Showing papers on "Dirty paper coding published in 2015"

Sum rate optimization for MIMO non-orthogonal multiple access systems

Abstract: Non-orthogonal multiple access (NOMA) is expected to be a promising technique for future wireless networks due to its superior spectral efficiency. In this paper, the sum rate optimization problem for multiple-input multiple-output (MIMO) NOMA systems is studied with the total transmit power constraint and the minimum rate constraint of weak user. We first derive a channel state information (CSI) condition in which MIMO NOMA systems can achieve full rate transmission, i.e. the transmission rate of the weak user equals to the channel capacity of weak user. Based on the CSI condition, we propose an optimal power allocation scheme for MIMO NOMA systems, which can achieve the capacity region of MIMO Broadcast channel as dirty paper coding. A low complexity suboptimal scheme is proposed as well for all CSI channel conditions. Numerical results show that the proposed NOMA schemes significantly outperform the traditional time division based single user MIMO scheme and the multi-user MIMO scheme.

MU-MIMO precoding for VLC with imperfect CSI

Abstract: This paper investigates the performance of different precoding schemes for a multi-user MIMO VLC system with channel estimation errors, an assumption that is commonly neglected in the literature. In particular, dirty paper coding, channel inversion, and block diagonalization, are considered for interference mitigation under imperfect channel state information. The impact of the variation of the beam angles of the transmitters and the field of view (FOV) of the receivers on the system performance is also examined. Simulation results reveal that, dirty paper coding provides the best performance under perfect channel state information (CSI). However, under imperfect CSI, suboptimal linear precoding schemes will give better performance. Furthermore, tuning the transmitting angles and the FOVs can significantly improve the system performance.

Improving throughput for downlink multi user MIMO-LTE advanced networks using SINR approximation and hierarchical CSI feedback

Abstract: In multi user MIMO-LTE advanced networks, the main issue is related to signal to noise ratio SINR mismatch which can result in reduced throughput and performance. Also the conventional code books may result in feedback overhead when the channels change slowly. Hence in this paper, we propose downlink multi user MIMO-LTE advanced networks using SINR approximation and hierarchical CSI feedback. Initially, signal and spatially correlated flat fading channels model of MU-MIMO is defined. Then a signal to noise ratio SINR approximation techniques is employed which utilises the channel state information at the base station. An advance structural codebook and an idea of hierarchical feedback are introduced. The main idea of hierarchical feedback is that if the channel is altered slowly, the channel state information feedback can be aggregated over multiple feedback intervals so that the aggregated bits index a larger codebook. There are pre-defined numbers of levels in a hierarchical codebook tree. This increased codebook size can effectively improve the performance of MU-MIMO. By simulation results, we show that the proposed technique improves the throughput and reduces the overhead.

Energy Efficiency Optimization With Interference Alignment in Multi-Cell MIMO Interfering Broadcast Channels

Abstract: Characterizing the fundamental energy efficiency (EE) performance of multiple-input–multiple-output interfering broadcast channels (MIMO-IFBC) is important for the design of green wireless system. In this paper, we propose a new network architecture proposition based on EE maximization for Multi-Cell MIMO-IFBC within the context of interference alignment (IA). Particularly, EE is maximized subject to maximum power and minimum throughput constraints. We propose two schemes to optimize EE for different signal-to-noise ratio (SNR) regions. For high-SNR operating regions, we employ a grouping-based IA scheme to jointly cancel intra- and inter-cell interferences and thus transform the MIMO-IFBC to a single-cell MIMO scenario. A gradient-based power adaptation scheme is proposed based on water-filling power adaptation and singular value decomposition to maximize EE for each cell. For moderate SNR cases, we propose an approach using dirty paper coding (DPC) with the principle of multiple access channel and broadcast channel duality to perform IA while maximizing EE in each cell. The algorithm in its dual form is solved using a subgradient method and a bisection searching scheme. Simulation results demonstrate the superior performance of the proposed schemes over several existing approaches. It also shows that interference-nulling-based IA approaches outperform hybrid DPC-IA approach in high-SNR region, and the opposite occurs in low-SNR region.

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, where a multiantenna 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, pseudorandom sequences that are a priori known and therefore can be cancelled at each ID receiver are used as the energy signals, and the information-theoretically optimal dirty paper coding is employed for the information transmission. We characterize the capacity region for ID 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 duality, which is only applicable to WSRMax problems with MaxLTCCs, and applying the ellipsoid method, we propose an efficient iterative 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.

A computationally efficient genetic algorithm for MIMO broadcast scheduling

Abstract: Graphical abstractDisplay Omitted HighlightsMultiple-input multiple-output (MIMO) is suitable technique to ensure high speed data transmission as well as low delay communication networksIn MIMO, dirty paper coding (DPC) is an efficient scheme to support multiple users with optimum sum rate capacity of the system However, DPC is a complex scheme where the user encoding sequence is important to transmit data to multiple usersAn optimal exhaustive search as used in DPC is prohibited due to the extremely large size of the search space in this optimization problemEvolutionary algorithm (genetic algorithm) can be used as an alternative for this optimization problem to reduce the complexity of the search (scheduling problem) The performance of the genetic algorithm with elitism and adaptive mutation is demonstrated to be near optimal as obtained with an exhaustive search It has been demonstrated in this paper that GA achieves about 98-99% of system sum rate as obtained with DPC with significant reduction in time and computational complexityThe proposed BGA is able to provide the optimum solution well within the packet duration of modern wireless packet data communications In conventional single-input single-output (SISO) systems, the capacity is limited as base station can provide service to only one user at any instant However, multiuser (MU) multiple-input multiple-output (MIMO) systems deliver optimum system capacity by providing service to multiple users (as many as transmit antennas) simultaneously according to dirty paper coding (DPC) scheme However, DPC is an exhaustive search algorithm (ESA) where the user encoding sequence is important to transmit data to multiple users Exhaustive search becomes imperative as the search space grows with number of users and number of transmit antennas in the MU MIMO system This can be treated as an optimization problem of maximizing the achievable system sum-rate In this paper, it has been demonstrated that combined user and antenna scheduling (CUAS) with binary genetic algorithm (BGA) adopting elitism and adaptive mutation (AM) achieves about 97-99% of system sum-rate obtained by ESA (DPC) with significantly reduced computational and time complexity It has been shown that BGA is able to find the globally optimum solution for MU MIMO systems well within the time interval of modern wireless packet data communications However, it is interesting to observe that BGA is able to find a solution to CUAS close to the optimum value quite rapidly In this paper, it is also shown that BGA with elitism and AM achieves higher throughput than limited feedback scheduling schemes as well

Bounds and Capacity Theorems for Cognitive Interference Channels With State

Abstract: A class of cognitive interference channels with state are investigated, in which a primary transmitter sends a message to two receivers (receivers 1 and 2) with assistance of a cognitive transmitter (that knows the primary transmitter’s message), and the cognitive transmitter also sends a separate message to receiver 2. The channel is corrupted by an independent and identically distributed (i.i.d.) state sequence. The scenario, in which the state sequence is noncausally known at both the cognitive transmitter and receiver 2, is first studied. The capacity region is obtained for both the discrete memoryless and Gaussian channels. The second scenario, in which the state sequence is noncausally known only at the cognitive transmitter, is further studied. Inner and outer bounds on the capacity region are obtained for the discrete memoryless channel and its degraded version. The capacity region is characterized for the degraded semideterministic channel and for channels that satisfy a less noisy condition. The Gaussian channels are further studied, which are partitioned into two cases based on how the interference compares with the signal at receiver 1. For each case, inner and outer bounds on the capacity region are derived, and partial boundaries of the capacity region are characterized. The full capacity region is also characterized for channels that satisfy certain conditions. It is shown that certain Gaussian channels achieve the capacity of the same channels with state noncausally known at both the cognitive transmitter and receiver 2.

On the Dispersions of the Gel’fand–Pinsker Channel and Dirty Paper Coding

Abstract: This paper studies the 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 empirical distribution of the state sequence. For error probabilities less than 0.5, it is shown that the second-order rate improves on an existing one based on independent and identically distributed random coding. In the Gaussian case (dirty paper coding) with an almost-sure power constraint, an achievability result is obtained 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.

Sum Rate Maximizing in a Multi-User MIMO System with SWIPT

Abstract: -This paper studies the simultaneous wireless infor- mation and power transfer (SWIPT) in a multiuser broadcast (BC) multiple-input multiple-output (MIMO) system, in which a base station sends messages to several information decoding (ID) users, and transmits wireless power to multiple energy harvesting (EH) user at the same time. We aim to maximize the sum-rate of the ID users while maintaining a minimum EH constraint for each EH user. Firstly, an optimal rate-energy (R-E) boundary is characterized by using a BC-multiple access channel (MAC) duality derived from dirty paper coding (DPC). Since the complexity of the DPC is quite high due to continuously encoding and decoding at the transceivers, we then propose a sub- optimal algorithm using a weighted minimum mean square error (WMMSE) approach, which has lower complexity and iteratively converges a local optimal point. Finally, the performance com- parisons and convergence properties are illustrated by simulation results

Han–Kobayashi and Dirty-Paper Coding for Superchannel Optical Communications

Abstract: Superchannel transmission is a candidate to realize Tb/s-class high-speed optical communications. In order to achieve higher spectrum efficiency, the channel spacing shall be as narrow as possible. However, densely allocated channels can cause non-negligible inter-channel interference (ICI) especially when the channel spacing is close to or below the Nyquist bandwidth. In this paper, we consider joint decoding to cancel the ICI in dense superchannel transmission. To further improve the spectrum efficiency, we propose the use of Han–Kobayashi superposition coding. In addition, for the case when neighboring subchannel transmitters can share data, we introduce dirty-paper coding for pre-cancelation of the ICI. We analytically evaluate the potential gains of these methods when ICI is present for sub-Nyquist channel spacing.

On Vector Perturbation Precoding for the MIMO Gaussian Broadcast Channel

Abstract: Precoding schemes in the framework of vector perturbation (VP) for the multiple-input multiple-output (MIMO) Gaussian broadcast channel (GBC) are investigated. The VP scheme, originally a “one-shot” technique, is generalized to encompass processing over multiple time instances. Using lattice-based extended alphabets (“perturbations”), and considering the infinite time-span extension limit, a lower bound on the achievable sum-rate using the generalized VP scheme is analytically obtained. The lower bound is shown to asymptotically achieve the optimum sum-rate in the high signal-to-noise ratio (SNR) regime (both in terms of degrees-of-freedom and power offset), for any number of users and transmit antennas. For the two-user cases, it is shown that the lower bound coincides with the sum-capacity for low SNR. The above lower bound is constructively obtained by means of an efficient practically oriented suboptimal transmit energy minimization algorithm, which exhibits a polynomial complexity in the number of users. The proposed precoding scheme demonstrates that the “shaping gain” is achievable for VP schemes, when employing “good” multidimensional lattices. It is also shown that the suboptimum algorithm has its merits, even when processing over multiple time instances is not employed. For the $2\times 2$ MIMO GBC, the VP scheme is generalized further, and an inner bound for the entire achievable rate region is obtained, by which an interesting correspondence is identified with the ultimate capacity region, as obtained by “dirty paper coding”.

State-Dependent Parallel Gaussian Networks With a Common State-Cognitive Helper

Abstract: State-dependent parallel networks with a common state-cognitive helper is studied, in which $K$ transmitters wish to send $K$ messages to their corresponding receivers over $K$ state-corrupted parallel channels, and a helper who knows the state information noncausally wishes to assist these receivers to cancel state interference. Furthermore, the helper also has its own message to be sent simultaneously to its corresponding receiver. Since the state information is known only to the helper, but not to other transmitters, transmitter-side state cognition and receiver-side state interference are mismatched. Our focus is on the high state power regime, i.e., the state power goes to infinity. Three (sub)models are studied. Model I serves as a basic model, which consists of only one transmitter–receiver (with state corruption) pair in addition to a helper that assists the receiver to cancel state in addition to transmitting its own message. Model II consists of two transmitter–receiver pairs in addition to a helper, and only one receiver is interfered by a state sequence. Model III generalizes model I to include multiple transmitter–receiver pairs with each receiver corrupted by independent state. For all models, the inner and outer bounds on the capacity region are derived, and comparison of the two bounds yields characterization of either full or partial boundary of the capacity region under various channel parameters.

Gaussian State Amplification with Noisy Observations

Abstract: We consider the problem of channel state amplification in a Gaussian channel with additive Gaussian channel states, where the encoder observes noncausally a noisy version of these states. A complete characterization is provided for the minimum reconstruction distortion under a transmitter power constraint, and it is shown that a simple analog scheme with power control is optimal. More precisely, if the power available to the encoder is below certain threshold, the analog scheme using full power is optimal, however, when the power available to the encoder is above that threshold, analog transmission using only a fixed amount of the available power is optimal. Furthermore, the problem of simultaneous message transmission and Gaussian state amplification with noisy observations is studied, for which an inner bound and two nontrivial outer bounds to the optimal tradeoff between the transmission rate and the state reconstruction distortion 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. The first outer bound is obtained by extending the channel decomposition technique, while the second outer bound requires a strategic analysis of the covariance matrix of the relevant random variables.

Opportunistic interference management: a new approach for multiantenna downlink cellular networks

Abstract: A new approach for multiantenna broadcast channels in cellular networks based on multiuser diversity concept is introduced. The technique called opportunistic interference management achieves dirty paper coding capacity asymptotically with minimum feedback required. When there are K antennas at the base station with M mobile users in the cell, the proposed technique only requires K integer numbers related to channel state information between mobile users and base station. The encoding and decoding complexity of this scheme is the same as that of point-to-point communications, which makes the implementation of this technique easy. An antenna selection scheme is proposed at the base station to reduce the minimum required mobile users significantly at the expense of reasonable increase in feedback. In order to guarantee fairness, a new algorithm is presented that incorporates opportunistic interference management into existing Global System for Mobile communications GSM standard. Copyright © 2014 John Wiley & Sons, Ltd.

Spectrum sharing on interference channels with a cognitive relay

Abstract: In this paper, an interference channel with a cognitive relay (IFC-CR) is considered to achieve spectrum sharing between a licensed primary user and an unlicensed secondary user. The CR assists both users in relaying their messages to the respective receivers, under the constraint that the performance of the legacy primary user is not degraded. Without requiring any non-causal knowledge, the CR uses a successive interference cancellation to first decode the primary and secondary messages after a transmission phase. A power allocation is then performed to forward a linear weighted combination of the processed signals in the relaying phase. Closed-form expressions of the end-to-end outage probability are derived for both primary and secondary users under the proposed approach. Furthermore, by exploiting the decoded primary and secondary messages in the first phase, we propose the use of dirty paper coding (DPC) at CR to pre-cancel the interference seen at the secondary (or primary) receiver in the second phase, which results in a performance upper bound for the secondary (or primary) user without affecting the other user. Simulation results demonstrate that with a joint consideration of the power control at the secondary transmitter and the power allocation at CR, performance gains can be achieved for both primary and secondary users.

Efficient beamforming method for downlink MU-MIMO broadcast channels

Abstract: The sum rate maximization in multiuser MIMO broadcast channels is investigated in this paper. Due to the high computational complexity of non-linear dirty paper coding (DPC), zero-forcing dirty paper coding (ZF-DPC) is proposed as an alternative suboptimal approach. However, traditional ZF-DPC method requires that the number of total receive antennas is less than or equal to the number of transmit antennas. In this paper, we consider the scenario where the sum number of receive antennas may be more than the number of transmit antennas. It is shown that the optimal data stream allocation needs exhaustive search over all possibilities, and the complexity is significantly high. We propose a greedy transmit data allocation scheme that allocates one data stream at each step, the corresponding transmit beamforming vector and receive combining vector are designed to avoid interfering with the previous allocated data streams, and the pre-equalization Tomlinson–Harashima Precoder (THP) technique is adopted to pre-cancel the non-causally known interference caused by the previous allocated data streams. The proposed method is computationally efficient thanks to the low complexity. Simulation results show that this novel method outperforms the methods in the literature.

Cognitive interference channel: achievable rate region and power allocation

Abstract: In this study, the authors consider a state-dependent two user interference channel. The two users sharing the spectrum are assumed to be cognitive and each user has a non-causal access to the signal from the other user. For this channel model, an achievable rate region is established for both discrete memoryless model and Gaussian channel. In particular, the achievable rate region is obtained by combining Han–Kobayashi rate splitting coding scheme, superposition coding, Gelfand–Pinsker coding scheme and zero-forcing dirty paper coding. Furthermore, the sum rate maximisation and the associated power allocation problem are studied, numerically and theoretically. The corresponding numerical examples show that the proposed combined coding scheme outperforms the existing schemes in the sense of achievable rate region. Moreover, the effectiveness of the optimal power allocation between the two cognitive nodes is also shown.

Performance Analysis of Linear and Nonlinear Precoding in MIMO Systems

Abstract: A MIMO system which is used to achieve high data rate and capacity in transmission medium is one of the significant emerging technologies today. The interferences occurring between the different antenna elements in MIMO OFDM can be mitigated to improve the performance of the system. The precoding technique, where the data is coded and transmitted to reduce the bit error rate can be used for this. There are linear precoding and nonlinear precoding methods are there.Linear precoding schemes have low complexity and can achieve a reasonable capacity. The nonlinear precoding can access more capacity with much receiver complexity. In this paper, the BER performance of different precoding schemes like Channel Inversion, Block Diagonalization, DPC and TH precoding are analysed to get a better performance for the MIMO systems. Simulation results shows that the nonlinear precoding technique Dirty Paper Coding (DPC) achieves better performance than all other precoding methods.

Z-interference channel with side information at the transmitters

Abstract: In this paper, channel coding strategies for the problem of communication over a two-user Z-interference channel (ZIC) in the presence of non-causal side information (NSI) at transmitters are presented. First, an achievable rate region for the general discrete memoryless ZIC-NSI is derived using rate splitting technique, superposition coding, Gel’fand–Pinsker-type binning scheme and joint typicality decoding. Next, the capacity region of a special case of the orthogonal ZIC-NSI is characterized. Then, the Gaussian version of the channel called the Gaussian Doubly Dirty ZIC (GDD-ZIC) is defined and a general outer bound to the capacity region of the GDD-ZIC is presented. After that, an inner bound for the sum-capacity of the channel using Costa's dirty paper coding is derived and thereby it is shown that Costa's strategy cannot achieve any positive rates over the GDD-ZIC for the case of strong state-interference. Finally, lattice-based achievable rates for the GDD-ZIC are obtained. These lattice-based rates are independent of the state-interference powers and thus, lattice-strategies are able to achieve positive rates for the case of strong state-interference. Moreover, it is shown that lattice-strategies are optimal for a class of the GDD-ZIC.

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.

Precoder design for distributed antenna systems (DAS) with limited channel state information

Abstract: A distributed antenna system (DAS) consists of multiple baseband units (BBUs) connecting to distributed antennas (DAs) via dedicated access links In this study, we investigate a DAS with limited channel state information (CSI) and consider an average rate of users as an objective, where the expectation is taken over the channel uncertainty We propose two distributed precoder designs that are based on a rate lower bound and a rate upper bound, respectively As a benchmark, coordinated precoder and cooperative dirty paper coding (DPC)-based precoder with full CSI are compared with our proposed algorithms Numerical results verifies that the rate performance of our upper-bound based scheme with limited CSI approaches tightly the maximum rates of the full CSI schemes, while that of lower-bound based scheme is relatively worse

Performance of cloud radio networks with clustering

Abstract: Cloud radio networks employ coordinated transmission among base stations (BSs) to reduce the interference effects The practical limitations in implementing coordination results in suboptimal systems with limited performance In this paper, we analyze the performance of a cloud network with clustering, where geographically close BSs form a clustered cloud Coverage probability and rate distributions are analyzed using stochastic geometric models Specifically, we develop approximations for the coverage probability of a typical user in a clustered cloud network with zero-forcing dirty paper coding The adverse effect of finite clusters on the achievable rate is quantified

On MMSE properties of “good” and “bad” codes for the Gaussian broadcast channel

Abstract: This work examines the properties of code sequences for the scalar Gaussian broadcast channel (BC). Specifically, the behavior in terms of the mutual information and minimum mean-square error (MMSE) functions for all signal-to-noise ratios (SNRs) is explored. It is shown that “good”, capacity achieving, code sequences must follow the behavior of a capacity achieving superposition code sequence, even if they use a different encoding-decoding scheme (such as “Dirty Paper Coding”). Necessary and sufficient conditions for reliable decoding in general and specifically for “good” code sequences for the scalar Gaussian BC, in terms of the MMSE and conditional MMSE functions, are derived. Finally, “bad” code sequences, that do not obtain the capacity of the scalar Gaussian BC, are examined. These codes are defined by an additional MMSE constraint at some other SNR. This constraint limits the amount of disturbance these codes may have on some unintended receiver at that SNR. The capacity region, given this constraint, is fully depicted.

Sum-rate analysis of two-way multi-relay multi-user MIMO networks with two-hop precoding

Abstract: In this paper, we study a joint source and relay pre-coding technique for multiuser multi-relay that help to maximize sum rate (SR) for Multiple-Input Multiple-Output (MIMO) link. Here we proposed two-hop precoding technique by implementing Zero-Forcing (ZF) as source precoder and Dirty Paper Coding (DPC) as relay precoder. We show performance by simulating and show that ZF-DPC (i.e., ZF at source and DPC at relay) technique help us to improve sum-rate than using ZF-ZF (i.e., ZF precoder at source and relay).

On the capacity of cognitive interference channel structures.

Abstract: The cognitive interference channel extends the classical two-user interference channel to have unidirectional cooperation at the transmitters. In this model, the cognitive transmitter is assumed to have noncausal knowledge of the other transmitter's current message (primary message). This a priori knowledge is used by the cognitive user to accomplish its two main purposes, i.e., to relay the primary message in order to boost the primary user's data rate and to maximise its own data rate by cancelling the interference at its receiver. The cognitive interference channel is well studied in the literature and capacity results are available for the weak and very strong interference regimes, amongst others. A general solution is still elusive. In this thesis we study the capacity region of cognitive structures that are based in their core on the cognitive interference channel but with the aggregate that an additional node is considered, e.g., an additional receiver node, an additional transmitter node or a relay node. The cognitive broadcast interference channel consists of the cognitive interference channel with an additional receiver. The cognitive side serves either one or two receivers and the interference goes from the cognitive transmitter to the primary receiver only. In this model we provide a general achievable rate region when the cognitive side serves two receivers. We analyse the discrete memoryless channel and show that the region simplifies to existing results in the literature when certain assumptions are made. An achievable rate region for the Gaussian channel is also provided for the case where the cognitive side sends common information to both receivers. When the cognitive side serves only one receiver, we provide an achievable rate region and an outer bound and show the gap graphically. The cognitive interference channel with a relay consists of the cognitive interference channel with an additional relay node. In this model we show that as in the interference channel with a relay, interference forwarding is also beneficial. We describe analytically achievable rate regions and show the benefits of interference forwarding. We also provide an achievable rate region with generalised interference forwarding, i.e., the relay forwards the intended message and the interference simultaneously, and show that allowing the relay to allocate part of its power to forward interference is beneficial when we are in the strong but not in the very strong interference regime. The cognitive interference channel with causal unidirectional destination cooperation is formed by transferring the relaying capabilities of the relay node in the previous model to the cognitive receiver and its operation is causal rather than strictly causal. In this model we show that instantaneous amplify and forward is good enough to achieve the capacity region of the Gaussian channel. We derive analytically an inner and outer bounds and show that they coincide for certain values of the antenna gain at the relay in the very strong interference regime. We also analyse the cognitive interference channel with a relay for the case where the relay operates causally. The capacity region is obtained for a special case of very strong interference. The cognitive multiple access interference channel consists of the cognitive interference channel with an additional cognitive transmitter. In this model the interference goes from the primary user to the cognitive receiver only. The cognitive users form a MAC channel. We show for this scenario that dirty paper coding achieves the capacity region in the Gaussian case. In the analysis we make use of encoding techniques first utilised for the MAC with state available noncausally at the encoder.

Energy efficiency optimization with non-linear precoding in multi-cell MISO broadcast channels

Abstract: In this paper, we focus on maximizing weighted sum energy efficiency (EE) for a multi-cell multi-user channel. In order to solve this non-convex problem, we first decompose the original problem into a sequence of parallel subproblems which can be optimized separately. For each subproblem, a base station employs dirty paper coding to maximize the EE for users within the cell while regulating interference induced to other cells. Since each subproblem can be transformed to a convex multiple-access channel problem, the proposed method provide a closed-form power allocation. Then, based on the optimal covariance matrix, a locally optimal solution is obtained to maximize the sum EE. Finally, simulation results show that our algorithm based on the non-linear precoding achieves close to 20 percent gain than the conventional linear precoding method.

State-dependent Gaussian Z-interference channel: Capacity results

Abstract: A type of state-dependent Gaussian Z-interference channels is studied, in which transmitters 1 and 2 wish to send two messages to receivers 1 and 2, and only receiver 1 is interfered by transmitter 2's signal. Both receivers are corrupted by the same but differently scaled state sequence. The state information is assumed to be known noncausally at both transmitters. The channel is partitioned into very strong, strong, and weak interference regimes based on the strength of the interference. Respectively for the very strong and strong regimes, the capacity region and points on the capacity region boundary are characterized under certain channel parameters by designing joint dirty paper coding between two transmitters to cancel the state at both receivers. For the weak interference regime, the sum capacity is characterized by independent dirty paper coding at two transmitters. Comparison between the state-dependent regular and Z-interference channels indicates that although with one interference-free link, Z-interference channel does not necessarily perform better, because the dirty paper coded interference can be useful to help to fully cancel the state via joint dirty paper coding between the transmitters.

Improved signal detection for multiuser MIMO system using BD QR-LRL

Abstract: QR-Least reliable layer (QR-LRL) technique in fusion with the channel block diagonalization (BD) is proposed for signal detection in the multiuser multiple input and multiple output (MU-MIMO) system. Literature survey shows various precoding techniques like BD-ZF, BD-MMSE, dirty paper coding (DPC) to overcome multiuser interference. However, they suffer in the terms of either noise enhancement or complexity or sum rate capacity. It is also shown in the literature that QR-LRL, an ordered successive interference cancellation (OSIC) detector achieves hard/soft ML performance with low complexity for SM-MIMO systems. In this paper, BD and QR-LRL are associated together in order to enhance the signal detection for MU-MIMO system. Simulation results showed that the proposed technique confirms improved detection compared to the conventional methods for multiuser scenario.

Duality analysis and improving the capacity of multi-input multi-output channel using dirty paper coding technique

Abstract: In wireless communication, Multi-Input Multi-Output (MIMO) technology offers significant increase in data throughput and link range without additional bandwidth. The dirty paper coding (DPC) achieves the sum rate capacity of Gaussian MIMO broadcast channel. The dirty paper coding is a technique for efficient transmission of digital data through a channel that is subject to some interference that is known to the transmitter. This technique consists of precoding the data so as to cancel the effect of interference. The duality relationship between BC and MAC channel has been studied and The Sato upper bound and Marton's inner bound on the capacity of Broadcast channel has been considered and applied this capacity to the MAC channel by showing the duality. The use of dirty paper coding closely achieves the sum-rate capacity region of broadcast channel. MIMO is abbreviation of Multiple Input Multiple Output. In MIMO fading environment, the so called degenerating channels or keyholes may exist that exhibit low partial fading correlation at both ends of the link but still have poor rank properties, and hence low ergodic capacity. The performance of dirty-paper coding over MIMO keyhole channels has been analyzed. The capacity and the probability of error of a MIMO system with Binary phase shift keying (BPSK) over keyhole channel. This paper also proves the intuitive result that the capacity under keyhole condition can be improved using Dirty paper coding.