Showing papers on "Dirty paper coding published in 2013"

Multi-user MISO broadcasting for indoor visible light communication

Abstract: In this paper, we study multi-user multi-input single-output (MU-MISO) broadcasting for visible light communication (VLC). VLC differs from radio frequency communication in both baseband signal format and optical power constraints. We propose a precoding and biasing model for MU-MISO transmitter design in indoor VLC. We formulate and solve optimization problems for maximizing max-min fairness or throughput subject to per transmitting unit optical power constraint. We apply linear zero forcing and zero forcing dirty paper coding techniques and compare them in simulations.

Approximative matrix inverse computations for very-large MIMO and applications to linear pre-coding systems

Abstract: In very-large multiple-input multiple-output (MIMO) systems, the base station (BS) is equipped with very large number of antennas as compared to previously considered systems. There are various advantages of increasing the number of antennas, and some schemes require handling large matrices for joint processing (pre-coding) at the BS. The dirty paper coding (DPC) is an optimal pre-coding scheme and has a very high complexity. However, with increasing number of BS antennas, linear pre-coding performance tends to that of the optimal DPC. Although linear pre-coding is less complex than DPC, there is a need to compute pseudo inverses of large matrices. In this paper we present a low complexity approximation of down-link Zero Forcing (ZF) linear pre-coding for very-large multi-user MIMO systems. Approximation using a Neumann series expansion is opted for inversion of matrices over traditional exact computations, by making use of special properties of the matrices, thereby reducing the cost of hardware. With this approximation of linear pre-coding, we can significantly reduce the computational complexity for large enough systems, i.e., where we have enough BS antenna elements. For the investigated case of 8 users, we obtain 90% of the full ZF sum rate, with lower computational complexity, when the number of BS antennas per user is about 20 or more.

Approximative Matrix Inverse Computations for Very-large MIMO and Applications to Linear Pre-coding Systems

Abstract: In very-large multiple-input multiple-output (MIMO) systems, the BS (base station) is equipped with very large number of antennas as compared to previously considered systems. There are various advantages of increasing the number of antennas, and some schemes would require handling large matrices for joint processing (pre-coding) at the base station. The dirty paper coding (DPC) is an optimal pre-coding scheme and has a very high complexity. However with increasing number of BS antennas linear pre-coding performance tends to that of the optimal DPC. Although linear pre-coding is less complex than DPC, there is a need to compute pseudo inverses of large matrices. In this paper we present a low complexity approximation of down-link Zero Forcing linear pre-coding for very-large multi-user MIMO systems. Approximation using a Neumann series expansion is opted for inversion of matrices over traditional exact computations, by making use of special properties of the matrices, thereby reducing the cost of hardware. With this approximation of linear pre-coding, we can significantly reduce the computational complexity for large enough systems, i.e., where we have enough BS antenna elements. For the investigated case of 8 users, we obtain 90% of the full ZF sum rate, with lower computational complexity, when the number of BS antennas per user is about 20 or more. (Less)

The Secrecy Capacity Region of the Gaussian MIMO Broadcast Channel

Abstract: In this paper, we consider a scenario where a source node wishes to broadcast two confidential messages for two respective receivers via a Gaussian multiple-input multiple-output (MIMO) broadcast channel. An eavesdropper also receives the transmitted signal via another MIMO channel. We first consider the discrete memoryless channel and obtain the capacity region of the degraded channel. The secret dirty paper coding (SDPC) region as an achievable rate region for the general discrete channel is introduced. Relying on the results for the discrete channel, we fully characterize the secrecy capacity region of MIMO broadcast channel. It is shown that the SDPC scheme is optimal. The converse part of the proof relies on the generalized Costa's entropy power inequality and a new channel enhancement strategy in which we only need to enhance the channels of the legitimate receivers, and the channel of the eavesdropper remains unchanged.

Beamformer Designs for MISO Broadcast Channels with Zero-Forcing Dirty Paper Coding

Abstract: We consider the beamformer design for multiple-input multiple-output (MISO) broadcast channels (MISO BCs) using zero-forcing dirty paper coding (ZF-DPC). Assuming a sum power constraint (SPC), most previously proposed beamformer designs are based on the QR decomposition (QRD), which is a natural choice to satisfy the ZF constraints. However, the optimality of the QRD-based design for ZF-DPC has remained unknown. In this paper, first, we analytically establish that the QRD-based design is indeed optimal for any performance measure under a SPC. Then, we propose an optimal beamformer design method for ZF-DPC with per-antenna power constraints (PAPCs), using a convex optimization framework. The beamformer design is first formulated as a rank-1-constrained optimization problem. Exploiting the special structure of the ZF-DPC scheme, we prove that the rank constraint can be relaxed and still provide the same solution. In addition, we propose a fast converging algorithm to the beamformer design problem, under the duality framework between the BCs and multiple access channels (MACs). More specifically, we show that a BC with ZF-DPC has the dual MAC with ZF-based successive interference cancellation (ZF-SIC). In this way, the beamformer design for ZF-DPC is transformed into a power allocation problem for ZF-SIC, which can be solved more efficiently.

Weighted Sum Rate Maximization for MIMO Broadcast Channels Using Dirty Paper Coding and Zero-forcing Methods

Abstract: We consider precoder design for maximizing the weighted sum rate (WSR) of successive zero-forcing dirty paper coding (SZF-DPC). For this problem, the existing precoder designs often assume a sum power constraint (SPC) and rely on the singular value decomposition (SVD). The SVD-based designs are known to be optimal but require high complexity. We first propose a low-complexity optimal precoder design for SZF-DPC under SPC, using the QR decomposition. Then, we propose an efficient numerical algorithm to find the optimal precoders subject to per-antenna power constraints (PAPCs). To this end, the precoder design for PAPCs is formulated as an optimization problem with a rank constraint on the covariance matrices. A well-known approach to solve this problem is to relax the rank constraints and solve the relaxed problem. Interestingly, for SZF-DPC, we are able to prove that the rank relaxation is tight. Consequently, the optimal precoder design for PAPCs is computed by solving the relaxed problem, for which we propose a customized interior-point method that exhibits a superlinear convergence rate. Two suboptimal precoder designs are also presented and compared to the optimal ones. We also show that the proposed numerical method is applicable for finding the optimal precoders for block diagonalization scheme.

Cognitive Orthogonal Precoder for Two-Tiered Networks Deployment

Abstract: In this work, the problem of cross-tier interference in a two-tiered (macro-cell and cognitive small-cells) network, under the complete spectrum sharing paradigm, is studied. A new orthogonal precoder transmit scheme for the small base stations, called multi-user Vandermonde-subspace frequency division multiplexing (MU-VFDM), is proposed. MU-VFDM allows several cognitive small base stations to coexist with legacy macro-cell receivers, by nulling the small- to macro-cell cross-tier interference, without any cooperation between the two tiers. This cleverly designed cascaded precoder structure, not only cancels the cross-tier interference, but avoids the co-tier interference for the small-cell network. The achievable sum-rate of the small-cell network, satisfying the interference cancelation requirements, is evaluated for perfect and imperfect channel state information at the transmitter. Simulation results for the cascaded MU-VFDM precoder show a comparable performance to that of state-of-the-art dirty paper coding technique, for the case of a dense cellular layout. Finally, a comparison between MU-VFDM and a standard complete spectrum separation strategy is proposed. Promising gains in terms of achievable sum-rate are shown for the two-tiered network w.r.t. the traditional bandwidth management approach.

State-dependent Gaussian Z-channel with mismatched side-information and interference

Abstract: A state-dependent Gaussian Z-interference channel model is investigated in the regime of high state power, in which transmitters 1 and 2 communicate with receivers 1 and 2, and only receiver 2 is interfered by transmitter 1's signal and a random state sequence. The state sequence is known noncausally only to transmitter 1, not to the corresponding transmitter 2. A layered coding scheme is designed for transmitter 1 to help interference cancelation at receiver 2 (using a cognitive dirty paper coding) and to transmit its own message to receiver 1. Inner and outer bounds are derived, and are further analyzed to characterize the boundary of the capacity region either fully or partially for all Gaussian channel parameters. Our results imply that the capacity region of such a channel with mismatched transmitter-side state cognition and receiver-side state interference is strictly less than that of the corresponding channel without state, which is in contrast to Costa type of dirty channels, for which dirty paper coding achieves the capacity of the corresponding channels without state.

On the Dispersions of the Gel'fand-Pinsker Channel and Dirty Paper Coding

Abstract: This paper studies second-order coding rates for memoryless channels with a state sequence known non-causally at the encoder. In the case of finite alphabets, an achievability result is obtained using constant-composition random coding, and by using a small fraction of the block to transmit the type of the state sequence. For error probabilities less than 1/2, it is shown that the second-order rate improves on an existing one based on i.i.d. random coding. In the Gaussian case (dirty paper coding) with an almost-sure power constraint, an achievability result is obtained used using random coding over the surface of a sphere, and using a small fraction of the block to transmit a quantized description of the state power. It is shown that the second-order asymptotics are identical to the single-user Gaussian channel of the same input power without a state.

Energy efficiency optimization in MIMO broadcast channels with fairness constraints

Abstract: We consider the minimization of the energy per bit (or, equivalently, the maximization of the energy efficiency) in multiple-input multiple-output (MIMO) broadcast channels with rate balancing constraints for fairness between users, and we propose a framework to find the globally optimal energy-efficient solution, which relies on dirty paper coding (DPC). The main idea is to introduce a continuous, differentiable, and concave optimal rate function, which transforms the problem into a convex-concave fractional program in one scalar variable. This not only allows an efficient solution, but also an intuitive interpretation of the method as well as the possibility to extend the method to related problems. In numerical simulations, we compare the energy efficiency with and without fairness constraints.

On MMSE Vector-Perturbation Precoding for MIMO Broadcast Channels With Per-Antenna-Group Power Constraints

Abstract: Recently, studies on suboptimal precoding techniques for multiple-input multiple-output broadcast channels (MIMO-BC), which achieve performance near to that of the dirty paper coding (DPC), have drawn attention to vector perturbation (VP) precoding. In practice, each antenna or more generally each antenna group has its own limit on the transmitted power, which makes per-antenna-group power constraints more meaningful than the sum power constraint. In this paper, we introduce an optimization technique for VP precoding employing the minimum mean-square error (MMSE) criterion with per-antenna-group power constraints. This technique is inspired by the p-sphere encoding in a sense that it involves finding the node with the lowest mean-square error (MSE) over a lattice. We demonstrate that the MSE metric, as well as the p-norm one, can be enclosed in a proper Frobenius-norm ball. This Frobenius-norm ball shrinks until it captures the perturbing vector minimizing the MSE. Numerical results show that the proposed algorithm outperforms conventional VP precoding and the p-sphere encoding, but at higher complexity. Consequently, we investigate a couple of simplified techniques employing the MMSE criterion, which perform almost as well as the proposed precoding technique, but are less complex.

Approximate Sum-Capacity of K-user Cognitive Interference Channels with Cumulative Message Sharing

Abstract: This paper considers the K user cognitive interference channel with one primary and K-1 secondary/cognitive transmitters with a cumulative message sharing structure, i.e cognitive transmitter $i\in [2:K]$ knows non-causally all messages of the users with index less than i. We propose a computable outer bound valid for any memoryless channel. We first evaluate the sum-rate outer bound for the high- SNR linear deterministic approximation of the Gaussian noise channel. This is shown to be capacity for the 3-user channel with arbitrary channel gains and the sum-capacity for the symmetric K-user channel. Interestingly. for the K user channel having only the K th cognitive know all the other messages is sufficient to achieve capacity i.e cognition at transmitter 2 to K-1 is not needed. Next the sum capacity of the symmetric Gaussian noise channel is characterized to within a constant additive and multiplicative gap. The proposed achievable scheme for the additive gap is based on Dirty paper coding and can be thought of as a MIMO-broadcast scheme where only one encoding order is possible due to the message sharing structure. As opposed to other multiuser interference channel models, a single scheme suffices for both the weak and strong interference regimes. With this scheme the generalized degrees of freedom (gDOF) is shown to be a function of K, in contrast to the non cognitive case and the broadcast channel case. Interestingly, it is show that as the number of users grows to infinity the gDoF of the K-user cognitive interference channel with cumulative message sharing tends to the gDoF of a broadcast channel with a K-antenna transmitter and K single-antenna receivers. The analytical additive additive and multiplicative gaps are a function of the number of users. Numerical evaluations of inner and outer bounds show that the actual gap is less than the analytical one.

A new practical interference mitigation scheme for interference cognitive radio networks

Abstract: SUMMARY In this paper, a new practical dirty paper coding scheme and its extension is proposed for interference mitigation of a single TV broadcast station in uplink and downlink of a cognitive radio network using both a single secondary user (SU) and multiple SU scenarios. In the single SU scenario, which is called interference cognitive radio channel, derived simulation results show that the transmission rate of the SU archives the capacity of an AWGN channel with the cost of a 2.5 dB extra signal-to-noise ratio. In the sequel, the proposed scheme is extended to a multiple SU scenario using direct sequence spread spectrum technique in both uplink and downlink considering a TV band. Derived simulation results show that the number of supportable SUs in our proposed scheme increases to a fully loaded scenario of the same multiuser direct sequence spread spectrum system. Copyright © 2012 John Wiley & Sons, Ltd.

Spectrum sharing on interference channels with a cognitive relay

Abstract: We consider a cognitive spectrum sharing system on an interference channel with a cognitive relay (IFC-CR) assisting both the primary and secondary users in forwarding their messages to the respective destination nodes. The CR uses a successive interference cancelation scheme to decode the primary and secondary messages after a first transmission phase. The CR performs power allocation and in the second transmission phase, forwards a linear weighted combination of the decoded primary and secondary messages. We demonstrate that with a properly designed power allocation, secondary spectrum sharing is achieved and at the same time a better performance can be achieved for the primary user than the case without spectrum sharing. The proposed spectrum sharing scheme further does not require any non-causal knowledge of the primary message at the secondary user or at the CR.

Coverage by pairwise base station cooperation under adaptive geometric policies

Abstract: We study a cooperation model where the positions of base stations follow a Poisson point process distribution and where Voronoi cells define the planar areas associated with them. For the service of each user, either one or two base stations are involved. If two, these cooperate by exchange of user data and reduced channel information (channel phase, second neighbour interference) with conferencing over some backhaul link. The total user transmission power is split between them and a common message is encoded, which is coherently transmitted by the stations. The decision for a user to choose service with or without cooperation is directed by a family of geometric policies. The suggested policies further control the shape of coverage contours in favor of cell-edge areas. Analytic expressions based on stochastic geometry are derived for the coverage probability in the network. Their numerical evaluation shows benefits from cooperation, which are enhanced when Dirty Paper Coding is applied to eliminate the second neighbour interference.

Relay Channel with Orthogonal Components and Structured Interference Known at the Source

Abstract: A relay channel with orthogonal components in which the destination is affected by an interference signal that is non-causally available only at the source is studied. The interference signal has structure in that it is produced by another transmitter communicating with its own destination. Moreover, the interferer is not willing to adjust its communication strategy to minimize the interference. Knowledge of the interferer's signal may be acquired by the source, for instance, by exploiting HARQ retransmissions on the interferer's link. The source can then utilize the relay not only for communicating its own message, but also for cooperative interference mitigation at the destination by informing the relay about the interference signal. Proposed transmission strategies are based on partial decode-and-forward (PDF) relaying and leverage the interference structure. Achievable schemes are derived for discrete memoryless models, Gaussian and Ricean fading channels. Furthermore, optimal strategies are identified in some special cases. Finally, numerical results bring insight into the advantages of utilizing the interference structure at the source, relay or destination.

On the coexistence of primary and secondary users in spectrum-sharing broadcast channels

Abstract: In this paper, we consider a broadcast channel in spectrum-sharing networks, where the base station schedules licensed primary users (PUs) and cognitive secondary users (SUs) simultaneously. Based on such a framework, we present a transmission strategy in the light of dirty paper coding. In order to promise the PUs' quality of service (QoS) in the broadcasting, the base station chooses codewords for the users by taking into account that the codewords pertaining to SUs can be pre-subtracted from those pertaining to PUs as if there were no interference from the secondary's data to the primary's data. For the purpose of performance evaluation, by taking capacity behavior and bit error rate (BER) as metrics, we study the achievable data rate regions for both types of users with the introduced design, and analyze the BER performance in corresponding systems implemented with hierarchical modulation. Numerical results substantiate that with flexible management of the spectrum resources, our proposed scheme provides more communication opportunities for SUs while maintaining PUs' QoS at an acceptable level.

A Robust Multi-Level Design for Dirty-Paper Coding

Abstract: We propose a robust close-to-capacity dirty-paper coding (DPC) design framework in which multi-level low density parity check (LDPC) codes and trellis coded quantization (TCQ) are employed as the channel and source coding components, respectively. The proposed design framework is robust in the sense that it yields close to capacity solutions in the high-, medium-, and low-rate regimes. This is in contrast to existing practical DPC schemes that perform well only in one or two of these regimes, but not all three. We design codes for transmission rates of 0.5, 1.0, 1.5, and 2.0 bits/sample (b/s) using one, two, three, and four LDPC levels; at a block length of 2×105, the codes perform 0.95, 0.58, 0.55, and 0.54 dB from the corresponding information theoretic limits, respectively. We also propose a low-complexity decoding scheme that does not involve iterative message passing between the source and channel decoders; the low-complexity scheme performs only 1.08, 0.85, and 0.79 dB away from the theoretical limits at transmission rates of 1.0, 1.5, and 2.0 b/s, respectively.

Gaussian state amplification with noisy state observations

Abstract: The problem of simultaneous message transmission and state amplification in a Gaussian channel with additive Gaussian state is studied when the sender has imperfect non-causal knowledge of the state sequence. Inner and outer bounds to the rate-state-distortion region are provided. The coding scheme underlying the inner bound combines analog signaling and Gelfand-Pinsker coding, where the latter deviates from the operating point of Costa's dirty paper coding.

Sum-rate maximization in the multicell MIMO broadcast channel with interference coordination

Abstract: This paper is concerned with the maximization of the weighted sum-rate (WSR) in a multicell multiple-input multiple-output (MIMO) broadcast channel (BC). Studied is the multicell network operating on the same frequency channel 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 at 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 complex. By applying a successive convex approximation technique, this work proposes a distributed algorithm that efficiently achieves a locally optimal solution. Simulations then show that the proposed algorithm can significantly improve the network-wide sum-rate, compared to the schemes with linear precoding or no interference coordination between the BSs.

Rewriting flash memories and dirty-paper coding

Abstract: This paper considers that write-once memory (WOM) codes can be seen as a type of dirty-paper code. The current state of the memory, which is known to the encoder, plays the role of the known interference of dirty-paper coding. Erez, Shamai and Zamir showed that lattice strategies can achieve the capacity of the known-interference channel. In this paper, lattices are used to design a WOM code. Encoding is performed modulo a shaping lattice with respect to a lattice fundamental region to obtain a codeword, to be added to the current state of the memory. The fundamental region is designed to accommodate the limitations of the flash memory system, particularly, that values can only increase. The criterion for evaluation is average number of writes. In order to improve the average number of writes, “coset select” bits are introduced, to maximize the average number of writes. For an eight-dimensional lattice, numerical results for practical parameter choices show a promising trend.

Performance Limits of a Cloud Radio

Abstract: Cooperation in a cellular network is seen as a key technique in managing other cell interference to observe a gain in achievable rate. In this paper, we present the achievable rate regions for a cloud radio network using a sub-optimal zero forcing equalizer with dirty paper precoding. We show that when complete channel state information is available at the cloud, rates close to those achievable with total interference cancellation can be achieved. With mean capacity gains, of up to 2 fold over the conventional cellular network in both uplink and downlink, this precoding scheme shows great promise for implementation in a cloud radio network. To simplify the analysis, we use a stochastic geometric framework based of Poisson point processes instead of the traditional grid based cellular network model. We also study the impact of limiting the channel state information and geographical clustering to limit the cloud size on the achievable rate. We have observed that using this zero forcing-dirty paper coding technique, the adverse effect of inter-cluster interference can be minimized thereby transforming an interference limited network into a noise limited network as experienced by an average user in the network for low operating signal-to-noise-ratios. However, for higher signal-to-noise-ratios, both the average achievable rate and cell-edge achievable rate saturate as observed in literature. As the implementation of dirty paper coding is practically not feasible, we present a practical design of a cloud radio network using cloud a minimum mean square equalizer for processing the uplink streams and use Tomlinson-Harashima precoder as a sub-optimal substitute for a dirty paper precoder in downlink.

On the Sum Rate Capacity of MIMO Broadcast Channels in Cognitive Radio Networks with Interference Power Constraints

Abstract: This paper investigates the sum rate capacity of MIMO broadcast channels (MIMO-BCs) in cognitive radio networks. A suboptimal user-selection algorithm is proposed to achieve a large sum rate capacity with reduced complexity. This algorithm consists of two steps. First, zero-forcing beamforming is utilized as a downlink precoding technique that precancels inter-user interference. Second, singular value decomposition is applied to the channel matrices of all the secondary users and only consider the singular vectors corresponding to the maximum singular values. The proposed user-selection algorithm chooses singular vectors which are nearly orthogonal to each other and nearly orthogonal to the vector of primary users. With this algorithm, the sum rate capacity of MIMO-BCs in CR networks with interference power constraints and transmit power constraints is derived. We formulate the sum rate capacity as a multi-constraint optimization problem and develop an algorithm to solve the problem in its equivalent form. Finally, numerical simulations are conducted to corroborate our theoretical results in flat Rayleigh fading environments. It is shown that the proposed algorithms are capable of achieving a large sum rate capacity with a very low complexity.

Two-Phase Scheduling and Leakage-Based Precoding in Wireless Cellular Networks

Abstract: We consider the downlink of a wireless cellular network where the base stations are equipped with multiple antennas and operate in the same frequency band. Since scheduling changes the spatial transmit signal processing with each time slot, information from neighboring base stations is required for data encoding. This can, in theory, be accomplished by a high-capacity backhaul network through which the base stations exchange channel state information (CSI) and other control signals. In reality, however, the temporal granularity of the scheduler does not allow for timely distribution of CSI among base stations. We propose a two-phase scheduler which optimizes the precoding in the first phase and allows the users to feed back their instantaneous interference power in the second phase. For the single-user case, we present a practical scheme that combines two-phase scheduling with precoders that maximize the signal-to-leakage-plus-noise ratio. If the users feed back the interference power together with a supported rate, communication between base stations can be limited to integers. By comparing the performance to multi-user two-phase scheduling with dirty paper coding and to algorithms that share CSI among base stations we show that two-phase scheduling is a technically and practically feasible solution to deal with non-stationary intercell interference.

Dirty paper coding using trellis-coded modulation

Abstract: Although the information theoretic result referred to as “dirty paper coding” [1] has been known for quite a while, it has not led to schemes that look attractive enough for real-life communication systems. In a companion paper [2], we presented the concept of sum codes and showed how they provide a convenient platform for interference suppression via dirty paper coding. In this paper, we present a dirty paper coding scheme based on trellis-coded modulation, which could be looked upon as an alternative to the sum-codes-based approach. Since trellis-coded modulation is designed for multi-level signal constellations, it is expected to work well as a platform for the proposed dirty paper coding scheme in which multi-level signal constellations play a critical role.

Optimal interference pre-cancellation order in DPC-based broadcast and unicast hybrid network

Abstract: It is well known that the Dirty Paper Coding (DPC) achieves the channel capacity for multiuser degraded channels. However, the optimality of DPC remains unknown for nondegraded channel. In this paper, we derive the optimal interference pre-cancellation order for a DPC based broadcast and unicast hybrid network. Specifically, we study different DPC cancellation schemes to maximize the hybrid capacity region. The conditions for each scheme being optimal are analytically derived. Our results show that the optimal interference precancellation order varies with SNR and broadcast and unicast channel conditions.

Energy efficiency optimization in the multiantenna downlink with linear transceivers

Abstract: Optimization of transmit strategies with linear transceivers in multiple-input multiple-output (MIMO) broadcast channels generally leads to nonconvex problems, which cannot be solved efficiently in a globally optimal manner. Instead, it is necessary to resort to suboptimal algorithms. In this paper, we evaluate the application of a gradient descent algorithm for the optimization of the energy efficiency in such a system. Since the quality of the obtained locally optimal solutions depends on the initialization, a successive stream allocation is introduced and combined with the gradient algorithm. Comparison with a globally optimal reference algorithm for the special case of single receive antennas shows that the obtained solutions are close to the global optimum. For the MIMO case, the energy per bit achievable with dirty paper coding, which is a lower bound for the case of linear transceivers, is used as benchmark, and good performance of the gradient-based methods is shown for MIMO systems as well.

Dirty paper coding using “sum codes”

Abstract: While the information theoretic result commonly referred to as “dirty paper coding” [1] has been known for long, it has not led to practical schemes that can be implemented easily in real-life communication systems. In this paper, we present the concept of sum codes and show how they provide a convenient platform for dirty paper coding. Comb-combined sum codes, which provide a convenient method of sum-code construction, are particularly useful in this respect. One can build comb-combined sum codes based on any linear block code to achieve reduction in the transmit energy required to attain a desired performance. Using an example based on tail-biting convolutional codes, we show how practical dirty paper coding may be implemented using any convenient linear block code.

Dirty Paper Coding for Gaussian Cognitive Z-Interference Channel: Performance Results

Abstract: In this paper, we present a practical application of dirty paper coding (DPC) for the Gaussian cognitive Z-interference channel. A two stage transmission scheme is proposed in which the cognitive transmitter first obtains the interference signal from the primary transmitter and then uses DPC to improve the performance of the cognitive link. Numerical results show that causal knowledge of the interference provides more than 3 dB improvement in performance in certain scenarios over a scheme that does not use interference cancellation. Results are also shown when the cognitive transmitter operates in both half-duplex and full-duplex modes.