimum user-rate maximizations. Utilizing Lagrange multipliers, the optimal precoders for both cases are solved in closed-forms in relation to optimal power allocations. For the sum-rate maximization, the optimal power allocation can be found through water filling, but with modified water levels depending on the parameter $
u $ , while for the minimum user-rate maximization that measures the quality of the service, the optimal power allocation is directly solved in closed-form, which also depends on $
u $ . Moreover, we propose two low-complexity user-ordering algorithms for the GZF-DP precoder designs for both maximizations, respectively. We show, through numerical results, that the proposed GZF-DP precoder with a small $
u $ value (≤ 3) renders significant rate increments compared with the previous precoder designs, such as the linear ZF and the user-grouping-based DPC precoders.
11 citations
TL;DR: This work forms a downlink sum rate optimization problem that takes both intracell and intercell interference into account, and uses the convex conjugate to transform the problem into an unconstrained dual problem to find an optimal solution by applying a quasi-Newton algorithm with low complexity per iteration.
Abstract: We propose a precoding scheme to improve the downlink sum rate for a multicell massive multiple-input multiple-output (MIMO) system. We first present a low-complexity approach based on dirty paper coding and zero-forcing that combines a reduced form of QR decomposition and an orthogonal projection. We formulate a downlink sum rate optimization problem that takes both intracell and intercell interference into account, and then we use the convex conjugate to transform the problem into an unconstrained dual problem to find an optimal solution by applying a quasi-Newton algorithm with low complexity per iteration. We prove that the proposed algorithm exhibits faster convergence than other methods, and the numerical results verify that the proposed precoding design outperforms conventional precoding methods in multicell massive MIMO systems.
11 citations
TL;DR: A multiple-input multiple-output (MIMO) version of the dirty paper channel is studied, where the channel input and the dirt experience the same fading process, and the fading channel state is known at the receiver.
Abstract: A multiple-input multiple-output (MIMO) version of the dirty paper channel is studied, where the channel input and the dirt experience the same fading process and the fading channel state is known at the receiver (CSIR). This represents settings where signal and interference sources are co-located, such as in the broadcast channel. First, a variant of Costa's dirty paper coding (DPC) is presented, whose achievable rates are within a constant gap to capacity for all signal and dirt powers. Additionally, a lattice coding and decoding scheme is proposed, whose decision regions are independent of the channel realizations. Under Rayleigh fading, the gap to capacity of the lattice coding scheme vanishes with the number of receive antennas, even at finite Signal-to-Noise Ratio (SNR). Thus, although the capacity of the fading dirty paper channel remains unknown, this work shows it is not far from its dirt-free counterpart. The insights from the dirty paper channel directly lead to transmission strategies for the two-user MIMO broadcast channel (BC), where the transmitter emits a superposition of desired and undesired (dirt) signals with respect to each receiver. The performance of the lattice coding scheme is analyzed under different fading dynamics for the two users, showing that high-dimensional lattices achieve rates close to capacity.
11 citations
TL;DR: This paper presents the hybrid Tomlinson–Harashima VP (TH-VP) algorithm, a novel zero-forcing precoding scheme, which combines TH precoding to remove interuser interference, and VP precode to equalize each user's multiple spatial streams and shows that the two nonlinear techniques can be integrated in a single optimization.
Abstract: Vector perturbation (VP) is a nonlinear precoding technique that achieves near-capacity performance in multiuser multiple-input multiple-output systems at the expense of large complexity due to the search for the optimum perturbation vector. In this paper, we present the hybrid Tomlinson–Harashima VP (TH-VP) algorithm, a novel zero-forcing precoding scheme, which combines TH precoding to remove interuser interference, and VP precoding to equalize each user's multiple spatial streams. We show that the two nonlinear techniques can be integrated in a single optimization and that the proposed algorithm has lower computational requirements than any other. The performance of TH-VP is analyzed and simulation results show that TH-VP outperforms conventional zero-forcing VP and approaches the performance of dirty paper coding.
10 citations
TL;DR: This paper proposes a generalized ZF (GZF) precoder in conjunction with successive dirty-paper coding (DPC) for data transmissions, namely, the GZF-DP precoder, where the suffix “DP” stands for “dirty-paper.”
Abstract: In this paper, we consider precoder designs for multiuser multiple-input-single-output (MISO) broadcasting channels. Instead of using a traditional linear zero-forcing (ZF) precoder, we propose a generalized ZF (GZF) precoder in conjunction with successive dirty-paper coding (DPC) for data-transmissions, namely, the GZF-DP precoder, where the suffix \lq{}DP\rq{} stands for \lq{}dirty-paper\rq{}. The GZF-DP precoder is designed to generate a band-shaped and lower-triangular effective channel $\vec{F}$ such that only the entries along the main diagonal and the $
u$ first lower-diagonals can take non-zero values. Utilizing the successive DPC, the known non-causal inter-user interferences from the other (up to) $
u$ users are canceled through successive encoding. We analyze optimal GZF-DP precoder designs both for sum-rate and minimum user-rate maximizations. Utilizing Lagrange multipliers, the optimal precoders for both cases are solved in closed-forms in relation to optimal power allocations. For the sum-rate maximization, the optimal power allocation can be found through water-filling, but with modified water-levels depending on the parameter $
u$. While for the minimum user-rate maximization that measures the quality of the service (QoS), the optimal power allocation is directly solved in closed-form which also depends on $
u$. Moreover, we propose two low-complexity user-ordering algorithms for the GZF-DP precoder designs for both maximizations, respectively. We show through numerical results that, the proposed GZF-DP precoder with a small $
u$ ($\leq\!3$) renders significant rate increments compared to the previous precoder designs such as the linear ZF and user-grouping based DPC (UG-DP) precoders.
8 citations
TL;DR: Simulation results show that compared to previous DPC schemes, the proposed schemes require lower transmission power to maintain the bit error rate to be within $10^{-5}$ .
Abstract: Dirty paper coding (DPC) offers an information-theoretic result for pre-cancellation of known interference at the transmitter. In this letter, we propose practical DPC schemes that use only one error correction code. Our designs focus on practical use from the viewpoint of complexity. For fair comparison with previous schemes, we compute the complexity of proposed schemes by the number of operations used. Simulation results show that compared to previous DPC schemes, the proposed schemes require lower transmission power to maintain the bit error rate to be within $10^{-5}$ .
7 citations
01 Jun 2017
TL;DR: This paper presents an application-specific instruction-set processor (ASIP) for multiuser multiple-input multiple-output (MU-MIMO) broadcast precoding and program zero forcing dirty paper coding (ZF-DPC) to demonstrate the reusability of the ASIP.
Abstract: This paper presents an application-specific instruction-set processor (ASIP) for multiuser multiple-input multiple-output (MU-MIMO) broadcast precoding. The ASIP is designed for a base station (BS) with four antennas to perform user scheduling and precoding. Transport triggered architecture (TTA) is used as the processor template and high level language is used to program the ASIP. Several special function units (SFU) are designed to accelerate norm-based greedy user scheduling and minimum-mean square error (MMSE) precoding. We also program zero forcing dirty paper coding (ZF-DPC) to demonstrate the reusability of the ASIP. A single core provides a throughput of 52.17 Mbps for MMSE precoding and takes an area of 87.53 kgates at 200 MHz on 90 nm technology.
01 Oct 2017
TL;DR: It is proved that multi-user MIMO (MU-MIMO) can be a perfect candidate for mm-Wave massive MIMo communication system and good sum rate performance compared with the traditional digital beamforming is provided.
Abstract: To provide gigabit-per-second data rates for the next generation (5G) of mobile cellular communication system, one option is to leverage that has gained increasing traction is communications over the millimeter-wave (mm-Wave) regime where the carrier frequency is in the 30 to 300 GHz range, so that the small wavelengths of millimeter wave is allowed to encapsulate the number of antennas in small physical space to form a larger aperture an antenna array and achieve the desired high gain of the link. This paper develops a dirty paper coding based multi-user hybrid beamforming for downlink millimeter wave (mm-Wave) massive MIMO systems. The hybrid beamforming is designed indirectly by considering the solution of digital beamforming which is obtained from the dirty paper coding(DPC) technique. We assume that the channel state information(CSI) at the transmitter is perfect, and further we consider the problem of maximizing the sum rate. DPC is a method of beamforming such that the interference which is known to the transmitter can be canceled efficiently, achieve the optimal performance of the sum rate and the capacity of the multiple antenna mm-Wave channel. Simulation results show the proposed algorithm provide good sum rate performance compared with the traditional digital beamforming and obviously improved the sum rate with the increase in the number of users. It is proved that multi-user MIMO (MU-MIMO) can be a perfect candidate for mm-Wave massive MIMO communication system.
TL;DR: A zero-forcing dirty paper coding technique is applied to eliminate the multiuser interference and derive the closed-form optimal solution to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of ID users and ID/EH users.
Abstract: We study the energy harvesting problem in the Internet of Things with heterogeneous users, where there are three types of single-antenna users: ID users that only receive information, EH users that can only receive energy, and ID/EH users that receive information and energy simultaneously from a multiantenna base station via power splitting. We aim to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of the ID users and ID/EH users by jointly designing the power allocation at the transmitter and the power splitting strategy at the ID/EH receivers under the maximum transmit power and the minimum energy harvesting constraints. Specifically, we first apply the semidefinite relaxation (SDR), zero-forcing (ZF), and maximum ratio transmission (MRT) techniques to solve the nonconvex problems. We then apply the zero-forcing dirty paper coding (ZF-DPC) technique to eliminate the multiuser interference and derive the closed-form optimal solution. Numerical results show that ZF-DPC provides higher achievable minimum SINR than SDR and ZF in most cases.
01 Jan 2017
TL;DR: This work discussed the statistical eigenmode (SE) and zero-forcing (ZF) in Ricean fading channels regarding the ergodic sum-rate capacity, and proposed a new solution method to find an optimum beam-vector, which maximise the SLNR and lead to increase the system capacity directly.
Abstract: Multi User-Multiple Input Multiple Output (MU-MIMO) wireless communication systems, can provide substantial downlink throughput in millimetre wave (mmW) communication by allowing multiple users to communicate on the same frequency and time slots. However, the design of an optimum beam-vector for each user to minimise the interference from other users is challenging. In this work, based on the concept of signal to leakage plus noise ratio (SLNR), we discuss the statistical eigenmode (SE) and zero-forcing (ZF) in Ricean fading channels regarding the ergodic sum-rate capacity. Moreover, also we show the effects of the number of antenna elements, on the achievable rate obtained by dirty paper coding method (DPC). Furthermore, we proposed a new solution method to find an optimum beam-vector, which maximise the SLNR and lead to increase the system capacity directly. The proposed method is based on power approximation, to find the most dominant eigenvector iteratively, to minimise the co-channel interference (CCI). Compared the proposed method with the singular value decomposition (SVD) solution, our proposed method achieved higher performance than SVD regarding achievable sum rate. Indeed, the maximum achieved average system capacity, for our proposed method is almost two times of the capacity achieved by SVD.
Proceedings Article•
01 Nov 2017TL;DR: The proposed approach is capable of achieving the same performance as that of the zero-forcing (ZF) algorithm over Rayleigh fading channels at the SU receiver and the BER performance of the PU under Rician fading channel is significantly improved for the proposed study.
Abstract: In this paper, the bit error rate (BER) performance analysis of an underlay cognitive radio (CR) network, which is considered as a broadcast scheme, over fading channels, is investigated. Particularly, the underlay CR network is studied as a closed loop multiple antenna system, presented with dirty paper coding (DPC) approach with the aim of allowing the secondary user (SU) transmission to utilize the spectrum resources efficiently and avoiding harmful interference to the primary user (PU) receiver. The proposed approach is capable of achieving the same performance as that of the zero-forcing (ZF) algorithm over Rayleigh fading channels at the SU receiver. We further show that the BER performance of the PU under Rician fading channel is significantly improved for the proposed study. Finally, numerical and simulation results are provided to demonstrate the performance and corroborate the theoretical analysis.
01 Sep 2017
TL;DR: A gradient descent (GD) method is proposed to compute the uplink precoder in each MAC problem which has low complexity and validates the better performance of the proposed algorithm over conventional linear precoding method.
Abstract: In this paper, we aim to maximize the total energy efficiency for a multi-cell MIMO broadcast channel with dirty paper coding, where both the base stations and users employ multiple antennas The EE metric is defined as the ratio of the total sum- rate to the total power consumption Because the original problem is non-convex and difficult to tackle directly, we employ the fractional programming and iterative linear approximation methods to transform it into a set of sub-problems After using Lagrange dual decomposition, each sub- problem essentially becomes a precoding design problem in MIMO broadcast channel (BC) and is still non-convex, which is then dealt with via BC- multiple access channel (MAC) duality property Specifically, we propose a gradient descent (GD) method to compute the uplink precoder in each MAC problem which has low complexity Thus, the dual BC problem can be solved and each BS can iteratively update its precoding matrices with small amount of information exchange among the base stations Numerical results validate the better performance of our proposed algorithm over conventional linear precoding method
Journal Article•
TL;DR: An optimization problem to maximize the achievable rate of the MIMO cognitive radio network under the constraints of power limits of each transmitter, where the requirement of not affecting PU’s transmission rate is also incorporated.
Abstract: 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. 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.
Using location base protocols try to improve avaibility rate of SU (secondary user).and use threshold approach to allow certain node which take a part in CR.
01 Dec 2017
TL;DR: This paper proposes a MU-C-MIMO scheme using dirty paper coding (DPC), a nonlinear precoding method, in order to realize the most ideal precoding characteristics, and evaluates the effectiveness of this scheme through numerical simulations.
Abstract: The multi-user multiple-input multiple-output (MU-MIMO) scheme is one of the main methods for improving the frequency-efficiency in wireless communication systems. In MU-MIMO systems, a base station equipped with multiple antennas and a large number of receivers with multiple antennas communicate simultaneously. Conventionally, we adopted the principle of chaos communications to MU-MIMO and proposed a multi-user chaos MIMO (MU-C-MIMO) scheme that has physical layer security between each receiver. In the previous study, we utilized block diagonalization (BD) — a liner precoding method — to remove interference components in MU-C-MIMO. On the one hand, channel gain for each user is not maximized in BD. On the other hand, the gain maximization can be realized using nonlinear precoding, and further improvement of transmission quality is expected in MU-C-MIMO. Therefore, in this paper, we propose a MU-C-MIMO scheme using dirty paper coding (DPC), a nonlinear precoding method, in order to realize the most ideal precoding characteristics. The effectiveness of this scheme is evaluated through numerical simulations with comparisons to a conventional MU-C-MIMO system with BD.
01 May 2017
TL;DR: An infinite vector model of Witsenhausen's counterexample is studied and a new bound for the cost function is derived and it is shown that this bound improves upon previously known bounds obtained by dirty paper coding in some SNR regimes.
Abstract: There is a growing concern regarding the design of decentralized control systems. Witsenhausen's counterexample is a well-known problem which has remained open in this context, and emphasizes the necessity of communication between blocks in a distributed control system. In this paper, we study an infinite vector model of this problem and a new bound for the cost function is derived. It is shown that this bound improves upon previously known bounds obtained by dirty paper coding in some SNR regimes. Consequently, a system can be designed to sense the SNR level and then select the best scheme between these two sub-optimal strategies.
01 Apr 2017
TL;DR: This paper focuses on image applications in this paper, where it encodes priors on possible image domain shift factors such as viewpoint, lighting, blur and appearance variations and utilize geometric adaptation mechanisms to perform clustering.
Abstract: We address domain adaptation in the context of clustering where we are given a set of unlabeled data, coming from several domains, and the goal is to group data into different categories regardless of the domain they come from. This is a challenging problem since we do not have any supervision unlike most adaptation scenarios studied earlier, and is very relevant in practical industry applications where labeled data often comes at a premium especially while deploying services that do not have a comparable predecessor. Our philosophy in addressing this problem draws motivation from the concept of dirty paper coding, a communications technique where the signal being transmitted through a noisy channel is encoded with priors on the possible noise patterns to assist reliable decoding of the signal at the receiver. We focus on image applications in this paper, where we encode priors on possible image domain shift factors such as viewpoint, lighting, blur and appearance variations and utilize geometric adaptation mechanisms to perform clustering. We illustrate the utility of our approach on standard datasets involving objects and faces, by obtaining around 18% improvement on average over existing approaches.
01 May 2017
TL;DR: This paper applies the techniques of semidefinite relaxation and zero-forcing to solve the non-convex problems in a multi-user MISO broadcast system, and shows that ZF-DPC provides higher achievable minimum SINR than SDR and ZF in most cases.
Abstract: In this paper, we study the power allocation and power splitting problem for simultaneous wireless information and power transfer (SWIPT) in a multi-user MISO broadcast system, in which there are two types of single-antenna users: traditional users that only receive information and modern users that receive information and energy simultaneously from a multi-antenna base station via power splitting. We aim to maximize the minimum signal to interference plus noise ratio (SINR) of the users by jointly designing the power allocation at the transmitter and the power splitting strategy at the receivers under the maximum transmit power and the minimum energy harvesting constraints. In specific, we first apply the techniques of semidefinite relaxation (SDR) and zero-forcing (ZF) to solve the non-convex problems. Then we apply the zero forcing dirty paper coding (ZF-DPC) technique to eliminate the multi-user interference and derive the optimal solution in closed-form. Numerical results show that ZF-DPC provides higher achievable minimum SINR than SDR and ZF in most cases.
TL;DR: Aiming to co-channel interference (CCI) for LTE downlink multi-user MIMO-OFDM system, maximizing the successive signal to leakage plus noise ratio (SSLNR) interference cancellation algorithm based on Pre-processing is proposed.
TL;DR: Two interference cancellation schemes, Block Diagonalization (BD) and Dirty Paper Coding (DPC) are discussed and performance comparison of block diagonalization and dirty paper coding schemes in term of Bit Error Rate Keywords-Multiuser MIMO, Block diagonalization, DPC is shown.
Abstract: In Multiuser MIMO system, multiple antennas are placed on base station and also on multiple users. Multiple antennas technique enhanced the performance parameters like reliability and data rate of wireless communication system without required more bandwidth, multiple antennas at transmitting and receiving end provides transmitting and receiving diversity, diversity increases the reliability of signal and spatial multiplexing increases the data rate by transmitting multiple information streams between transmitter and receiver. The base station transmits multiple streams to mobile station through downlink channel, known as broadcast channel and mobile users also transmit multiple streams to base station through uplink channel, known as multiple access channel. This paper considers only broadcast channel, the major issue in information transmission in broadcast channel is that the desired signal on the receiving side is affected by other user interference as well as inter-antenna interference. So, interference cancellation schemes on the transmitting end plays very important role to reduced interference on receiving end in multiuser MIMO wireless communication system. This paper discusses two interference cancellation schemes, Block Diagonalization (BD) and Dirty Paper Coding (DPC). Block Diaganalization is linear precoding technique that is used at transmitting end and it uses singular value decomposition operation to get block diagonalization precoding weights. Dirty Paper Coding is non-linear precoding technique; this technique is applied only when channel gains are completely known at transmitting end. This paper also shows performance comparison of block diagonalization and dirty paper coding schemes in term of Bit Error Rate Keywords-Multiuser MIMO, Block Diagonalization, DPC.
01 Jan 2017
TL;DR: This chapter describes how error-correcting codes can be used to impress additional information onto waveforms with a minimal level of distortion, for applications including watermarking and steganography.
Abstract: This chapter describes how error-correcting codes can be used to impress additional information onto waveforms with a minimal level of distortion. Applications include watermarking and steganography. It is shown how the modified Dorsch decoder of Chap. 15 may be used to find codewords from partitioned classes of codewords, whose waveforms may be used as a watermark which is almost invisible, and still be reliably detected.
14 Jul 2017
TL;DR: The proposed scheme has superior bit error rate (BER) performance compared with the existing algorithm, when BER is 10−4, SNR is improved about 4 dB, and the sum-capacity is improved by pre-processing Matrix.
Abstract: Aiming to co-channel interference (CCI) and multi-stream for LTE downlink multi-user multiple input multiple output orthogonal frequency division multiple (MIMO-OFDM) system, a successive signal to leakage plus noise ratio (SLNR) with geometric mean decomposition (GMD) for downlink multi-user multi-stream MIMO systems based on pre-processing matrix is proposed. The algorithm utilizes precoding matrix based on SSLNR scheme to process emission signal at the transmitter, and the known leakages is canceled by dirty paper coding (DPC) algorithm. GMD is applied to cancel the known leakages, as all subchannels for this system have identical signal noise ratio (SNR), it is more convenient to reduce the influence of gain. Moreover, the received signal is treated by preconditioned matrix, the interference between different users is eliminated in further, the sum-capacity is improved by pre-processing Matrix. Meanwhile, the proposed scheme has no restriction of the number of antennas. The performance improvement is verified by simulation, the proposed scheme has superior bit error rate (BER) performance compared with the existing algorithm, when BER is 10−4, SNR is improved about 4 dB.
TL;DR: This paper proposes energy efficient RUB systems that select the optimal number of streams and transmission power to maximize energy efficiency (EE) by using the statistical characteristics of RUB, which have been studied in previous works.
Abstract: Random unitary beamforming (RUB) achieves multiuser diversity gain over multiple-input multiple-output broadcast channels with partial channel state information (CSI). RUB can asymptotically achieve the same growth of rate $M\log \log K$ as the optimal dirty paper coding or sub-optimal zero-forcing beamforming, which need full CSI at the transmitter. In this paper, we propose energy efficient RUB systems that select the optimal number of streams and transmission power to maximize energy efficiency (EE). In contrast to other beamforming schemes that use full CSI, optimizing RUB in terms of EE is a difficult task due to the CSI constraints. To solve this problem, we first select the EE-optimal number of streams and transmission power by using the statistical characteristics of RUB, which have been studied in previous works. Next, based on partial CSI feedback from users, we propose the method whereby the transmitter of RUB can adaptively control the transmission power. Simulation results demonstrate that our proposed systems can improve the EE performance of RUB and that the analytical results derived in this paper are accurate.