Patent Description:
In the prior art, precoding and beamforming techniques are limited by the accuracy of Channel State Information (CSI) information available at the gateway. Additionally, precoding techniques are also limited by the lack of feeder-link bandwidth. Compensating for CCI at a receiver, for example, a user terminal, overcomes the above limitations.

A multibeam satellite system employs frequency reuse in which different beams share the same frequency resource or bandwidth. Beams sharing bandwidth are known as co-channel beams. The closer the two co-channel beams are located geographically, the greater is the co-channel interference (CCI). CCI can have devastating impact on the performance, hence prior art systems maintain CCI at acceptable levels by typically employing a reuse factor of <NUM>, illustrated in <FIG>, where the total system bandwidth B is divided into two parts on each antenna polarization, such that each beam has bandwidth of B/<NUM>.

<FIG> illustrates a prior art beam laydown pattern with a <NUM>-reuse plan for a multi-beam satellite, according to various embodiments.

<FIG> illustrates a reuse plan combining signal polarization and nonoverlapping frequency spectrums to create a <NUM>-reuse plan <NUM>. In the example, the four colors (hashing in <FIG>) correspond to four different frequency/polarization allocations. An available frequency spectrum is divided into two frequency sub-bands - F1 and F2 - and each sub-band is assigned/mapped to a different color, and two orthogonal polarizations are assigned/mapped colors to provide the two other colors in the <NUM>-color reuse plan. A service or coverage area <NUM> may be divided into cells. Multi-beam satellites typically illuminate multiple hexagonal cells within a service area <NUM>. In exemplary embodiments, a cell <NUM> may be illuminated by a far field beam pattern in band F1 using a right hand circular polarization (RHCP), a cell <NUM> in band F1 may be illuminated by a far field beam pattern in band F1 using a left hand circular polarization (LHCP), a cell <NUM> may be illuminated by a far field beam pattern in F2 using a RHCP and a cell <NUM> which may be illuminated by a far field beam pattern in F2 using a LHCP A multi-beam satellite implementing a reuse plan may arrange the two polarizations in separate alternate rows, for example, a LHCP row <NUM> and a RHCP row <NUM>. It is possible to tessellate a desired coverage area, such as, earth's surface, using an Nc color reuse tessellate where Nc is any positive natural number. A one-color and two-color is also known. Moreover, a <NUM> or <NUM>-color reuse plan, each of which use both polarizations, is also known.

The very high capacity required by the next generation of broadband satellites makes it necessary to adopt more aggressive reuse factors such as reuse <NUM> and reuse <NUM> in which each beam can make use of the entire bandwidth B. Under such deployments, users at the edge of the co-channel cells experience severe CCI which adversely affects their data rate and quality of service.

The CCI mitigation techniques applied at the satellite gateway such as precoding and beamforming are well known. The effectiveness of precoding and beamforming depends on the accuracy of the Channel State Information (CSI) (for example, magnitude, phase, and delay) available at the gateway. CSI depends on effective estimation and frequent reporting from user terminals to the gateway. Furthermore, transmitter-based techniques used, for example, at the gateway, are also limited by the feeder-link bandwidth since effective precoding requires that signals transmitted to co-frequency beams come from the same gateway.

The multiuser detection framework of prior art receivers assumes that CCI is memoryless, namely, that the current receive filter sampled output depends only on the current symbol from CCI. However, memory effects in CCI are inevitable since the desired signal and interfering signals arrive asynchronously at the user terminal. Even though the co-channel beams may be formed and emitted by the satellite simultaneously, they propagate through different paths causing unavoidable differential delays. Further, the beams could be conveying signals originating from multiple gateways, interconnected via terrestrial links. Other sources that generate memory effects include different symbol rates required by co-channel beams and/or using pulse shaping with different rolloff values. Prior art receivers based on optimal realizations handle memory effects with a complexity that is exponential with the number of interferers and the memory span of each CCI source, making such a receiver severely unaffordable. Other receivers suffer from <NUM> dB of degradation with only moderate timing offset of <NUM>% of the symbol period. Additionally, the memory effects can be made worse due to different symbol rates and/or different roll-off factors employed by the different co-channel beams. These critical limitations motivate the development of low-complexity, innovative solutions that can compensate for CCI with memory at the user terminal and are described in detail in this disclosure. <CIT> relates to methods and apparatus for low complexity soft-in soft-out detection that divide a plurality of received symbols into a plurality of groups of symbols and performs preprocessing on the symbols in each group to suppress interference from other groups. The preprocessing may utilize a priori information for one or more symbols in one or more groups that are not yet detected, and/or a posteriori information for one or more symbols in one or more groups that are already detected and/or decoded. The preprocessed symbols may then be detected using a soft-in soft-out detection algorithm.

This Summary is provided to introduce a selection of concepts in a simplified form that is further described below in the Detailed Description.

In the present teachings, receiver based CCI mitigation alleviates the need for frequent reporting of CSI by the user terminal to the different gateways. Additionally, the receiver-based mitigation overcomes feeder-link bandwidth limitation since it does not require the interfering signals being processed at the user terminal to be generated by the same gateway.

The present teachings disclose several signal processing innovations absent in the prior art multiuser detection techniques. An innovation is the ability to mitigate memory effects in CCI at a user terminal receiver, having a modular structure, without an exponential increase in the receiver complexity. The receiver mitigates interference terms with computational power commensurate with the intensity level of interference experienced at the user terminal. Extensive performance evaluation of the receiver using state-of-the art MODCODs selected from the DVB-S2X standard demonstrates effectiveness under severe CCI with memory. The performance associated with the receiver is near capacity approaching the limits predicted by information theory.

A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One or more computer programs can be configured to perform operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions. A communications apparatus according to the invention is set forth in claim <NUM>.

Implementations may include one or more of the following features. The communications apparatus where the detector of each of the N frameworks transforms the APP to a First Log-Likelihood Ratios (LLRs) using a bit-to-symbol mapping rule, and each of N frameworks further may include a deinterleaver to deinterleave the first LLRs into a decoder input, a Forward Error Correcting (FEC) decoder to decode the decoder input and to generate a second LLRs from a decoded decoder input, and an interleaver to interleave the second LLRs, where the second LLR are treated as a priori probabilities for a respective N framework after the interleaver of the respective N framework, and the second LLRs of each of the N frameworks represent either the desired symbols or the interferer symbols.

In some embodiments, the desired signal is more robust than each of the interferer signals, and the second LLRs from the FEC decoder of a first framework of the N frameworks represent the desired symbols. In some embodiments, at least one of the interferer signals is more robust than the desired signal, and the second LLRs from the FEC decoder of a framework other than a first framework of the N frameworks represent the desired symbols. In some embodiments, the desired symbols are recovered by Simultaneous Decoding (SD) or by Simultaneous Non-Unique Decoding (SND). In some embodiments, the communications apparatus is disposed in an SISO Iterative Divide and Conquer (IDAC) receiver and the detector is a SISO DAC detector.

In some embodiments, an output <MAT> where ai,nd [k] is partitioned into three groups, <MAT>, and <MAT> represents spatial and temporal CCI channel coefficients corresponding to the NF group, the SC group and the OB group, respectively. In some embodiments, the detector is mathematically expressed as <MAT> where pDAC(·) is <MAT> a likelihood function associated with observing x[k], P(·) is the a priori probabilities corresponding to the second LLRs representing the desired symbols, <MAT>, and <MAT>. In some embodiments, a count of the N frameworks is selected from one (<NUM>), two (<NUM>) or three (<NUM>). In some embodiments, the desired signal and the interferer signals may include DVB-S2X standard compliant signals. Implementations of the described techniques may include hardware, a method or process, or computer software on a computer-accessible medium.

A computer-implemented method according to the invention is set forth in claim <NUM>.

Additional features will be set forth in the description that follows, and in part will be apparent from the description, or may be learned by practice of what is described.

In order to describe the manner in which the above-recited and other advantages and features may be obtained, a more particular description is provided below and will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments and are not, therefore, to be limiting of its scope, implementations will be described and explained with additional specificity and detail with the accompanying drawings.

The present teachings may be a system, a method, and/or a computer program product at any possible technical detail level of integration.

Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as SMALLTALK, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages.

Reference in the specification to "one embodiment" or "an embodiment" of the present invention, as well as other variations thereof, means that a feature, structure, characteristic, and so forth described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrase "in one embodiment" or "in an embodiment", as well any other variations, appearing in various places throughout the specification are not necessarily all referring to the same embodiment.

The ever-increasing demand for higher throughput and ubiquitous connectivity implies extracting higher spectral efficiencies and improved energy efficiencies from modern satellite broadband systems. Spectrum scarcity imposes fundamental limitations on the data rates and necessitates the most efficient use of available frequency resources.

In the prior art, precoding and beamforming techniques are limited by the accuracy of Channel State Information (CSI) available at the gateway. Additionally, precoding techniques are also limited by the lack of feeder-link bandwidth. Compensating for CCI at a receiver, for example, a user terminal, overcomes the above limitations. In the present teachings, a user terminal mitigates CCI in a multiuser detection framework by jointly processing a desired signal together with a dominant source. In some embodiments, the dominant source can comprise one, two or more interferers.

Extensive computer simulations, along with accompanying information-theoretic results, demonstrate the superlative performance of the present teachings when tackling severe cases of CCI in multibeam satellite systems employing aggressive frequency reuse, even without imposing the restrictive requirement of synchronous reception.

<FIG> illustrates two users serviced by two co-channel beams showing CCI between beams according to various embodiments.

<FIG> illustrates a satellite communications system <NUM> including a user terminal (UT) <NUM> communicating with a satellite <NUM> via a beam <NUM>. When the UT <NUM> is located near an edge <NUM> or <NUM> of their coverage area <NUM>, a co-channel beam <NUM> (here intended for coverage area <NUM>), in a reuse <NUM> deployment will interfere with the beam <NUM>. In this case, the UT <NUM> will receive its desired/intended signal (beam <NUM>) in the presence of interference arising from interferer signals/co-channel beams <NUM>, <NUM> intended for a UT disposed in the coverage areas <NUM>, <NUM> respectively. The ratio of the beam <NUM> at UT <NUM> (C) to the interfering signal/co-channel beams <NUM>, <NUM> (I) is known as the carrier-to-interference ratio (C/I) and can be as high as <NUM> dB, or of equal strength. In some deployments, one or more of the interferer signals <NUM>, <NUM> may be more robust than the desired signal <NUM>. An interference severity may be based on the C/I ratio.

It is quite likely that the desired signal and the interferer signals can come from different gateways (not shown), employ different coded-modulation (MODCOD) formats, have different symbol rates and pulse shaping filters with different roll-off factors. The desired and interfering signals can arrive at the user terminal in an asynchronous manner. Even though the co-channel beams may be formed and emitted by the satellite simultaneously, they propagate through different paths causing unavoidable differential delays. Further, the beams could be conveying signals originating from multiple gateways, interconnected via terrestrial links. Other sources that generate memory effects include different symbol rates required by co-channel beams and/or using pulse shaping with different rolloff values. CCI mitigation techniques are required to maintain reasonable performance for such users.

Here co-channel beam <NUM> may also be known as a dominant source. When a UT, such as UT <NUM>, is disposed near two edges of its coverage area (i.e., coverage area <NUM>), the UT <NUM> may receive two co-channel beams (second co-channel beam not shown) and portions of both may qualify as dominant sources with respect to the desired signal. For example, a current sample of the co-channel beam may be considered a dominant source, while a previous sample of the co-channel beam may be considered a non-dominant source. In some embodiments, an intended signal of a UT may be interfered with by one or more dominant sources.

The interfering signal/co-channel beams <NUM>, <NUM> may include interfering symbols. Interfering symbols of the beam <NUM> targeting the coverage area <NUM> immediately adjacent to the coverage area <NUM> where the UT <NUM> is disposed may be partitioned into a dominant group of interfering symbols. Interfering symbols of the beam <NUM> targeting the coverage area <NUM> not immediately adjacent to the coverage area <NUM> may be partitioned into a non-dominant group of interfering symbols. Interfering symbols of a beam (not shown) targeting the coverage area <NUM> that is immediately adjacent to the coverage area <NUM> may also be partitioned into the non-dominant group of interfering symbols as the UT <NUM> is not disposed adjacent to a common edge of the coverage areas <NUM>, <NUM>.

<FIG> illustrates a multi-spot beam satellite system model according to various embodiments.

A multi-spot beam satellite system <NUM> is illustrated in <FIG> focuses on a forward link from a satellite gateway to a user terminal. Information bits <NUM> intended for a particular user located in a specific beam n, are FEC-encoded <NUM>, bit-interleaved <NUM> and mapped onto an M-ary complex constellation <NUM> at a gateway <NUM> to form a symbol sequence of length Ns and symbol rate <MAT> such that, {an,i; i = <NUM>, <NUM>,. , Ns -<NUM>}. The uplink signal after pulse shaping has a baseband representation given by
<MAT>
Uplink signals <NUM> intended for the different spot beams are processed by their respective transponders <NUM> and transmitted to intended beams <NUM> by the satellite feed and antenna mechanism <NUM>.

When aggressive frequency reuse factors, such as reuse <NUM> and reuse <NUM> are employed to boost a system's capacity, user terminals, especially those at the beam edge, experience a high level of CCI due to the sharing of common time-frequency resources. In such cases, the terminal receives the intended transmission and transmissions from NB - <NUM> co-channel beams such that the received signal at a user terminal can be modelled using (<NUM>) as
<MAT>
In (<NUM>), Υn is a complex-valued channel gain that is a function of the antenna gain from the nth beam's feed in the direction of the user terminal under consideration. Here, {εn, δfn, θn} represents the normalized differences in arrival times, carrier frequencies and carrier phases between the NB co-frequency beams at the receiver. In this example, downlink noise n(t) is assumed as an Additive White Gaussian Noise (AWGN) with a single-sided Power Spectral Density (PSD) level of N<NUM> (Watt/Hz). The uplink noise may be assumed to be negligible relative to the downlink noise, a situation achieved through proper satellite link parameters including the size of the transmit antenna. Finally, it is assumed that any on-board High-Power Amplifiers (HPAs) have small nonlinear impact at the user terminals.

Without limitation, per statistical decision theory, a set of sufficient statistics can be generated at the output of a filter matched to the desired signal, labelled as nd, then sampled at the symbol rate Ts,nd, or x((k + εnd) Ts,nd), where
<MAT>
and
<MAT>
is the phase associated with the complex-valued channel gain γnd. To characterize the effective CCI channel response, substitute (<NUM>) into (<NUM>) to yield
<MAT>
where
<MAT>
is the spatial contribution, while ηn,nd(t<NUM>, t<NUM>) represents the time-varying impulse response due to the temporal contribution of CCI. In (<NUM>),
<MAT>
and
<MAT>.

Focusing on the pulse shaping that satisfies the Nyquist criterion of zero Inter-Symbol Interference (ISI), such as bandwidth-efficient Root-Raised Cosine (RRC) pulses, used in the widely adopted DVB-S2X satellite standard. Thus, sampling the matched filter output in (<NUM>) at the correct sampling instant yields
<MAT>
where Ln denotes the memory-span associated with CCI. From (<NUM>), it can be inferred that the desired symbols at the matched filter output are affected by CCI coming from NB - <NUM> beams, in addition to Gaussian noise. It can also be inferred that CCI has memory due to the interfering signals combining asynchronously. The memory effects can be made worse due to different symbol rates and/or different roll-off factors employed by the different co-channel beams.

<FIG> illustrates a block diagram of a Soft-In-Soft-Out (SISO) Iterative Soft-In-Soft-Out (IDAC) receiver according to various embodiments.

A Soft-In-Soft-Out (SISO) Iterative Soft-In-Soft-Out (IDAC) receiver <NUM> implements a plurality of Soft-In-Soft-Out (SISO) frameworks <NUM>, <NUM>' and <NUM>". The count of SISO frameworks may vary. For brevity, the framework <NUM> is further elaborated below. However, each of the frameworks <NUM>', <NUM>" function in a manner similar to the framework <NUM>.

The framework <NUM> performs joint detection with a SISO DAC detector <NUM> along with decoding with a FEC decoder <NUM> (after deinterleaving with a deinterleaver <NUM>) is applied in an iterative fashion to recover the information bits intended for a user terminal. An outer or global iteration begins by processing a composite signal <NUM> including a desired signal and interfering signal. The outer or global iteration processes the interfering signal by employing the most robust signal in the joint CCI SISO DAC detector <NUM>, while assuming equally likely a priori information <NUM>, <NUM>, <NUM> for the interferer signal, the desired signal and any additional interfering signal being processed jointly. The Iterative Divide-And-Conquer Detection (IDAC), detailed above, provides soft-information about CCI in the form of the symbol A Posteriori Probabilities (APPs) <NUM>, <NUM>, <NUM> which are transformed to bit Log-Likelihood Ratios (LLRs) using the bit-to-symbol mapping rule employed at the transmitter.

These bit LLRs are in turn deinterleaved by the deterleaver <NUM> and input to the FEC decoder <NUM> as a decoding input <NUM>. The FEC decoder <NUM> subsequently generates LLR soft-estimates of the interfering signal's information bits. These are converted to extrinsic information by subtracting the LLRs at the input to the FEC decoder <NUM>. The receiver <NUM> immediately uses this extrinsic information as a posteriori probability <NUM>, <NUM>, <NUM> for processing the composite signal <NUM> employing the next most robust signal, thereby incorporating the latest information from the previous signal's FEC decoder, during the same outer iteration, leading to faster convergence.

At the completion of an outer iteration, the receiver has the APP <NUM>, <NUM>, <NUM> estimates for all the signals being jointly processed and can use them during the next outer iteration as a priori information <NUM>, <NUM>, <NUM>. As such the APP of a first iteration is the a priori information for the next iteration. Each framework may use the APP in succession or in parallel. For example, the receiver <NUM> uses the APP generated by the framework <NUM> in succession for the framework <NUM>', and the APP generated by the framework <NUM>' is used in succession for the framework <NUM>". In a parallel implementation (not shown) of the receiver, the APP of an iteration is not used by the plurality of frameworks within the iteration.

The above framework can be applied to systems employing either Simultaneous Decoding (SD) or Simultaneous Non-unique Decoding (SND) methods. In SD, after a certain maximum number of global iterations, the hard decisions provided by two or more decoders is multiplexed by multiplexor <NUM> to form an estimate of the desired symbols <NUM> that may be converted to the user's information bits, for example, in a splitter <NUM>. In SND, after a certain maximum number of global iterations, the hard decisions provided by only a single FEC decoder provides an estimate of the desired symbols <NUM> that may be converted to the user's information bits, for example, in the splitter <NUM>. In SND, the multiplexor <NUM> may be eliminated.

Using the analysis above, a useful formulation is disclosed for IDAC detection. It is based on a stacked construction that models the spatial and temporal contributions of the CCI in multibeam satellite systems on the forward link, namely from the gateway to the user terminals. The kth time-instant of the MF output x[k] of (<NUM>), received in the ndth beam, is described as
<MAT>
where hl,nd [k] is a stacked row-vector containing the channel coefficients associated with each of the neighboring co-channel interfering beams and al,nd [k] is a stacked column-vector that models the corresponding symbols serviced by the interfering beams, defined as
<MAT>
and
<MAT>
respectively. The individual row-vector hl,n [k] in (<NUM>) is in turn composed of a vector containing the spatial and temporal coefficients belonging to the nth beam with single-sided memory of Ln (see for example, <NUM>, <NUM>, <NUM> in <FIG>) symbols, outlined in (<NUM>), and expressed as
<MAT>
In (<NUM>), an[k, Ln] is a column-vector containing the individual interfering symbols from the nth beam or
<MAT>.

The receiver implements a SISO Divide-And-Conquer (DAC) detector of CCI which partitions the interfering symbols into three smaller groups depending on the intensity of their interference levels. These smaller groups use different methods of contributing to the APP computation. The first is the Noise-Floor (NF) group whose elements are incorporated only through their powers. The second is the Subtractive-Cancellation (SC) group which is incorporated in the SISO DAC APP module via first- and second-order moments, derived from a priori probabilities.

The third group is based on the Optimal-Bayesian (OB) method contributing to the SISO DAC APP module using the a priori probability mass function (pmf) of the interfering symbols from within the OB group only. To start the kth time-instant of the MF output x[k] of (<NUM>) is equivalently expressed as
<MAT>
where the elements of al,nd [k] is partitioned into three groups,
<MAT>
and
<MAT>
are the corresponding spatial and temporal CCI channel coefficients extracted from hl,nd [k]. Based on the partitioned expression (<NUM>), the proposed SISO DAC APP module, PDAC(and,k|x[k]), is mathematically expressed as
<MAT>
where pDAC(·) is the likelihood function associated with observing x[k] given the desired and interfering symbols and P(·) is the a priori pmf corresponding to the symbols computed based on the individual FEC decoders. In (<NUM>), the likelihood function pDAC(·) assumes that x[k] is a random variable that retains a Gaussian density expression or
<MAT>
where
<MAT>
is the soft CCI estimate arising from the SC group that is subtracted and is computed as
<MAT>
Also, the likelihood expression in (<NUM>) contains the variances from the SC and NF interfering groups,
<MAT>
and
<MAT>
respectively, obtained by
<MAT>
and
<MAT>.

Extensive performance evaluations demonstrate the effectiveness of the IDAC receiver. The simulation setup implements the system model described previously and employs Low-Density Parity Check (LDPC) codes for FEC as well as the modulation formats defined in the DVB-S2X standard. RRC filters with a rolloff of <NUM> are considered at the transmitters for pulse-shaping and at their corresponding receivers for matched filtering. It is assumed that the satellite transponders are operated in a single-carrier per-HPA mode with the operating point causing small nonlinear distortion at the user terminals. It is also assumed that a multibeam system is employing aggressive frequency reuse, and as such the channel gains from a particular beam in the direction of a user terminal located in a neighboring co-channel beam are severe. This results in CCI at the user terminal which can be as high as C/I = <NUM> dB, i.e., of equal strength, as considered in the performance evaluations. In a multibeam system, a user's receiver may experience a substantial amount of CCI with memory due to the desired signal and interference arriving at the user terminal asynchronously with some relative delay.

<FIG> illustrates a coded PER of DVB-S2X 16APSK with code rate <NUM>/<NUM> when interfered by QPSK with rate R<NUM> at different levels of timing offset (TO) according to various embodiments.

<FIG> starts with an examination of the Packet Error Rate (PER) performance in the presence of CCI and AWGN. <FIG> documents PER versus Es/N<NUM> for a desired user employing 16APSK with the rate <NUM>/<NUM> LDPC code. In this scenario, 16APSK symbols intended for the desired user arrive at the user terminal in the presence of a strong co-channel interferer at C/I = <NUM> dB that employs QPSK MODCOD with rates of <NUM>/<NUM> or <NUM>/<NUM>. A significant amount of distortion experienced at the decoder input will cause the LDPC decoding to fail without CCI mitigation. <FIG> also illustrates the inability of state-of-the-art (SOA) memoryless CCI mitigation techniques popular in the literature to handle asynchronous reception. As an example, when the offset between the desired signal and the interferer is <NUM>% of Ts, performance with the memoryless solution degrades by more than <NUM> dB and a delay of <NUM>% relative to Ts causes the receiver to become ineffective. These limitations motivate the need for the innovative, low-complexity and modular IDAC framework disclosed in the present teachings.

As is evident in <FIG>, the receiver of the present teachings does not suffer from performance degradation even at delays as high as <NUM>% of Ts and approaches no-CCI performance. Further, the present teachings are just as effective when the interfering beam carries QPSK with the weaker code rate of <NUM>/<NUM>. The low-complexity of the present teachings is particularly noteworthy in light of the significant CCI memory span and APSK modulation cardinality. The impressive performance offered by the present teachings allows user terminals located at the edges of co-frequency beams to benefit from high spectral efficiencies offered by APSK MODCODs.

<FIG> illustrates an information-theoretic achievable-rate region for 16APSK when interfered by QPSK at C/I = <NUM> dB and Es/N<NUM> = <NUM> dB), according to various embodiments.

<FIG> illustrates a map out of the information-theoretic rate regions supported at a user terminal when 16APSK and QPSK symbols are transmitted on co-channel beams. These report mutual information between the transmitted modulated symbols and the received symbols at Es/N<NUM> = <NUM> dB. By adopting that with the SND method, only 16APSK symbols carry information for the targeted user which the user terminal can recover by jointly processing the desired signal and the interfering signal. The rate region has several points of interest that are discussed here; the point labelled A denotes the maximum rate R<NUM> at which 16APSK symbols can be reliably received at the user terminal when there is no CCI and is approximately <NUM> bits-per-symbol.

Conversely, the point B denotes the maximum rate R<NUM> at which QPSK symbols can be reliably received at the same user terminal, without any CCI and is <NUM> bits-per-symbol. Points C and D are the maximum rates possible when CCI is unmitigated and treated as noise at the receiver, these rates are R<NUM>= <NUM> bits-per-symbol for 16APSK and R<NUM>= <NUM> bits-per-symbol for QPSK, respectively. It is clear from these results that CCI, if left unmitigated can impose a significant penalty on the spectral efficiency. Information theory also indicates that as long as <NUM> < R<NUM> ≤ <NUM>, it is possible to receive 16APSK at its maximum rate at the user terminal in the presence of CCI by jointly processing both signals. In particular, QPSK can be recovered first and can subsequently assist in recovering the 16APSK symbols. As an example, the curve marked in green diamond indicates that 16APSK can be signaled at its maximum rate of <NUM> bits-per-symbol when the interfering QPSK signal has rates R<NUM>= <NUM> × {<NUM>/<NUM>, <NUM>/<NUM>, <NUM>/<NUM>, <NUM>/<NUM>} by jointly processing both signals at the user terminal.

It is also interesting to visualize how the rates promised by information-theory compare with performance achievable with the IDAC receiver employing finite-length DVB-S2X LDPC codes and operating under the realistic assumption of CCI with memory. Towards this end, extensive PER performance simulations were conducted by transmitting progressively more spectrally efficient QPSK MODCODs on the interfering signal by increasing its code rate to <NUM>/<NUM>, <NUM>/<NUM> and <NUM>/<NUM>. As done previously, C/I = <NUM> dB and timing offset of <NUM>% of Ts were assumed. Results indicate that. similar to <FIG>, there is no noticeable performance loss relative to a no-CCI scenario. This implies that the IDAC receiver does not penalize the interfering user to employ its most spectrally efficient MODCOD. Furthermore, the achievable rate for 16APSK of <NUM> bits-per-symbol, when using <NUM>/<NUM> code, is quite close to the information-theoretic maximum of <NUM> bits-per-symbol. This is also illustrated in <FIG>, where the Es/N<NUM> for the coded simulations corresponds to a PER of <NUM>-<NUM>. Hence, it is easy to infer from these results that the IDAC receiver offers a capacity-approaching solution to handling severe CCI at the user terminal, even when confronted with symbol asynchronism.

Claim 1:
A communications apparatus (<NUM>) comprising:
a receiver (<NUM>) configured to receive a composite signal (<NUM>) comprising a desired signal (<NUM>) and interferer signals (<NUM>, <NUM>), wherein the desired signal (<NUM>) comprises desired symbols and the interferer signals (<NUM>, <NUM>) comprise interferer symbols, and the interferer signals (<NUM>, <NUM>) are caused by co-channel beams; and
N frameworks (<NUM>), each framework comprising
a detector (<NUM>) configured to partition the interferer symbols based on an interference severity into a dominant group and a non-dominant group, and to generate A Posteriori Probabilities, APP, (<NUM>, <NUM>, <NUM>) of the desired symbols and the interferer symbols, wherein the non-dominant group comprises a Noise-Floor, NF, group and a Subtractive-Cancellation, SC, group, and the dominant group comprises an Optimal-Bayesian, OB, group,
wherein the detector (<NUM>) of each of the N frameworks (<NUM>) is configured to generate the APP (<NUM>, <NUM>, <NUM>) based on a feedback of a priori probabilities (<NUM>, <NUM>, <NUM>) from each of the N frameworks (<NUM>), and wherein the detector (<NUM>) is configured to generate the APP (<NUM>, <NUM>, <NUM>) based on: the NF group via a power of each member; the SC group via first- and second-order moments derived from the a priori probabilities (<NUM>, <NUM>, <NUM>); and the OB group via a probability mass function, pmf;
wherein the detector (<NUM>) is Soft-In Soft-Out Devide-And-Conquer, SISO DAC, detector;
wherein the a priori probabilities (<NUM>, <NUM>, <NUM>) comprise the APP (<NUM>, <NUM>, <NUM>) generated on the previous iteration of the N frameworks (<NUM>).