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Bit rate fairness is an important concern in current G.fast and the forthcoming fifth generation DSL systems where the frequency is extended to hundreds of MHz and crosstalk couplings reach unprecedented levels. In this paper, we study the price of fairness (PoF) in dynamic spectrum management (DSM) enabled DSL systems. We propose optimal low complexity PoF-constrained max-min fairness (MMF), weighted max-min fairness (WMMF), proportional fairness (PF), and $(p,\alpha)$ -PF algorithms. The proposed algorithms inherently provide weight factors which can be used to reduce the computational complexity of user encoding or decoding order optimizing algorithms used in nonlinear vectoring. Our simulation results show that although PoF grows exponentially with the minimum bit rate, fairness can be improved considerably with a relatively small price in DSM level 2 spectrum balancing and particularly in DSM level 3 using minimum mean square error (MMSE) generalized decision feedback equalizer (GDFE). It is also seen that the proposed optimal PoF-constrained MMF algorithm can reach the solutions of PF and $(p,\alpha)$ -PF measures for some PoF. That is, the PoF-constrained MMF or WMMF algorithms can be used instead of the non-linear PF and $(p,\alpha)$ -PF measures, which often result in computationally intensive solutions.

Probabilistic constellation shaping (PCS) has attracted a lot of attention for increasing the spectral efficiency (SE) in coherent fiber optic communication. Unfortunately, increasing the transmit power could increase non-linear self- and cross-phase modulations due to the Kerr effect in fiber optic. Owing to smaller peak-to-average power ratio (PAPR), higher angular distance between constellation points, and lower amplitude levels, amplitude and phase shift keying (APSK) can be more robust to phase noise than quadrature amplitude modulation (QAM). A new PCS scheme is proposed for the standard APSK 16 and 64 DVB-S2/S2X modulation formats. Simulation results in additive white gaussian noise (AWGN) channels show a close bit error rate performance for the proposed system compared to probabilistically-shaped QAM.

A well-known property of the Z transform is the differentiation in z-domain property, which states that if X(z) ≡ Z{x[n]} is the Z transform of a sequence x[n] then the Z transform of the sequence nx[n] is Z{nx[n]}=−z(dX (z)/dz). It is generally believed that the regions of convergence (ROC) for the two Z transforms are the same. It is shown that this is not true in the general case where X(z) is not rational and an example, in which the ROC is different for X(z) and Z{nx[n]}, is given.

Interference alignment (IA) is an effective scheme for counteracting multi-user interference in wireless networks. Unfortunately, IA is sensitive to channel-state-information (CSI) imperfections. Achieving perfect CSI knowledge at a central node in large scale antenna wireless networks implies a huge feedback which is prohibitive. In this paper, we assume a distributed multicellular scenario, where there is no central node that knows global CSI and optimizing IA’s precoder and combiner matrices is done by exchanging the local channel information between users and base stations (BSs) in several iterations. By using low-rank matrix approximation theory, we propose an efficient method to iteratively optimize precoder and combiner matrices for distributed IA. In each iteration, only a part of the CSI is fed back to BSs. More precisely, based on the latest available CSI and certain performance criteria, a few columns of the effective channel are sent back to the transmitters to approximate the interference covariance matrix which is then used to update the precoder matrices. We also propose a new method for quantizing the channel information matrix non-uniformly, which improves upon the conventional channel feedback quantization techniques. We evaluate the proposed methods by simulating a cellular network with various number of BS antennas and different feedback channel capacities. Simulation results show that our methods outperform both the conventional and improved channel feedback quantization algorithms significantly.

There are two types of crosstalk in digital subscriber line (DSL) systems, namely near-end crosstalk (NEXT) and far-end crosstalk (FEXT). NEXT is usually much stronger than FEXT. Therefore, high-speed DSL systems transmit in preplanned disjoint downstream (DS) and upstream (US) frequency bands to avoid NEXT. Although easy for implementation, such a fixed bandplan can lead to inefficient bandwidth usage, depending on the DS and US bit rate requirements and the loop topology, particularly in so-called vectored DSL systems, which include signal coordination for FEXT cancellation. In dynamic bandplanning (DBP), each frequency band is allocated to either DS, US, or to both directions depending on the aforementioned parameters. In this paper, we consider optimal DBP for vectored DSL with linear as well as with nonlinear transmitter/receiver structures. We propose an optimal DBP algorithm for systems with disjoint DS and US bands. For systems with overlapping bands, the problem of finding the optimal transmitter/receiver filters is nonconvex and we propose two iterative algorithms based on recent optimum spectrum balancing schemes from the literature. We also study the effect of echo and US NEXT cancellation on the system performance. Finally, simulation results are provided to demonstrate that our algorithms can indeed significantly increase the achievable bit rates.

In this letter, we derive formulas for optimal discrete-time pulse shaping for communications in multiband channels. Furthermore, we propose a technique for extending a short signal segment for the purpose of power spectral estimation using the available information about the signal stopbands. The later technique can be also used for minimizing the energy leakage into stopbands of a signal, e.g., as in windowing for orthogonal frequency division modulation (OFDM). Simulation results show that when the pulse duration is long enough, the stopband energy can be practically reduced to zero using the proposed technique. The proposed power spectral estimation technique can improve the resolution and reduce the energy leakage from signal passbands into adjacent stopbands. Moreover, it can reduce the out-of-band power leakage significantly when used for windowing in OFDM.

Characterizing the satellite beam footprint boundary can be used to measure the overlap of the beam coverage area of a satellite with that of other communication systems. A crucial application of this is in emerging cognitive satellite communication systems. In this paper, an analytical model based on ray tracing is proposed for specifying the boundary and the size of the satellite beam footprint and the distance of the footprint center from the beam center on Earth's surface. These characteristics are primarily a function of four parameters, namely, the coordinates of satellite, the beam cross-sectional shape, the coordinates of beam center, and the beamwidth. These parameters are reduced to only two parameters of Earth central angle between the nadir and the beam center and the beamwidth. Numerical results show that by increasing any of the two parameters the asymmetry of the footprint, its size, and the distance between the footprint center and the beam center increase.

One of the main impairments for advanced digital subscriber line (DSL) systems is crosstalk. Crosstalk can be effectively cancelled using vectoring. However, some challenges such as implementation and computational complexities associated with full users' coordination when the number of DSL lines is large or when they are not co-located at any end make full vectoring impractical in many scenarios. In this paper, we consider interference alignment (IA) as an alternative technique when full vectoring is not practical. We apply this technique to both non-coordinated and partially coordinated very fast digital subscriber line 2 (VDSL2) systems. The computational complexity of IA can be prohibitive, however, we reduce it by applying IA to subsets of tones resulting in a computational complexity much smaller than that of vectoring. We also use iterative IA algorithms for performance improvement. Simulation results show that IA increases the achievable rates of VDSL2 loops considerably without a need for signal coordination among users. Moreover, when IA and partial vectoring are applied together, the users can achieve bit rates moderately close to that of a crosstalk-free network.

In this paper, we investigate joint level 2 and 3 dynamic spectrum management (joint DSM 2/3) for downstream (DS) DSL. We consider a DS scenario in which users are divided into a few separate groups, where vector encoding based signal coordination can be applied in each group and spectrum coordination is possible for all users. This can be seen as a mixed interference/broadcast channel (IF/BC) scenario. In order to obtain the optimal transmitter structure, we develop a generalized duality between the vector broadcast and multiple-access channel (MAC) for scenarios in which partial signal coordination is available among users. This theory together with optimal spectrum balancing (OSB) is exploited to calculate the jointly optimal filters and transmit powers for non-linear vector dirty paper coding structures (in the form of Tomlinson-Harashima precoder (THP)) in the groups. The proposed scheme is compared to several other joint DSM 2/3 algorithms for DS DSL. Simulation results show that the proposed scheme (referred to as the IF/BC-OSB algorithm) achieves considerably higher bit rates than the other schemes. IF/BC-OSB encompasses the earlier developed BC-OSB algorithm as a special case. A simplified version of IF/BC-OSB avoiding exhaustive search with near-optimal performance is also proposed. © 2012 IEEE. ispartof: IEEE Transactions on Communications vol:60 issue:10 pages:3111-3122 status: published

Orthogonal spreading codes play an essential role in code-division multiple-access (CDMA) systems by eliminating multiple-access interference (MAI). In this paper, a novel orthogonal spreading code has been proposed for spectrally-encoded (SE) CDMA, a.k.a., spread-time (ST) CDMA with arbitrary pulse shape. It has been shown that it is possible to retain the orthogonality of the code in the presence of tail truncation by time windowing and in a general multipath fading channel in which users experience different frequency selectivity just by modifying the user codewords. Simulation results show that the proposed codes can achieve single user performance when the code length is twice the number of users.

In this paper, we propose a new approach for signal level estimation in binary phase shift keying (BPSK) modulation based on the empirical characteristic function (ECF), when the probability density function (PDF) of the noise is unknown. Then, we compare our proposed method with two other estimators that are suggested for systems with known noises. Numerical results show that, in the presence of Laplace noise, the ECF estimator has a better performance in low signal-to-noise ratios (SNR) in comparison with previously proposed methods. Moreover, the proposed method does not require the knowledge of noise PDF and works without any training sequence.

A class of generalized optical orthogonal codes (OOCs), namely, frame time-hopping (FTH) patterns with an extremely large cardinality, are studied for implementing multirate and multiservice (MR/MS) optical CDMA (OCDMA) networks. Conventional MR/MS methods, namely variable spreading rate and parallel mapping, are considered. Using FTH patterns, the problem of low OOC code cardinality in conventional MR/MS schemes is removed. Moreover, several new multicode methods, using subcode concatenation scheme, are proposed for MR/MS OCDMA. The proposed multicode schemes present flexibility for supporting MR/MS applications such as lower implementation complexity and cost, less need for service synchronization, and finally lower link power budget. Multiple-access performances of the systems are evaluated using saddle-point approximation methods considering photodetector shot-noise, dark current, and circuit thermal noise. The results show that the conventional parallel mapping outperforms the other schemes in high received powers, and the proposed multicode method, using Walsh subcode along with difference modulation, presents the best performance in low received powers for the cases considered.

An ultra-wide bandwidth time-hopping spread-spectrum code division multiple-access system employing a binary PPM signaling has been introduced by Scholtz (1993), and its performance was obtained based on a Gaussian distribution assumption for the multiple-access interference. In this paper, we begin first by proposing to use a practical low-rate error correcting code in the system without any further required bandwidth expansion. We then present a more precise performance analysis of the system for both coded and uncoded schemes. Our analysis shows that the Gaussian assumption is not accurate for predicting bit error rates at high data transmission rates for the uncoded scheme. Furthermore, it indicates that the proposed coded scheme outperforms the uncoded scheme significantly, or more importantly, at a given bit error rate, the coding scheme increases the number of users by a factor which is logarithmic in the number of pulses used in time-hopping spread-spectrum systems.

Previous works in spectrum leasing for centralized cognitive radio networks (CRNs) are based on selecting a secondary user as a relay to cooperatively transmit the primary data and then leasing the released spectrum due to the cooperation to the selected user. In this paper, we propose a new spectrum leasing scheme to improve the throughput and thus the spectrum efficiency of the secondary system. The proposed approach selects two secondary users for cooperation and secondary transmission independently, which are the best users towards the primary and secondary systems, respectively. We show that the outage performance of the secondary system is enhanced as a result of the independent secondary user selection. Analytical and simulation results are presented to verify the efficiency of our approach and performance improvement in the secondary system.

The interference issues related to ultrawideband (UWB) radio pose tight restrictions on the maximum data rate of UWB radio telecommunication systems. A possible solution is to reduce the required signal to interference ratio (SIR) that gives satisfactory performance to the UWB system. In this letter, we propose coded M-ary UWB radio communication systems. Two classes of convolutional codes, namely, low-rate superorthogonal codes and high-rate punctured codes are considered for this purpose. Simulation results on the bit error rate of the proposed system indicates that the system is capable to work in lower SIR's and therefore supports higher data transmission rates in a real interference environment compared to the previously proposed UWB communication systems.

In this paper, we consider optimal dynamic spectrum management (DSM) for a downstream (DS) DSL scenario in which users are divided into a few separate groups, where vector encoding based signal coordination can be applied in each group and spectrum coordination is possible for all users. This can be seen as a mixed interference/broadcast channel (IF/BC) scenario. We investigate several candidates for vector encoding the signals inside the groups, including the linear zero-forcing (ZF) pre-compensator, ZF Tomlinson-Harashima pre-coder (THP), optimal linear pre-compensator (OLP), and THP with optimal transmit filters. The calculation of the optimal transmit filters (for both the linear pre-compensator and THP) is a non-convex problem. To resolve this problem, we develop a generalized duality between the IF/BC and IF/multiple-access channel (MAC). In order to achieve the highest data rates, optimal spectrum balancing (OSB) is applied to all users on top of the vector encoding inside the groups. Simulation results show that the grouped THP with optimal transmit filters achieves considerably higher bit rates than the other schemes. The resulting algorithm is referred to as the IF/BC-OSB algorithm, and encompasses the OSB (i.e., IF-OSB) and the earlier developed BC-OSB algorithm as special cases.

Lagrange dual optimization technique (LDO) is a powerful tool for solving constrained optimization problems in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing systems (OFDM) and is generally considered to be optimal in the literature. LDO relaxes a constrained problem into an unconstrained dual problem using Lagrange multipliers. To solve the dual problem, the optimal value of the Lagrange multipliers should be found. The Lagrange multipliers are usually determined in an iterative process and reducing the number of iterations is of crucial importance to obtain systems with manageable computational complexity. In this paper, we show that for the LDO to be optimal in optimal spectrum balancing of DSL, the joint rate and power region (JRPR) should be strictly convex. Moreover, we propose a new LDO based algorithm with two basic advantages. Firstly, the computational complexity of the algorithm is logarithmic in the desired precision. Secondly, the algorithm can be used to find the optimal solution even for the cases with non-strictly convex JRPR. Our results can potentially be generalized to a wider range of optimization problems in the context of MIMO-OFDM and other complex separable systems.