This paper explores the tradeoff between covert communication capacity and secret key requirements over discrete memoryless channels (DMCs). We focus on settings where under a covertness constraint both communication and key rates are measured as the number of bits per square root of the block-length. While previous work has identified the maximum covert communication rates and the corresponding minimum key rates needed to achieve them, our study characterizes the minimum key rates necessary for all of desired covert communication rates. In equivalent terms, we determine, for any given key rate, the set of achievable covert rates. This relationship defines what we call the covert capacity-key tradeoff.Our analysis reveals several new insights. In scenarios where only small key rates are available and the adversary has a stronger channel than the intended receiver, binary signaling is optimal—regardless of the specific channel characteristics or input alphabets. In these cases, the covert capacity increases linearly with the available key rate. In other cases and for larger key rates, the covert capacity-key tradeoff grows sublinearly.We also extend our findings to multi-access channels (MACs) with binary inputs.

This paper identifies the Stein exponent of two distributed detection (binary hypothesis testing) setups with limited communication over a discrete memoryless channel (DMC). In the first setup, the DMC can only be used k(n) times, where k(n) grows sublinearly in the length of the observations n. In the second setup, the DMC can be used n times, however a block-input cost constraint Cnis imposed and Cngrows sublinearly in n. The optimal Stein exponent coincides for both setups and depends on whether the DMC is partially-connected, i.e., one of the output symbols can only be induced by a strict subset of the input symbols, or fully-connected. For partially-connected DMCs, the optimal Stein exponent of our setups coincides with the optimal Stein exponent (identified by Han and by Shalaby and Papamarcou) for the scenario where the sensor can communicate a sublinear (in n) number of bits to the decision center and communication is over a noiseless link. In contrast, for fully-connected DMCs the optimal Stein exponent collapses and is given by the optimal Stein exponent of the local test at the decision center. In this case, the sensor and the DMC do not help in improving the Stein exponent. Our results hold for general independent and identically distributed sources.

The fundamental limit of Semantic Communications (joint source-channel coding) is established when the transmission needs to be kept covert from an external warden. We derive information-theoretic achievability and matching converse results and we show that source and channel coding separation holds for this setup. Furthermore, we show through an experimental setup that one can train a deep neural network to achieve covert semantic communication for the classification task. Our numerical experiments confirm our theoretical findings, which indicate that for reliable joint source-channel coding, the number of transmitted source symbols can only scale as the square-root of the number of channel uses.

In this paper, we caracterize the fundamental limits of a communication system with three users (i.e., three transmitters) and a single receiver where communication from two covert users must remain undetectable to an external warden. Our results show a tradeoff between the highest rates that are simultaneously achievable for the three users. They further show that the presence of a non-covert user in the system can enhance the capacities of the covert users under stringent secret-key constraints. To derive our fundamental limits, we provide an information-theoretic converse proof and present a coding scheme that achieves the performance of our converse result. Our coding scheme is based on multiplexing different code phases, which seems to be essential to exhaust the entire tradeoff region between the rates at the covert and the two non-covert users. This property is reminiscent of the setup with multiple non-covert users, where multiplexing is also required to exhaust the entire rate-region.

This paper studies the problem of distributed detection (binary hypothesis testing) over a discrete memoryless channel (DMC) under the constraint that an eavesdropping adversary should not be able to determine whether communication is ongoing or not, i.e., communication over the DMC has to remain covert. The main contribution of the paper is an upper bound on the largest possible Stein exponent, showing that it cannot exceed the largest exponent achievable under zero-rate communication over a noise-free link. In interesting special cases, the upper bound is achieved by a local test at the decision center that completely ig-nores the communication. In these cases, the covertness constraint renders communication useless for improving the Stein exponent.

The paper presents exponentially-strong converses for source-coding, channel coding, and hypothesis testing problems. More specifically, it presents alternative proofs for the well-known exponentially-strong converse for almost lossless source-coding with side-information and for channel coding over a discrete memoryless channel (DMC). These alternative proofs are solely based on a change of measure argument on the sets of conditionally or jointly-typical sequences that result in a correct decision, and on the analysis of these measures in the asymptotic regime of infinite blocklengths. The paper also presents new exponentially-strong converses for the$K$-hop hypothesis testing against independence problem with certain Markov chains and for the two-terminal$L$-round interactive compression problem with$J\geq 1$distortion constraints that depend on both sources and both reconstructions. For this latter problem, the exponentially-strong converse result states that whenever the rates lie outside the vanishing-excess-distortion-probability rate-region, then the sum of the$J$excess distortion probabilities asymptotically exceeds 1 or tends to 1 exponentially fast in the blocklength. (When the sum of the excess distortion probabilities exceeds 1, then a larger rate-distortion region is shown to be achievable.) The considered$L$-round$J$-distortion interactive source coding problem includes as special cases the Wyner-Ziv problem, the interactive function computation problem, and the compression with lossy common reconstruction problem. The new strong converse proofs for lossy compression and distributed hypothesis testing are derived using similar change of measure arguments as mentioned earlier and by additionally proving that certain Markov chains involving auxiliary random variables hold in the asymptotic regime of infinite blocklengths.

This paper establishes the fundamental limits of a two-user single-receiver system where communication from User 1 (but not from User 2) needs to be undetectable to an external warden. Our fundamental limits show a tradeoff between the highest rates (or square-root rates) that are simultaneously achievable for the two users. Moreover, coded time-sharing for both users is fundamentally required on most channels, which distinguishes this setup from the more classical setups with either only covert users or only non-covert users. Interestingly, the presence of a non-covert user can be beneficial for improving the covert capacity of the other user.

We study a distributed binary hypothesis testing (HT) problem with communication and security constraints, involving three parties: a remote sensor called Alice, a legitimate decision center called Bob, and an eavesdropper called Eve, all having their own source observations. In this system, Alice conveys a rate-R description of her observations to Bob, and Bob performs a binary hypothesis test on the joint distribution underlying his and Alice’s observations. The goal of Alice and Bob is to maximize the exponential decay of Bob’s miss-detection (type-II error) probability under two constraints: Bob’s false-alarm (type-I error) probability has to stay below a given threshold and Eve’s uncertainty (equivocation) about Alice’s observations should stay above a given security threshold even when Eve learns Alice’s message. For the special case of testing against independence, we characterize the largest possible type-II error exponent under the described type-I error probability and security constraints.

We consider a Non Orthogonal Multiple Access (NOMA)-based wireless network where User Equipments (UEs) are connected to a Base Station (BS) equipped with a Mobile Edge Computing (MEC) server. The UEs can process their buffered data packets with strict delay either locally or by offloading them to the base station's MEC server. In order to minimize the dropped packets due to buffer overflow or delay violation, the scheduling-offloading problem is formulated as a Markov Decision Process (MDP) and solved using various optimal and Reinforcement Learning (RL) algorithms. The output of each policy is, for each user, the number of packets to be processed and the type of processing (locally or remotely). The decisions rely on the channel state information and the buffers states. The numerical results show the great advantage of using NOMA compared to Orthogonal Multiple Access (OMA). We further analyze the scalability capabilities of the used algorithms, which validates the benefits of using Deep Reinforcement Learning (DRL) techniques.

We consider a multi-hop distributed hypothesis testing problem with multiple decision centers (DCs) for testing against independence and where the observations obey some Markov chain. For this system, we characterize the fundamental type-II error exponents region, i.e., the type-II error exponents that the various DCs can achieve simultaneously, under expected rate-constraints. Our results show that this fundamental exponents region is boosted compared to the region under maximum-rate constraints, and that it depends on the permissible type-I error probabilities. When all DCs have equal permissible type-I error probabilities, the exponents region is rectangular and all DCs can simultaneously achieve their optimal type-II error exponents. When the DCs have different permissible type-I error probabilities, a tradeoff between the type-II error exponents at the different DCs arises. New achievability and converse proofs are presented. For the achievability, a new multiplexing and rate-sharing strategy is proposed. The converse proof is based on applying different change of measure arguments in parallel and on proving asymptotic Markov chains. For the special casesK∈ {2, 3}, and for arbitraryK≥ 2 when all permissible type-I error probabilities at the various DCs are equal, we provide simplified expressions for the exponents region; a similar simplification is conjectured for the general case.

We study distributed binary hypothesis testing with a single sensor and two remote decision centers that are also equipped with local sensors. The communication between the sensor and the two decision centers takes place over three links: a shared link to both centers and an individual link to each of the two centers. All communication links are subject to expected rate constraints. This paper characterizes the optimal exponents region of the type-II error for given type-I error thresholds at the two decision centers and further simplifies the expressions in the special case of having only the single shared link. The exponents region illustrates a gain under expected rate constraints compared to equivalent maximum rate constraints. Moreover, it exhibits a tradeoff between the exponents achieved at the two centers.

The main contribution of this paper is a strong converse result for K-hop distributed hypothesis testing against independence with multiple (intermediate) decision centers under a Markov condition. Our result shows that the set of type-II error exponents that can simultaneously be achieved at all the terminals does not depend on the maximum permissible type-I error probabilities. Our strong converse proof is based on a change of measure argument and on the asymptotic proof of specific Markov chains. This proof method seems to be useful also in other applications, and is appealing because it does not require resorting to variational characterizations or blowing-up methods as in previous related proofs.

The paper studies distributed binary hypothesis testing over a two-hop relay network where both the relay and the receiver decide on the hypothesis. Both communication links are subject to expected rate constraints, which differs from the classical assumption of maximum rate constraints. We exactly characterize the set of type-II error exponent pairs at the relay and the receiver when both type-I error probabilities are constrained by the same value$\epsilon > 0$. No tradeoff is observed between the two exponents, i.e., one can simultaneously attain maximum type-II error exponents both at the relay and at the receiver. For$\epsilon_{1}\neq\epsilon_{2}$, we present an achievable exponents region, which we obtain with a scheme that applies different versions of a basic two-hop scheme that is optimal under maximum rate constraints. We use the basic two-hop scheme with two choices of parameters and rates, depending on the transmitter's observed sequence. For$\epsilon_{1}=\epsilon_{2}$, a single choice is shown to be sufficient. Numerical simulations indicate that extending to three or more parameter choices is never beneficial.

Cascaded binary hypothesis testing is studied in this paper with two decision centers at the relay and the receiver. All terminals have their own observations, where we assume that the observations at the transmitter, the relay, and the receiver form a Markov chain in this order. The communication occurs over two hops, from the transmitter to the relay, and from the relay to the receiver. Expected rate constraints are imposed on both communication links. In this work, we characterize the optimal type-II error exponents at the two decision centers under constraints on the allowed type-I error probabilities. Our recent work characterized the optimal type-II error exponents in the special case when the two decision centers have same type-I error constraints and provided an achievability scheme for the general setup. To obtain the exact characterization for the general case, in this paper we provide a new converse proof as well as a new matching achievability scheme. Our results indicate that under unequal type-I error constraints at the relay and the receiver, a tradeoff arises between the maximum type-II error probabilities at these two terminals. Previous results showed that such a tradeoff does not exist under equal type-I error constraints or under general type-I error constraints when a maximum rate constraint is imposed on the communication links.

We investigate the testing-against-independence problem over a cooperative MAC with two sensors and a single detector under an average rate constraint on the sensors-detector links. For this setup, we design a variable-length coding scheme that maximizes the achievable type-II error exponent when the type-I error probability is limited to ϵ. Similarly to the single-link result, we show here that the optimal error exponent depends on ϵ and that variable-length coding allows to increase the rates over the optimal fixed-length coding scheme by the factor (1 − ϵ)−1.

This paper proposes a joint packet scheduling and computation offloading policy for an Energy Harvesting (EH) mobile terminal wirelessly connected to a Base Station (BS) when the channel between the mobile and the BS is unavailable at the mobile side. The mobile terminal has to decide if its packet related to one application is computed either locally or remotely by the BS within a strict delay imposed by this application without knowing the channel in advance. Our objective is to guarantee reliable communication by minimizing the packet loss. This packet loss is due to butter overflow, strict delay violation and channel mismatch. We formulate the problem using a Markov Decision Process (MDP) and we propose and implement the optimal deterministic offline policy to solve it. This optimal policy decides: (i) the execution location (locally or remotely), (ii) the number of packets to be executed and (iii) the corresponding transmission power. This policy offers a dramatic increase in the number of executed packets and a significant energy saving.

The paper considers a coded caching setup with two libraries and where only one of them needs to be kept secret from an external eavesdropper. We provide upper and lower bounds on the secrecy rate-memory tradeoff for systems with K = 2 or K = 3 receivers. Our bounds are tight in some regimes and show that the standard (non-secure) coded caching upper bound can be approached for a wide range of parameters. In some cases, the proposed upper bound on the secrecy rate-memory tradeoff is even lower than the lower bound for standard coded caching. The reason is that in our setup the ratio of receivers requesting secure files over those requesting nonsecure files is fixed and known to everyone in advance. The transmitter can thus adjust the contents stored in the cache memories to this ratio.

This paper derives upper and lower bounds on the secrecy capacity-memory tradeoff of a wiretap erasure broadcast channel (BC) with Kw weak receivers and Ks strong receivers, where weak receivers and strong receivers have the same erasure probabilities and cache sizes, respectively. The lower bounds are achieved by the schemes that meticulously combine joint cache-channel coding with wiretap coding and key-aided onetime pads. The presented upper bound holds more generally for arbitrary degraded BCs and arbitrary cache sizes. When only weak receivers have cache memories, upper and lower bounds coincide for small and large cache memories, thus providing the exact secrecy capacity-memory tradeoff for this setup. The derived bounds further allow us to conclude that the secrecy capacity is positive even when the eavesdropper is stronger than all the legitimate receivers with cache memories. Moreover, they show that the secrecy capacity-memory tradeoff can be significantly smaller than its non-secure counterpart, but it grows much faster when cache memories are small. This paper also presents a lower bound on the global secrecy capacity-memory tradeoff where one is allowed to optimize the cache assignment subject to a total cache budget. It is close to the best known lower bound without secrecy constraint. For small total cache budget, the global secrecy capacity-memory tradeoff is achieved by assigning all the available cache memory uniformly over all the receivers if the eavesdropper is stronger than all the legitimate receivers, and it is achieved by assigning the cache memory uniformly only over the weak receivers if the eavesdropper is weaker than the strong receivers.

We consider a K-receiver wiretap broadcast channel where Kw receivers are weak and have cache memories and Ks receivers are strong and have no cache memories. We derive an upper bound on the secrecy rate-memory tradeoff under a joint secrecy constraint and under decentralized caching. In contrast to previous works, prefetching in our scheme is purely decentralized and receivers randomly sample from a random key stream available at the transmitter and from the files in a library. For small cache sizes, the performance of our scheme improves with increasing length of the random key stream. For moderate and large cache sizes, a small key stream suffices to perform close to the information-theoretic limit of the system.

This paper investigates the resource scheduling minimizing the packet loss when the wireless communication system operates with Energy Harvesting (EH) based devices. The packet loss occurs when the buffer is overflowed and when the queued packet is older than a certain pre-defined threshold. We so consider a strict delay constraint rather than an average delay constraint. The associated optimization problem can be modeled as Markov Decision Problem (MDP) where the actions are the number of packets sent on the known channel at each slot. The optimal deterministic offline policy is exhibited through dynamic programming techniques, i.e. Value Iteration (VI) algorithm. We show the gain in the number of transmitted packets and the consumed energy is substantial compared to a naive policy which forces the system to send the maximum number of packets using the available energy in the battery.

We derive upper and lower bounds on the secure capacity-memory tradeoff of the K-user (K > 2) wiretap erasure broadcast channel where Kwreceivers are weak and have cache memories of equal size, and Ksreceivers are strong and have no cache. The bounds coincide for small and large cache memories. The lower bound also exhibits that cache memories provide larger gains under a secrecy constraint than without such a constraint. The lower bound is based on a joint cache-channel coding scheme that simultaneously exploits the cache contents and the channel statistics. Moreover, we show for the two-user scenario that in the regime of small cache memories, the capacity-memory tradeoff is larger when only the weaker receiver has cache memory than when this cache memory is split equally among the two receivers.

The paper studies the wiretap erasure broadcast channel (BC) with an external eavesdropper when the legitimate receivers have cache memories. Various secure coding schemes are proposed for a scenario where Kwweak receivers have same erasure probabilities and Ksstrong receivers have same erasure probabilities. The coding schemes achieve the cache-aided secrecy capacity when only weak receivers have cache memories and this cache memory is either small or large. They also allow to conclude the following: 1) Under a total cache budget it is often beneficial to assign the cache memories unequally between strong and weak receivers. 2.) Joint cache-channel coding is necessary to attain the optimal performance. 3.) The secrecy capacity can be positive even when the eavesdropper is stronger than the legitimate receivers.

We derive upper and lower bounds on the secure capacity-memory tradeoff of the two-user wiretap erasure BC with cache memory at the weaker receiver. The bounds coincide when the cache memory exceeds a given threshold. The lower bound also exhibits that cache memories provide larger gains under a secrecy constraint than without such a constraint. Moreover, for a large set of parameters the capacity-memory tradeoff is larger if only the weaker receiver has cache memory than when this cache memory is split equally among the receivers. The lower bound is based on a joint cache-channel coding scheme that simultaneously exploits the cache contents and the channel statistics. Such a joint design yields significant gains over a separation-based design.

Stopping sets for MDS-based product codes under iterative row-column algebraic decoding are analyzed in this paper. A union bound to the performance of iterative decoding is established for the independent symbol erasure channel. This bound is tight at low and very low error rates. We also proved that the performance of iterative decoding reaches the performance of Maximum-Likelihood decoding at vanishing channel erasure probability. Numerical results are shown for product codes at different coding rates.

The numerous features installed in recent mobile phones opened the door to a wide range of applications involving localization, storage, photo and video taking and communication. A significant number of applications involve user generated content and require intensive processing which limits dramatically the battery lifetime of featured mobile terminals. Mobile cloud computing has been recently proposed as a promising solution allowing the mobile users to run computing-intensive and energy parsimonious applications. This new feature requires new functionalities inside the cellular network architecture and needs appropriate resource allocation strategies which account for computation and communication in the same time. In this paper we present promising options to upgrade 4G architecture to support these new features. We also present two resource allocation strategies accounting for both computation and radio resources. These strategies are devised so that to minimize the energy consumption of the mobile terminals while satisfying predefined delay constraints. We compare online learning based solutions where the network adapts dynamically to the application that is run on mobile terminals, and pre-calculated offline solutions which are employed when a certain level of knowledge about the application and the channel conditions is available at the network side. We show, that even with imperfect knowledge about the application, pre-calculated offline strategies offer better performance in terms of energy consumption of mobile terminals.

In this paper, we address computation offloading problem from mobile users to their serving small cell base stations. These base stations can be endowed with some computational capabilities providing thus users proximity access to the cloud services. We aim to jointly optimize the radio resource scheduling and computation offloading in order to minimize the average energy consumed by all the users terminals to process their mobile applications under average delay constraints tolerated by these applications. We investigate for this problem offline and online dynamic programming approaches and we devise deterministic solutions to find the optimal scheduling-offloading policy. The proposed solutions select only one user for scheduling, hence offloading, and decides for the other users either local processing or staying idle according to their application rates. We show that the offline strategy is optimal in terms of energy saving compared to the online strategy. It can benefit from prior knowledge on the channel statistics and the application properties to satisfy the users requirements.

In wireless cellular networks, multiple scenarios involve the communication between devices located in the same vicinity. These links can be offloaded to a device to device (D2D) underlay which is controlled by the cellular infrastructure. Such an option alleviates the load on the base stations and saves spectrum resources for downlink connections. In this paper, we investigate the impact of D2D communications on the capacity of a cellular network from two directions: average link capacity and coverage. We present a stochastic geometry based framework which captures both cellular and device to device links. Based on this framework, we quantify the enhancements offered by D2D underlay in terms of system coverage, average link capacity and spectrum usage.

This paper studies a Gaussian two-way relay channel where two communication nodes exchange messages with each other via a relay. It is assumed that all nodes operate in half-duplex mode without any direct link between the communication nodes. A compress-and-forward relaying strategy using nested lattice codes is first proposed. Then, the proposed scheme is improved by performing layered coding: A common layer is decoded by both receivers, and a refinement layer is recovered only by the receiver that has the best channel conditions. The achievable rates of the new scheme are characterized and are shown to be higher than those provided by the decode-and-forward strategy in some regions.

Parallel two-way relay channel models a cooperative communication scenario where a relay helps two terminals to exchange their messages over independent Gaussian channels. For the single channel case, we have shown previously that lattice-based physical layer network coding achieves the same rate as compress-and-forward scheme with a random coding strategy. A direct extension of this lattice-based scheme to parallel Gaussian channel is to repeat the same strategy for each subchannel. However this approach is not scalable with the number of sub-channels since the complexity of the scheme becomes prohibitive when a large number of sub-channels is employed. In this contribution, we investigate a lattice-based physical layer network coding scheme where the relay jointly processes all the sub-channels together. We characterize the rate region allowed by our coding scheme and assess the performance penalty compared to the separate channel processing approach.

Recently, Delay-Tolerant Space-Time Codes (DT-STCs) have been designed for cooperative communications. They are optimal in synchronous transmission and preserve their full-diversity order for arbitrary delays in asynchronous case. In this paper, we investigate these DT-STCs in femtocell networks where Femtocell Access Points can assist Macrocell Base Stations to transmit data information to users. The delays can be randomly introduced by the MBSs-FAPs backhaul links. We consider concatenated DT-STCs based on previous designs and we address their optimal and sub-optimal decoding schemes. In order to reduce the complexity, we propose a new sub-optimal algorithm based on successive sub-codewords decoding. Simulation results show that the proposed decoder achieves good performance-complexity tradeoff.

Perfect space-time codes (STC) are optimal codes in their original construction for multiple-input multiple-output (MIMO) systems. Based on cyclic division algebras (CDA), they are full-rate, full-diversity codes, have non-vanishing determinants (NVD) and hence achieve diversity-multiplexing tradeoff (DMT). In addition, these codes have led to optimal distributed space-time codes when applied in cooperative networks under the assumption of perfect synchronization between relays. However, they lose their diversity when delays are introduced and thus are not delay-tolerant. In this paper, using the cyclic division algebras of perfect codes, we construct new codes that maintain the same properties as perfect codes in the synchronous case. Moreover, these codes preserve their full-diversity in asynchronous transmission.

Perfect Space-Time Codes (STC) are full-rate, full-diversity codes originally proposed for Multiple Input Multiple Output (MIMO) systems. Based on Cyclic Division Algebras (CDA), they have non-vanishing determinants and hence achieve the Diversity-Multiplexing Tradeoff (DMT). In addition, these codes have led to optimal distributed Space-Time Codes when applied in cooperative networks under the assumption of perfect synchronization between relays. However, they lose their diversity when delays are introduced and thus are not delay-tolerant. In this paper, using the cyclic division algebras of perfect codes, we construct new codes that maintain the same properties as perfect codes in the synchronous case. Moreover, these codes preserve their full-diversity in asynchronous transmission.

Distributed space-time codes over two asynchronous relays are considered. First, we show that the space-time code proposed in [1] is suitable for asynchronous transmission over two relays. Using tools from division algebra, we study the quadratic form resulting from its determinant and we prove that this code has a non-vanishing determinant over all constellations carved from Zopf[i], and thus is optimal in the sense of diversity-multiplexing tradeoff [2]. Then, we propose a delay-tolerant code based on the Golden code [3] the full-rate full-diversity information lossless space-time code proposed for the MIMO channel, and we deduce the convenient unitary matrices to obtain the modified code. Applying these matrices to other MIMO codes, namely Tirkkonen-Hottinen [4] and Sezginer-Sari code [5], we infer new delay-tolerant codes. In addition of being suitable for asynchronous relay transmission, all the new codes have the same determinants as the old ones.

In this paper, we introduce two novel low complexity detectors derived from the MAP-DFE detector for MC-CDMA uplink system. By simulation, we show small performance loss while reducing excessively the complexity.

The full rate, full rank golden code showed to overcome all previous codes in (2 x 2) multiple input multiple output (MIMO) uncoded system when decoded with maximum- likelihood (ML) detectors. Therefore, its efficiency motivates us to study the code performance with suboptimal detectors, precisely two detectors based on decision feedback equalizer (DFE) detection. The first one is a DFE detector with preprocessing stage based minimum mean square error generalized DFE (MMSE-GDFE), Lattice reduction (LR) and Vertical-Bell Labs layered space-time (V-BLAST) greedy ordering. The second one is the enhanced maximum a posteriori DFE (E-MAP-DFE) detector. To extend the study for coded systems, other soft output algorithms are presented based on the first detection stage. The key idea of these algorithms is to provide candidate lists for more reliable detection. So, in this context, simulations were carried out to compare the detectors' performance.

In this paper, linear scalable dispersion (LSD) code is investigated for multiple input multiple output multi-carrier code division multiple access (MIMO MC-CDMA) systems. The code already introduced in MIMO systems is extended to the MC-CDMA downlink transmission. It provides a flexible compromise between diversity and spatial multiplexing in Rayleigh and Ricean fading channels; therefore, it realizes high transmission rate while benefiting from transmit diversity. In this context, we show through simulations that LSD scheme improves significantly the performance in different channel conditions

In this paper, multi-user detection (MUD) techniques are investigated for multiple input multiple output multi- carrier code division multiple access (MIMO MC-CDMA) systems. maximum a posteriori decision feedback equalizer (MAP-DFE) already introduced in MIMO systems is extended to the MC-CDMA downlink transmission. This detector cancels the Inter-Symbol Interference (ISI) on the basis of the a posteriori error probability estimation. In this context, we show through simulations that MAP-DFE performance improves significantly compared to other well-known detection techniques such as Minimum Mean Square Error (MMSE) and Block DFE (BDFE).

This paper aims at the system design on the MC-CDMA uplink. In this paper, we compare the performance and the complexity of MC-CDMIA systems with and without iterative detectors and multiple receive antenna arrays. Through extensive computer simulation, we demonstrate that the following four combinations are good solutions: a single-antenna receiver with an iterative PIC detector initialized by the MF and with 3 iterations, a two-antenna receiver with MMSE-MUD or an iterative PIC detector initialized by the MF and with 2 iterations, and a four-antenna receiver with a simple MF detector. Therefore, non-iterative detectors can be used with multiple receive antenna arrays to substitute complicated iterative detectors and it is a promising solution for the 4G up-link MC-CDMA systems where multiple receive antennas are available. In this paper, we have also considered pilot-aided channel estimation with weighted delay profile technique and investigated the impact of channel estimation error on different systems.